A Survey On Empirical Requirements Engineering Research Practices

ȱ
ȱ
TableȱofȱContentsȱ
ȱ
ȱ
PartȱI:ȱREFSQȱ2012ȱWorkshopȱProceedingsȱ ȱ
1ȱ Prefaceȱ 5
2ȱ RequirementsȱEngineeringȱforȱSustainableȱSystemsȱ(RE4SuSy)ȱ 7
3ȱ RequirementsȱEngineeringȱEfficiencyȱWorkshopȱ(REEW)ȱ 47
4ȱ CreativityȱinȱRequirementsȱEngineeringȱ(CreaRE)ȱ 83
5ȱ RequirementsȱPrioritizationȱforȱCustomerȱOrientedȱSoftwareȱDevelopmentȱ(RePriCo)ȱ 129
6ȱ InternationalȱWorkshopȱonȱSoftwareȱProductȱȱManagementȱ(IWSPM)ȱ 181
ȱ ȱ
PartȱII:ȱREFSQȱ2012ȱEmpiricalȱTrack Proceedingsȱ
7ȱ Prefaceȱ 259
8ȱ AliveȱEmpiricalȱStudyȱ 265
9ȱ OnlineȱQuestionnairesȱ 281
10ȱ EmpiricalȱResearchȱFairȱ 311
ȱ ȱ
PartȱIII:ȱREFSQȱ2012ȱDoctoralȱSymposiumȱProceedingsȱ
11ȱ Prefaceȱ 327
12ȱ DoctoralȱSymposiumȱ 333
ȱ
iii

ȱ
ȱ
ȱ
ȱ
ȱ
ȱ
PartI
REFSQ2012WorkshopProceedings
1

1 Preface
Editor
Samuel A. Fricker
Blekinge Institute of Technology, Sweden, samuel.fricker@bth.se
REFSQ 2012 Workshop Proceedings
3

Preface from the RefsQ 2012 Workshops Chair
Samuel A. Fricker
Blekinge Institute of Technology, School of Computing
Campus Gräsvik, 371 79 Karlskrona, Sweden
samuel.fricker@bth.se
Conference workshops are important forum to initiate new research and to develop
young researchers. This is especially true for the International Working Conference
on Requirements Engineering: Foundation for Software Quality (RefsQ) series, which
targets an “I heard it first at RefsQ!” experience. The RefsQ workshops allow re-
searchers to expose their research ideas and early results. Each workshop provides
time and an interested audience from industry and academia to discuss the presented
ideas. In addition, the RefsQ workshops allow young, promising researchers to plan
and implement a researcher meeting for the first time. This experience and the net-
work they develop enable them to actively participate in the research community.
RefsQ 2012 called for proposals of workshops that have the potential to signifi-
cantly advance requirements engineering. Such workshops cover topics that are im-
portant for practice, are new to the field, have controversial viewpoints, and are unsat-
isfactorily understood. The dialogue among participants shall lead to interesting fol-
low-up research, empirical investigations, and industrial practice improvement.
The workshop proposals were evaluated based on the following criteria. A work-
shop should be led by a senior and a junior researcher to transfer knowledge and re-
search culture. Its topic should be novel to enable growth of the field. It should attract
both earlier and new RefsQ participants to enable growth of the community. Its for-
mat should allow generating, rather than only consuming knowledge. Finally, to ena-
ble innovation, established workshops were only accepted if successful previously.
RefsQ 2012 accepted five workshops. The new International Workshop on Re-
quirements Engineering for Sustainable Systems (RE4SuSy) addressed requirements
engineering in the sustainability context, which has become important for our society.
The Requirements Engineering Efficiency Workshop (REEW) was held for the second
time to discuss approaches for increasing requirements engineering efficiency. The
workshop on Creativity in Requirements Engineering (CREARE) was held for the
second time to address requirements engineering in an innovation context. The work-
shop on Requirements Prioritization for Customer Oriented Software Development
(RePriCo) was held for the third time to discuss prioritization of requirements. The
International Workshop on Software Product Management (IWSPM) joined RefsQ for
the first time to discuss approaches for managing software as a product. This proceed-
ings explains the paper selection processes and includes the accepted contributions.
On behalf of the RefsQ organization committee, I would like to thank all workshop
organizers and contributors to their excellent work. The workshops fulfilled their
expectations to our highest satisfaction.
5

2 Requirements Engineering for Sustainable Systems (RE4SuSy)
Editors
Birgit Penzenstadler
Technische Universittät München, Germany, penzenst@in.tum.de
Martin Mahaux
University of Namur, Belgium, martin.mahaux@fundp.ac.be
Camille Salinesi
Université Paris 1 - Sorbonne, France, camille@univ-paris1.fr
Workshop Programme
First International Workshop on Requirements Engineering for Sustainable
Systems (RE4SuSy)
Birgit Penzenstadler, Martin Mahaux, and Camille Salinesi
8
Integrating Energy and Eco-Aware Requirements Engineering in the Development
of Services-Based Applications on Virtual Clouds
Jean-Christophe Deprez, Ravi Ramdoyal, and Christophe Ponsard
13
Making use of scenarios for environmentally aware system design
Konstantin Hoesch-Klohe, and Aditya Ghose
20
Green Requirements Engineering with the GREENSOFT Model Taking the whole
Lifecycle of Software into Account
Eva Kern, Markus Dick, Stefan Naumann, Timo Johann, Matthias Giesselmann,
and Patrick Lang
26
Integrating the Complexity of Sustainability in Requirements Engineering
Martin Mahaux, and Caroline Canon
28
RE4ES: Support Environmental Sustainability by Requirements Engineering
Birgit Penzenstadler, Bill Tomlinson, and Debra Richardson
34
Writing Requirements for Electromobility and Smart Grids Systems: Challenges
and Opportunities
Jean-Charles Jacquemin, and Martin Mahaux
40
7

First International Workshop on Requirements
Engineering for Sustainable Systems (RE4SuSy)
Birgit Penzenstadler (Organization Chair), Martin Mahaux (Organization
Chair), and Camille Salinesi (Program Chair)
1
Technische Universität München, Germany, penzenst@in.tum.de
2
University of Namur, Belgium, martin.mahaux@fundp.ac.be
3
Université Paris 1 - Sorbonne, France, camille@univ-paris1.fr
Abstract. Researchers have recently started to explore how to support
the elicitation and documentation of sustainability requirements. In the
mean time, ubiquitous socio-technical systems alter the way we live, and
consequently have a potentially huge impact on sustainability. As sus-
tainability is one of the biggest challenges facing humanity in the coming
decades, we must reinforce research in this direction and ensure it is ap-
propriately rooted in the practice. The workshop provided an interactive
stage to collaboratively define a research agenda in RE for sustainable
systems, and also to jumpstart collaboration through networking and
active discussion on concrete points of this agenda.
Keywords: requirements, sustainability, environment, society
1 Background Goals
ICT-based systems are tremendously affecting the way we interact with the
world around us. These changes occur at a high rate and in shortening innova-
tion cycles. As suggested by the Smart2020 report [1], ICT can play a positive
role towards a more sustainable world. In that context, requirements engineers
will be key in ensuring that not only present needs, but also future generations
needs, can be satisfied. Indeed, in order to use the potential of ICT to reach more
sustainable behaviors, sustainability should be made a first class quality require-
ment. This is our overarching goal: ensure that sustainability requirements are
systematically and adequately elicited and documented when developing socio-
technical systems.
2 Addressed Themes
The most cited definition of the term “sustainable development” stems from the
so-called Brundtland report (“Our common future” [2]): “Sustainable develop-
ment is development that meets the needs of the present without compromising
the ability of future generations to meet their own needs”. It is interesting to
8
Requirements Engineering for Sustainable Systems (RE4SuSy)

note that, if it is commonly accepted that RE is mainly concerned with satisfying
present needs, then “sustainable RE” is a natural extension to this understand-
ing, anticipating on the satisfaction of future needs.
Sustainability has three major pillars: environment, society and economy.
Economy being targeted by traditional RE, we will concentrate on the two others.
Examples of environmental sustainability in RE research can be found in [3–
5]. The november 2010 edition of the IEEE Computer journal [6], addressing
Technology Mediated Social Participation gives an excellent idea of how ICT is
related to social sustainability. Although not limited to these items, the workshop
fosters discussion on:
– how requirements engineering can help in analysing sustainability issues;
– how to adapt existing or invent new elicitation, documentation, validation
techniques and tools for sustainability requirements;
– how to model sustainability requirements with all necessary context;
– how to learn from and interact with other sustainability-related domains
(e.g., environmental informatics);
– how to define, measure and assess sustainability as quality attribute.
As sustainability is a global and pervasive challenge, no particular industry
sector is excluded from our analysis. Any human activity that has an impact
on its society or its environment and involves a socio-technical system is on our
focus. Our aim is to see how such a socio-technical system can be better designed
to reduce its negative impacts, and strengthen the positive ones. However, some
industry sectors have been particularly under focus for the envisioned improve-
ment. The smart2020 report [1], Van Ypersele’s keynote at RE’08 conference [7]
and Pirolli et al. [6] suggest fields like Energy Supply, Transports, Buildings,
Agriculture, Waste, Governance, Health and more.
3 Submissions and Selection Process
In order to reach the goals of the workshop, we encouraged short submissions
formats for Problem Statements, Visions, Research Preview, Ongoing Research
Projects, Research Results. We invited posters, video clips or multi-media pre-
sentations of up to seven minutes with a one page abstract. We also invited short
papers of up to 6 pages LNCS style if authors wish to submit a more polished
relevant research.
For the selection process, the Program Chair assigned each submission to
three members of the Program Committee (PC) for a formal blind review pro-
cess. All authors (including the two Organization co-Chairs) indicated their
Conflicts of Interests with the PC members, so reviews could be performed ad-
equately. The PC members were Lorenz Hilty (University of Zürich), Steffen
Zschaler (King’s College London), Ruzanna Chitchyan (Leicester University),
Stefan Naumann (Trier University of Applied Sciences), Bill Tomlinson (Uni-
versity of California, Irvine), Toni Ahlqvist (VTT Finland), Brian Donnellan
(University of Ireland, Maynooth), David Stefan (University College London),
9

Emmanuel Letier (University College London), Andrea Zisman (City Univer-
sity London), Debra Richardson (University of California, Irvine), and Alistair
Mavin (Rolls Royce, UK).
Being a starting community, and given the workshop’s goals, we asked the
PC members to focus their review on the relevance for the workshop and the
potential for triggering discussion on a research agenda for RE4SuSy, rather than
on maturity of the work or strength of the validation.
The reviews were published on the workshop wiki (https://sustainability.
wiki.tum.de/RE4SuSy) along with the papers to kickstart the discussion pro-
cess between all the stakeholders. The goal was to have authors enhancing their
papers guided by the reviews and the potential comments from other workshop
participants. This also made the review process entirely transparent. All sub-
mitted contributions were finally accepted. While this rate can be interpreted as
a sign of looseness of the review process, we regard it as an effect of the positive
and constructive review process and the quality of initial submissions.
4 Workshop Format
The focus was on interaction and participation. After a short energizing exercise
and peronal presentation, the authors had five minutes to present their contribu-
tion. These were followed by heavy discussions (up to 25 minutes), kickstarted
by the discussant assigned to each paper. After the break we brainstormed about
possible research agenda items for RE4SuSy. This resulted in a list of interesting
topics for our community to work on. Below we summarize initial contributions
and present those results.
5 Summary of Contributions
The submissions covered a vast area of expertise, indicating the breadth of the
RE4SuSy topic. Mahaux and Canon suggested in a position paper that the con-
cept of sustainability was indeed more complex than one could initially imagine,
and that it’s integration into RE would be even more complex. As a first answer
to this problem, researchers are developing new RE approaches, frameworks and
tools. Penzenstadler et al. described their plans towards a new RE approach
tailored to SuSy. Kern et al. presented a multi-media poster for GREENSOFT,
a conceptual reference model for Green and Sustainable Software. It tries to
characterize the what, where, when, how and who of this topic. Hoesch-Klohe
and Ghose suggested to use scenarios as a basis for analyzing environmentally
aware systems, showing their amenability for identifying the (approximated) en-
vironmental performance of a system. Two contributions highlighted aspects of
RE4SuSy in specific sectors, with more in details. Jacquemin and Mahaux pre-
sented their view on RE for smart grids and electro-mobility, while Deprez et al.
presented challenges on energy and eco-aware RE for cloud applications.
10

6 Results
The raw brainstormings results are available online at https://sustainability.
wiki.tum.de/Research+Agenda+Items.
They served as a basis for suggesting the following research directions:
1. Understanding sustainability and sustainable systems: building interdisci-
plinary platforms for undertaking RE4SuSy research. How can we under-
stand what sustainability means and harness the knowledge of other disci-
plines to achieve sustainable systems, taking into account that there is no
single definition for sustainability, as it depends at least on the context and
evolve over time?
2. Roles and Scoping:
– Is RE4SuSy different to ordinary RE? Or is it just another NFR to
optimize?
– Who are the main RE4SuSy stakeholders?
3. Vertical / illustrative case study (E-mobility, SOA, etc.). It is suggested
that, in parallel to more theoretical studies, applied research on specific cases
should be undertaken to get a feeling from the practice and test preliminary
ideas. Specific interesting areas are suggested, such as Cloud Applications
for 1st level impacts, and smart grids for 2nd level.
4. Quality models, metrics, impacts, attributes that will help characterize pre-
cisely sustainable systems.
5. Cross-disciplinary future road mapping. Ensuring the satisfaction of future
needs requires having a look at the future. How can we impact the present
by looking at the future?
For each of the topics, there were at least one or two workshop participants
who wanted to actively conduct respective research.
7 Conclusion and Next Steps
The 1st International Workshop on Requirements Engineering for Sustainable
Systems (RE4SuSy) was a success and we received a lot of positive feedback.
We hope to organize the workshop next year, too, and to attract an increasing
number of submissions and participants for advancing and promoting research
on this challenging topic.
The wiki is still open so that workshop participants as well as further inter-
ested researchers and practitioners can discuss the topics of the research agenda.
Our next steps are to establish the research collaborations that were initiated
during the workshop. Thereby, the researcher who enlisted him-/herself for a
specific item on the research agenda serves as leader for the collaboration on a
designated topic and invites the others who were interested in contributing to
that same research agenda item. All participants agreed that it was crucial to
involve other disciplines and each of us is initiating contacts to researchers from
disciplines also related to sustainability.
We are looking forward to prosperous collaborations that will provide a strong
basis for a follow-up workshop.
11

References
1. The Climate Group: Smart 2020: Enabling the low carbon economy in the infor-
mation age. Technical report, Global eSustainability Initiative (2008)
2. United Nations World Commission on Environment and Development: Our Com-
mon Future. In: United Nations Conference. (1987)
3. Mahaux, M., Heymans, P., Saval, G.: Discovering Sustainability Requirements: an
Experience Report. In: 17th REFSQ. (2011)
4. Cabot, J., Easterbrook, S., Horkoff, J., Lessard, L., Liaskos, S., Mazon, J.N.: Inte-
grating sustainability in Decision-Making processes: A modelling strategy. In: 31st
ICSE. (2009)
5. Stefan, D., Letier, E., Barrett, M., Stella-Sawicki, M.: Goal-Oriented system mod-
elling for managing environmental sustainability. In: Third Workshop on Software
Research and Climate Change. (2011)
6. Pirolli, P., Preece, J., Shneiderman, B.: Cyberinfrastructure for social action on
national priorities. IEEE Computer 43 (2010) 20–21
7. 16th IEEE International Requirements Engineering Conference. In: 16th IEEE
International Requirements Engineering Conference. (2008)
12

Integrating Energy and Eco-Aware
Requirements Engineering in the Development
of Services-Based Applications on Virtual Clouds
Jean-Christophe Deprez, Ravi Ramdoyal, and Christophe Ponsard
CETIC - Center of Excellence in Information and Communication Technologies
29/3 Rue des Frères Wright, B-6041 Charleroi, Belgium
{jcd,rr,cp}@cetic.be - www.cetic.be
Abstract. Over the last decades, the energy and ecological footprint of
ICT systems, in particular those hosted at data centers, has grown signif-
icantly and continues to increase at an exponential rate. In parallel, re-
search in self-adaptation has yielded initial results where reconﬁguration
of ICT systems at runtime enables dynamic improved quality of service.
However, little has been done with regards to requirement engineering
for self-adaptive system for a lower energy and ecological footprint. This
paper sketches a framework on how to best reconcile these aspects in a
conscious way covering requirements, design and run-time, by capturing,
reasoning, monitoring and acting upon a set of interlinked system goals.
We highlight a number of important problems to overcome for the ap-
proach to be feasible, present our current view on it and state interesting
research questions open for discussions.
Keywords: Energy and Eco-Aware Requirements, Services-Based Ap-
plications, Virtual Clouds
1 Introduction
In 2007, the total footprint of the ICT sector was already about 2% of the
estimated total emissions resulting from human activities, and this amount is
expected to exceed 6 % in 2020 [9]. In parallel, the Climate Savers Computing
Initiative (CSCI, which involves Intel, IBM, and Google among others) main
aim is to reduce annual CO2 emissions from the IT sector by 54 million metric
tons by 2011 and an additional 38 million metric tons by 2015, which is the
equivalent of A
C 3.75 billion in annual energy cost savings. Its next focus is on
energy efficiency of computing equipment (including networking systems and
devices), adoption and deployment of power management, and promotion of
smart computing practices (particularly developers).
In response to this trend, hardware and software are designed to become
more aware of their ecological impact. Among the current new trends, cloud
computing has received considerable attention as a promising approach for
delivering energy and eco-aware ICT services by improving the utilization of
13

data center resources. In principle, cloud computing can be an inherently energy-
efficient technology for ICT provided that its potential for significant energy
savings is fully achieved at operation time, for instance, by enabling an eco-aware
management of a cloud infrastructure. Besides, a highly questionable assumption
regarding energy-effectiveness is precisely that energy savings necessarily equate
to reduce carbon emissions [14]. Virtualisation has increased the capability of
self-adaptation and self-reconfiguration of systems transparent to the end users
[5].
However current research results do not fully address the problem of energy
and eco-awareness in virtualized cloud infrastructure:
– most of the research addresses design-time solutions to provide run-time
adaptation, while requirements engineering for self-adaptive software sys-
tems has received less attention [16].
– as our dependency on such systems is increasing, the underlying energy costs
are also rising, which stresses the need for new energy-efficient and eco-
friendly technologies that enable new pricing models for data centers [3].
– the kind of energy source (green vs brown) is not taken into account.
Within this context, this paper introduces a new approach to help software
engineers address energy and ecological requirements when developing service-
based applications developed to run in virtualized cloud environment, as well as
to produce self-adaptable architectures that can optimize the energy and ecolog-
ical performance at runtime. This approach starts by promoting goal oriented
requirements engineering (GORE), where energy goals will be elicited and refined
into energy requirements that specify specific service level objectives (SLO) for
the runtime behavior of the software service. Second, the approach guides soft-
ware engineers in producing design models that can be self-adaptive to achieve
energy performance at runtime while keeping other parameters of the quality of
service under control.
The remainder of the paper is structured as follows. Section 2 first introduces
the key concepts of the approach, which is presented in Section 3. Section 4 then
highlight some related work. Section 5 finally summarises some key research
questions.
2 A Goal-Oriented Background
In this section, we introduce key definitions and concepts used in the proposed
approach, notably, goal oriented requirement engineering and measures and as-
sociated key performance indicators on energy and ecology in cloud environment.
Goal-oriented requirements engineering (GORE) relies on the use of goals
for eliciting, elaborating, structuring, specifying, analyzing, negotiating, docu-
menting, and modifying requirements [13]. Such use is based on a multi-view
model showing how goals, objects, agents, scenarios, operations, and domain
properties are inter-related in the system-as-is and the system-to-be. A goal is
an intent that can address different types of aspects. For instance, a behavioral
14

goal describes how the expected system should behave, while a soft goal describes
wishes with less clear-cut criteria (typically improve, increase/reduce or maxi-
mize/minimize a given property of the system). Soft-goals are at the heart
of the proposed approach, as they can deal with energy-effectiveness
and eco-awareness notably through first, improved adaptability of the
architecture of service-based applications and second, minimization
of the associated energetic needs and ecological footprints of service-
based applications in operation. In GORE, Goals are refined in subgoals and
other relationships between goals (such as obstacles, conflicts, reinforcement) are
explicitly elicited to form a goal graph. Alternative designs can also be captured.
A requirement is a terminal goal (lead node in a goal graph) which is under the
responsibility of a single agent (human or sub-system). The satisfiability of a
goal can be specified by a measurable key performance indicator (KPI).
In the proposed approach these goal constructs will be used to show explic-
itly how energy and ecological goals relate to other non-functional goals of the
system-as-is or the system-to-be. We will also define energy and ecological key
performances indicators.
In the context of cloud computing, the metrics used to measure KPIs on
energy usually focus on the energy consumed by hardware in the data cen-
ters, which is however not the only dimension [1]. This raises the first ques-
tion: RQ#1: How to deal with the lack of normalization for energy-
effectiveness metrics and the lack of ecological-awareness regarding
available energy sources ? Our idea is to overcome two of the main current
shortcomings, namely the lack of normalization for energy-effectiveness metrics
and the lack ecological-awareness regarding available energy sources. Energy nor-
malization is important if new pricing models per energy consumption and car-
bon emission are to be developed by cloud infrastructure provider and perceived
fair by service providers. In particular, pay per Watts could lead to different bills
if the same service with same input is scheduled on older or new more efficient
hardware. Green vs. brown energy measures also provides an important aspect
to consider in pricing models. For instance, if a software service can easily be
scheduled during green energy production peaks then it could be given priority
in case of overbooking of service providers.
The collection of energy KPI is triggering a second research question: RQ#2
How to match fine grained energy consumption of VMs and even
software components in a VM with the limited capabilities of mea-
surement at the hardware level only?. Indeed most data centers currently
providing Infrastructure as a service (IaaS) are limited to general physical mea-
sures. A possible answer is that energy-consumption models have to be developed
to normalize and estimate the desired measures as precisely as possible. For in-
stance, the combination of CPU-usage percentage, disk accesses and network
transfers measures will be used to define the energetic consumption of software
services components. Kansal et al. have proposed a model to infer VM consump-
tion from hardware energetic consumption [10] and could be explored to achieve
finer grain measurements.
15

3 From Energy Requirements to Runtime Eco-driven
Evolution
The scope targeted for the proposed approach is the following, on the one hand,
the infrastructure (IaaS) provider owns the hardware and the virtual infrastruc-
ture software and on the other hand, the software (SaaS) service provider owns
and packages a service-based application to be deployed and operated at the IaaS
provider. In this setup, the SaaS provider has little control over the scheduling
and placement policies of the IaaS provider. It is however anticipated that IaaS
provider will publish the required KPI measurements. As mentioned in the defi-
nition section, IaaS providers only have measurements on hardware consumption
at the server rack level; however, new accurate estimation models can help to in-
fer energy measurement at the VM and soon at a finer grain software component
in a VM. The proposed approach is independent of who provides the software
specific energy measurements. It can be the IaaS provider or even an indepen-
dent energy service provider who acts as a trusted third party between the IaaS
and SaaS providers. The important aspect is that energy measurement be fair
and trusted by the SaaS providers. The proposed approach also assumes that
the IaaS provider accepts to share energy measurements with the SaaS provider
who will in turn use these measurements to improve the quality profile of its
software service-based application.
To reduce the energy-consumption and improve the eco-friendliness of a
service-based application, we claim that energy and eco-awareness must become
a core principle of the architecture, design and implementation of all software
components involved at the different layers (Infrastructure and application). This
rather disruptive, cleans slate approach, where different layers of an ICT system
are re-designed and re-implemented to better handle a given concern, was fol-
lowed with great success by Donofrio et al. [6] who showed how co-design with
all aspects of the infrastructure and of the application in mind helps to make
high power computing more efficient while consuming less energy.
Figure 1 gives a high level view of our approach. At specification and
design level, it starts with a requirements elicitation and analysis of
a new software service partly driven by library of energy goals ex-
plicitly related to other application?s functional and non-functional goals. This
helps architects to select the most appropriate architecture for developing a
self-adaptable software service, and second, to generate the KPI and thresholds
specific to the software service under development. An interesting question is
RQ#3: how to relate KPI of contributing/conflicting goals?. To some
extend the normalization discussed earlier helps but multiple criteria must be
taken into account to design system adaptation policies that balance ecological
and other SLA goals appropriately.
The next step consists of propagating these KPI and thresholds at detailed
design level, for instance, annotating elements of UML diagrams with particular
energy KPI thresholds. These annotations are then used at compile time to
inject the necessary measurement probes in the application to enable runtime
measurements. These runtime measurements will then be used at three different
16

Fig. 1. Eco-aware Evolution Framework
levels, at software service operation level, at maintenance level of the particular
software service and at a more general level for the development of new software
services. The rest of this section details them.
At the service operation level, the KPI measurements are used
by the service itself to perform self-adaptation actions that will im-
prove its energy runtime performance while satisfying the other SLA
aspects such as performance and security. Self-adaptation is limited to
anticipated variability injected in the service architecture. A legitimate question
is: RQ#4: how to identify variability point at design time and design
adaptations policies that balance ecological and other SLA goals. For
example, depending on the usage load, a self-adaptable system would vary its
configuration between an energy costly mirror-oriented data storage and a more
economic but also less available single centralized storage. In addition, an infras-
tructure is required to manage the KPI monitoring and adaptation policy rules.
A question here is RQ#5: which concrete and efficient form can this take
in a SOA/Cloud architecture? Middelware level will allow to benefit from
application transparency and scalability but attention must be given to avoid
consuming more energy than what is saved for example by triggering frequent
reconfiguration or gathering too large amounts of historical data.
At the maintenance level, the KPI measurements provide valuable
feedback to architects and developers of the measured software ser-
vice. In turn, they can refactor the software service based on concrete energy
data and clearly identify the energy bottlenecks of the software service. While
self-adaptation can be performed along a few anticipated energy bottlenecks, the
manual refactoring based on energy KPI will address more intricate behaviours
of the software service that could not be anticipated at the design time.
At the general level, an overall guidance is needed to develop new
service-based applications with better energy and ecological profiles.
To formulate appropriate guidance to architects at requirement and design phase,
17

data on many applications are needed to cross relate their energy goals, their
architectures, their variability points, etc. A question here is RQ#6: What
data on architectures, variability points to capture and cross-relate to
KPI to enable efficient ecological guideance of future applications?
4 Related Works
In practice, current research on energy-aware cloud computing is limited to im-
proving the energy-efficient operation of computer hardware and network infras-
tructure. For instance, Intel has recently pushed server hardware with increased
computing efficiency targeted for data center providing a virtual infrastructure
[8], while [17, 11, 7] focused on the consolidation of virtualized infrastructure in
data centers to improve energy efficiency. The FP7 research projects FIT4Green
[2] and GAMES [4] are further advancing on consolidation techniques in virtual-
ized environment, while [12] also proposes an approach to creating environmental
awareness in service oriented software engineering.
However, none of these researches ensure energy-awareness at the different
steps and levels of a service-based application to run in a virtualized cloud. In
particular, very few methodology is currently proposed to support the require-
ments engineer and design modeling of systems that manages self-adaptation
according to energy and eco-awareness. A good survey confirming the currently
limited work devoted to this domain is presented in [15]. Without more en-
ergy consideration at the requirement and design phase, the development of
energy-aware code at the various layers, infrastructure, middleware and service
application is unlikely to be successful. We believe that the proposed approach
that supports the requirements engineering and design modeling for energy-and
eco-aware, self-adaptive systems will contribute further improve the energy and
ecological profile of ICT systems running in virtualised cloud environments.
5 Conclusion and Future Works
In this paper, we sketched an approach to improve the ecological awareness
of service-based applications. Our goal is not to propose a definitive solution
but rather to highlight a number of open research questions and propose some
partial answers. To increase the impact of the approach, it is worth noting that its
application is not limited to new development project but is applicable to existing
systems. The main difference resides in the self-adaptation, in particular, the
architecture of an existing software service will not initially include well-defined
and controlable variability points. Thus, the guidance on refactoring will also
cover existing service-based systems.
References
1. Baliga, J., Ayre, R.W.A., Hinton, K., Tucker, R.S.: Green cloud computing: Bal-
ancing energy in processing, storage, and transport. In: Proceedings of the IEEE.
vol. 99 (January 2011)
18

2. Basmadjian, R., Bunse, C., Georgiadou, V., Giuliani, G., Klingert, S., Lovasz, G.,
Majanen, M.: Fit4green - energy aware ict optimization policies. In: Proc. COST
Action IC0804 on Energy Efficiency in Large Scale Distributed Systems (2010)
3. Berl, A., Gelenbe, E., Di Girolamo, M., Giuliani, G., De Meer, H., Dang, M.Q.,
Pentikousis, K.: Energy-efficient cloud computing. The Computer Journal 53(7),
1045–1051 (2009)
4. Bertoncini, M., Pernici, B., Salomie, I., Wesner, S.: Games: Green active manage-
ment of energy in it service centres. In: CAiSE Forum 2010, Hammamet, Tunisia,
June 7-9. pp. 238–252 (2010)
5. Cheng, B.H.C.e.a.: Software engineering for self-adaptive systems: A research
roadmap. In: Cheng, B.H.C., de Lemos, R., Giese, H., Inverardi, P., Magee, J.
(eds.) Software Engineering for Self-Adaptive Systems. Lecture Notes in Computer
Science, vol. 5525, pp. 1–26. Springer (2009)
6. Donofrio, D.e.a.: Energy-efficient computing for extreme-scale science. Computer
42, 62–71 (November 2009)
7. Garg, S.K., Yeo, C.S., Buyya, R.: Green cloud framework for improving carbon
efficiency of clouds. In: Proc. of the 17th Int. Conf. on Parallel Processing - Volume
Part I. pp. 491–502. Euro-Par’11, Springer-Verlag, Berlin, Heidelberg (2011)
8. Intel: Breakthrough security capabilities and energy-efficient performance for cloud
computing infrastructures (2010), http://software.intel.com/file/26765
9. Juan-Carlos Lı̈£¡pez-Lı̈£¡pez, Giovanna Sissa, L.N.: Green ict: The information
society’s commitment for environmental sustainability. In: UPGRADE, vol. XII.
Council of European Professional Informatics Societies (CEPIS) (October 2011)
10. Kansal, A., Zhao, F., Liu, J., Kothari, N., Bhattacharya, A.A.: Virtual machine
power metering and provisioning. In: Hellerstein, J.M., Chaudhuri, S., Rosenblum,
M. (eds.) SoCC. pp. 39–50. ACM (2010), http://doi.acm.org/10.1145/1807128.
1807136
11. Kim, K.H., Beloglazov, A., Buyya, R.: Power-aware provisioning of virtual ma-
chines for real-time cloud services. Concurr. Comput. : Pract. Exper. 23, 1491–1505
(September 2011)
12. Lago, P., Jansen, T.: Creating environmental awareness in service oriented software
engineering. In: Proc. s of the 2010 Int. Conf. on Service-oriented Computing. pp.
181–186. ICSOC’10, Springer-Verlag, Berlin, Heidelberg (2011)
13. van Lamsweerde, A.: Requirements engineering: from system goals to UML models
to software speciﬁcations. John Wiley and Sons, Ltd. (2009)
14. Linthicum, D.: Beware: Cloud computing’s green claims aren’t always
true. Infoworld (July 2011), http://www.infoworld.com/d/cloud-computing/
beware-cloud-computings-green-claims-arent-always-true-167984
15. Mahaux, M., Heymans, P., Saval, G.: Discovering sustainability requirements: An
experience report. In: Berry, D.M., Franch, X. (eds.) REFSQ. Lecture Notes in
Computer Science, vol. 6606, pp. 19–33. Springer (2011)
16. Qureshi, N.A., Perini, A.: Engineering adaptive requirements. In: Proceedings of
the 2009 ICSE Workshop on Software Engineering for Adaptive and Self-Managing
Systems. pp. 126–131. IEEE Computer Society, Washington, DC, USA (2009)
17. Srikantaiah, S., Kansal, A., Zhao, F.: Energy aware consolidation for cloud comput-
ing. In: Proceedings of the 2008 conference on Power aware computing and systems.
pp. 10–10. HotPower’08, USENIX Association, Berkeley, CA, USA (2008)
19

Making use of scenarios for environmentally
aware system design
Konstantin Hoesch-Klohe, Aditya Ghose
Decision Systems Lab (DSL),
School of Computer Science and Software Engineering,
University of Wollongong.
Abstract. This paper motivates the use of scenarios as a basis for en-
vironmentally aware system design, by showing their amenability for
identifying the (approximated) environmental performance of an to-be
system. In particular, we describe two complementary techniques for as-
sessing and comparing the environmental performance of scenarios and
how this can promote environmentally friendly decision making.
Keywords: Environmentally aware design, Requirements Engineering
(RE), Scenarios, Resource modelling, Non-functional requirements (NFR).
1 Introduction
While much research attention has focused on developing alternative energy
sources, automotive technologies or waste disposal techniques, we often ignore
the fact that our behaviour (or that of a system) is a critical contributor to our
environmental footprint. It is therefore crucial that we start to analyse existing-
and to-be system behaviour and the intentions that give rationale to the former,
in the context of our accumulated environmental debts. Requirements engineer-
ing (RE), supports the identification, analysis and specification of stakeholder
intentions and their refinement to a concrete system design, which gives rise to
the particular behaviour from its behaviour. We therefore believe that RE is the
right starting point for nurturing the development of environmentally friendly
systems (this has also been pointed out in e.g. [1]). Moreover, requirements
engineering principles and techniques are not only applicable to the design of
technical systems (e.g. a software system), but can also help us to understand
and improve non-technical systems (e.g. an organisation).
For requirements engineering to succeed in this exercise, we must be able
to make informed decisions among alternative requirements and system designs.
However, during RE no concrete materializations of an envisioned system (and
its potential alternatives) are available, which limits our ability to assess their
environmental performance and therefore to make informed decisions. We argue
that it is nevertheless possible to assess the environmental performance of an
envisioned system (even early in the requirements engineering process), by mak-
ing use of scenarios and scenario-based requirements engineering techniques. In
20

particular, we describe two complementary techniques for assessing and com-
paring the environmental performance of alternative scenarios and how this can
promote environmentally friendly decision making. This is aligned with exist-
ing work on the use of scenarios in the context of identifying and analysing
non-functional requirements (e.g. in [2,3,4]).
In the following this paper (1) motivates scenarios in the context of envi-
ronmentally aware system design, (2) proposes techniques for determining the
environmental performance of scenarios, and (3) outlines how the former can
form the basis for environmentally informed design decision.
2 Scenarios - snapshots of a environmental performance
A scenario is a storyline or script describing a system’s behaviour in a particular
situation of events. A scenario therefore contains information about the actions
of an existing or envisioned system, in a particular context. The representation
of a scenario can vary from a narrative description (a storyline) to a precise
formal representation. For example, the scenario below is a narrative snapshot,
in the context of a delivery company, told from the system perspective1
.
Scenario 1: A parcel for Jim has arrived at Pit Street hub. The parcel is trans-
ported to Jim’s home address. On arrival, Jim is not available and a notification
message is left. The parcel is delivered to the closest pick up location, to be picked
up by Jim.
Scenarios are interesting in the context of environmentally aware system de-
sign, since they offer the right level of abstraction - their concrete representation
of system behaviour (in the given example the system is the delivery company)
eases the correlation of environmental performance values. Hence, scenarios al-
low us to not only get a behavioural snapshot of a system, but also a snapshot of
its performance in a given situation. These snapshots are not sufficient to deter-
mine, e.g. the total carbon dioxide emission of a system for a particular period of
time. However, we are not in the game of carbon accounting, but rather seek to
support informed design decisions. When confronted with alternative scenarios,
it is sufficient to know which scenarios perform more preferred than others, to
make environmentally aware decisions.
Scenarios can not only be identified by observing the behaviour of a realized
system, but also (1) early in the RE process, by envisioning the behaviour of a
to-be system (e.g. see [5]) and/or (2) later in the RE process, by extraction from
designs like an use case-, activity- or sequence diagrams (e.g. see [6]). In either
case, for scenarios to form the basis for environmentally aware design decisions,
their environmental performance must be explicated.
In short, to identify the environmental performance of a scenario, we first
identify all (system) actions within the scenario. For example, the narrative
scenario given above can be translated into a sequence of actions as shown in
Figure 1. We then associate (by manual- or automated annotation) with each
1
Scenarios can also be captured from the user perspective.
21

action a performance value, using one of the methods described in the follow-
ing subsection. The overall performance of the scenario is then determined by
accumulating all performance values along the sequence of actions.
Fig. 1. The parcel delivery scenario as a sequence of actions
2.1 Identifying a scenario’s environmental performance
In the following we describe two complementary techniques for correlating en-
vironmental performance values with actions of a scenario. This requires us to
make precise the abstract notion of environmental performance. There are nu-
merous ways in which “environmental performance” can be captured, i.e. car-
bon dioxide equivalent (CO2-e) emission2
, water consumption, waste generation,
damage to fauna and ﬂora, air quality, or some combination of the former. For
ease of elaboration and without loss of generality, we use CO2-e as the only
non-functional requirement of interest.
Educated guess: In this method the requirement engineer makes an educated
guess on the expected CO2-e emission of each action of a scenario. Note that
by guessing the CO2-e emission performance, the context of an action is taken
implicitly into account. However, the quantitative amount of CO2-e emission
(e.g. in number of kilograms) is hard to guess and in practice often leading to
unrealistic values. We therefore recommend to abstract away from a quantitative
scale to a qualitative scale. For example, the traffic light scale could be used,
where red could denote a high CO2 emission impact, “orange” a moderate emis-
sion impact and green a low emission impact. We belief (and our observations
conﬁrm this) that practitioners have a good “gut-feeling” in guessing the CO2-e
emission performance, when working with a simple scale. In the (likely) case
that the assessment is done by more than one person, we further recommend to
jointly do the initial assessments, such that a shared understanding of “high”
and “low” emitting actions can emerge. A possible assessment of our running
example (using the traffic light scale) is given in Figure 2.
Fig. 2. Scenario assessment using the traffic light scale
2
CO2-e is an expression of other greenhouse gases as their carbon dioxide equivalent
by their global warming potential (CO2 itself has a global warming potential of 1).
22

This method is interesting in the case that (1) the envisioned system and
context is still vague and as a consequence more detailed values cannot be deter-
mined, i.e. early in the requirements engineering process and (2) an initial “quick
and dirty” overview of the performance of the scenario landscape is desired.
Modelling the resource context: More precise CO2-e emission values can be
determined, by considering the context in which an action is (or will be) per-
formed. We argue that the relevant context for the environmental performance
of an action is given by the resources it uses. More precisely, the emission values
of an action are influenced by: (1) What resources are used, e.g. driving a truck
with a particle filter causes less emission than driving the same truck without the
particle filter; (2) How the resource is used, e.g. driving an empty truck causes
less emission than driving a fully loaded truck; (3) The intensity with which a
resource is used, e.g. driving a truck 100km or 200km; and (4) What other sub-
resources are used e.g. the fuel used for combustion and the associated carbon
emission for gathering and transporting the fuel to the petrol station (if this
level of detail is desired - again we are not in the game of carbon-accounting).
In [7] a way of modelling this “usage-cost” interplay among resources (as well
as other relationships like “is-a” and “part-whole” for other reasoning purposes)
and actions is described. Essentially, the proposed resource model can be queried
by a functional call, which states what resource is used, how it is used, and with
which intensity, returning the respective performance values. For example, the
call use(truck, loaded, 30km) (given a particular resource model instance) could
return a value of 8.4kg CO2-e emission. Given the former, each action in a sce-
nario is annotated with a functional call. The expression is evaluated w.r.t. to the
currently selected resource model instance (other instances could be considered
to reflect an alternative context) and returns the corresponding emission figures.
Figure 3 shows the running example with the annotation of functional calls.
Note that values can also be annotated manually, e.g. the emission of the action
“leave message” has been considered as neglectable and is therefore annotated
with “0 kg CO2-e”.
Fig. 3. Scenario assessment using a functional call to a resource model
This method is interesting in the case that a decision among alternative
scenarios is to be based on concrete and arbitrarily precise3
CO2-e emission
performance values. Since the resources and their usage-cost relations need to
be captured this method is more suitable later in the requirements engineering
3
The more fine-grained the resource model the more precise its answers, but also the
higher the cost for building and maintaining the model.
23

process.
Combining performance values: The CO2-e emission performance values
associated with each action can now be used to determine the performance of a
scenario. In case of quantitative CO2-e emission values, two values are combined
by summation, such that the performance of a scenario is simply the sum over
all values. For example, the quantitative CO2-e emission performance of scenario
one is 9.8kg. In case of qualitative CO2-e emission values, two values are com-
bined by selecting the least preferred, such that the performance of a scenario is
simply the performance of its least performing action. For example, the qualita-
tive CO2-e emission performance of scenario one is “high”. Although, the later
would treat two scenarios with values “high-high-high” and ”low-low-high” as
equally preferable, it allows us to treat both qualitative and quantitative mea-
sures in the same (algebraic) framework, i.e. the c-semi-ring framework [8]. This
is important in the cases where some scenarios are given qualitative and others
quantitative values.
2.2 Scenarios and environmentally informed decision making
An (environmentally aware) decision can be made, whenever there is choice -
i.e. whenever it can be chosen among alternatives. In this paper we promote the
use of scenarios as the basis of choice among alternative systems. Two diﬀer-
ent scenarios can be treated as alternatives, if they realize the same high-level
stakeholder objectives (in which case the stakeholder objectives are treated ax-
iomatically), and/or if they describe the behaviour of a system w.r.t. the same
sequence of events. In the running example (which does not consider stakeholder
objectives) the sequence of events is “parcel for Jim has arrived at Pit Street
hub” before “Jim is not available”. An alternative to scenario one, taking into
account the same sequence of events, is scenario two (Figure 4 is a graphical de-
scription of the alternative scenario with associated qualitative and quantitative
CO2-e performance values):
Scenario 2: A parcel for Jim has arrived at Pit Street hub. Send mo-
bile text message to Jim to conﬁrm his availability on the expected arrival. Jim
replies that he is not available during this time. The parcel is delivered to the
closest pick up location, to be picked up by Jim.
Applying the associated qualitative values, scenario one and two are equally
preferred. However, applying the quantitative values, scenario two (total CO2-e
emission of 7.65kg) is preferred over scenario one (total CO2-e emission of 9.8kg).
Such preference relation among alternative scenarios can support environmen-
tally aware decision making and system design at least in the following. (1) The
chosen set of scenarios can be used to extract new requirements. A way of deriv-
ing requirements from scenarios has, for example been described in [9]. (2) The
chosen set of scenarios can be used to analyse existing requirements against the
set of preferred scenarios (e.g. see [10]), which can then form the basis for adapt-
ing the existing requirements. However, in all cases the decision for a particular
set of requirements must take into consideration the impact on other functional
24

Fig. 4. Alternative scenario with concrete and abstract CO2-e performance val-
ues
and non-functional requirements, i.e. the global impact of a particular decision
must be understood.
3 Conclusion Future Work
This paper motivates the use of scenarios as a basis for building environmentally
sustainable systems. In this context, two complementary techniques, which can
be used to assess the environmental impact of scenarios have been described as
well as how this can form the basis for environmentally aware decision making.
Future work is concerned with the following question. Given a set of (envi-
ronmentally preferred) scenarios describing a to-be system, how can an existing
system design be minimally changed, such that it is shown to entail all to-be
scenarios. Minimal change is important, because it protects existing investments
in the context of desired change. We seek to answer this question by leveraging
“light-weight” formal machinery (limiting the burden on the engineer).
References
1. Stefan, D., Letier, E., Barrett, M., Stella-Sawicki, M.: Goal-oriented system mod-
elling for managing environmental sustainability. In: 3rd Workshop on Software
Research and Climate Change. (2011)
2. Sutcliffe, A., Minocha, S.: Scenario-based analysis of non-functional requirements.
In: REFSQ. (1998) 219–234
3. Gregoriades, A., Sutcliffe, A.: Scenario-based assessment of nonfunctional require-
ments. IEEE TSE 31(5) (2005) 392 – 409
4. Nixon, B.: Management of performance requirements for information systems.
Software Engineering, IEEE Transactions on 26(12) (2000) 1122–1146
5. Hooper, J., Hsia, P.: Scenario-based prototyping for requirements identification.
In: ACM SIGSOFT Software Engineering Notes. Volume 7., ACM (1982) 88–93
6. Briand, L., Labiche, Y.: A uml-based approach to system testing. Software and
Systems Modeling 1 (2002) 10–42
7. Hoesch-Klohe, K., Ghose, A.: Towards Green Business Process Management. In:
SCC. (2010)
8. Bistarelli, S., Montanari, U., Rossi, F.: Semiring-based constraint satisfaction and
optimization. Journal of the ACM (JACM) 44(2) (1997) 236
9. Alrajeh, D., Ray, O., Russo, A., Uchitel, S.: Extracting requirements from scenarios
with ILP. Lecture Notes in Computer Science 4455 (2007) 64
10. Sutcliffe, A.: Scenario-based requirements analysis. RE (1998)
25

Green Requirements Engineering with the GREENSOFT
Model
Taking the whole Lifecycle of Software into Account
Eva Kern, Markus Dick, Stefan Naumann, Timo Johann, Matthias Giesselmann,
Patrick Lang
Umwelt-Campus Birkenfeld, Trier University of Applied Sciences,
Institute for Software Systems
greensoft@umwelt-campus.de
1 Green and Sustainable Software Engineering
In an earlier paper we gave the following definition: “Sustainable Software
Engineering is the art of defining and developing software products in a way so that
the negative and positive impacts on sustainability that result and/or are expected to
result from the software product over its whole lifecycle are continuously assessed,
documented, and optimized.”
Based on that definition it is required to pay attention to the whole life
cycle of a software product from beginning on, starting with the requirements
review. Since many different processes, products and services are involved in
this life cycle, which have impacts on sustainable development, they must be
considered in order to figure out if a software product and even its engineering
process is green or not. In view of the fact that several design and implementation
decisions are made in the requirements phase, it is necessary that the consequences of
these decisions are taken into account at this phase.
2 Reference Model for „Green Software“
Based on this aspects we developed a conceptual reference model shown in
our multi-media presentation that supports sustainable production and usage of
software. It includes a life cycle of software products, sustainability criteria and
metrics for software products, procedure models as well as recommendations for
actions and tools for purchasers, developers, administrators, and users. In that way the
different user roles are addressed.
The introduced Lifecycle for Software Products supports responsible persons in
estimating the impacts on sustainable development by software products. The
approach based on Life Cycle Assessment (LCA) [1] takes the direct effects (Green
IT) and the indirect effects (Green by IT) into account.
The quality model (based on [2–4]) gives an overview of potential aspects which
can be taken as Sustainability Criteria and Metrics for Software Products. The
metrics need to be defined for specific types of software. In order to support software
developers during the development process and administrators and users in
26

configuring or choosing software we present a measurement model. The method is to
compare the energy consumption of different software or different configurations of
software.
The generic Procedure Model takes an organizational perspective look at the
development phase of a software product and extends software development
processes by sustainability aspects.
As examples for Recommendations for Actions and Tools the model includes a
knowledge base with a collection of guidelines, tips and hints in the area of
sustainable information technology. Regarding the Green Web the Firefox Add-on
“Green Power Indicator” displays whether the called site is hosted on a server, which
is operated with environment-friendly produced electricity.
3 Conclusion
We present a conceptual reference model for Green and Sustainable Software that
comprises a software products’ life cycle, direct and indirect effects, different user
roles and approaches for activities. As a reference model its objective is to structure
concepts, strategies, activities, and processes of Green Software Engineering
and to organize research in the field of Sustainability Informatics. With our
model, requirements engineers can take different aspects of sustainable and
green software into account. This comprises e.g. aspects like software
architecture decisions, tools for measuring energy-efficiency code and what
impact each software engineering phase onto environment has.
4 References
1. Deutsches Institut für Normung e.V. (2009) Environmental management - Life cycle
assessment - Principles and framework (ISO 14040:2006); German and English version EN
ISO 14040:2006. Beuth, Berlin 13.020.10(DIN EN ISO 14040:2009-11 (D))
2. Albertao F, Xiao J, Tian C, Lu Y, Zhang KQ, Liu C (2010) Measuring the Sustainability
Performance of Software Projects. In: 2010 IEEE 7th International Conference on e-
Business Engineering (ICEBE 2010), Shanghai, China, pp 369–373
3. Naumann S, Dick M, Kern E, Johann T (2011) The GREENSOFT Model: A Reference
Model for Green and Sustainable Software and its Engineering. SUSCOM 1(4):294–304.
doi:10.1016/j.suscom.2011.06.004
4. Taina J (2011) Good, Bad, and Beautiful Software - In Search of Green Software Quality
Factors. CEPIS UPGRADE XII(4):22–27
Acknowledgments This paper evolved from the research and development project
“Green Software Engineering” (GREENSOFT), which is sponsored by the German
Federal Ministry of Education and Research under reference 17N1209. The authors
are solely responsible for the content.
27

Integrating the Complexity of Sustainability in Requirements
Engineering
Martin Mahaux1
, Caroline Canon2
1
PReCISE Research Centre, University of Namur, Belgium
2
Sustainable Development Research Group, University of Namur, Belgium
{martin.mahaux, caroline.canon}@fundp.ac.be
Abstract. [Context and Motivation] While having a simple definition,
Sustainable Development is a broad, interdisciplinary and complex concept.
Applying this concept when designing products is therefore a complex task that
requires a lot of interdisciplinarity. [Question/Problem] As software continues
to invade all aspects of our lives under ever-renewed forms, we realize that
designing sustainable software is probably of paramount difficulty and
importance. [Position] This position paper argues that this new field will have
no other option than integrating this complexity into its design practices
through opening collaborations with sustainability experts.
2. Introduction
Sustainability Informatics has been suggested as a new research field in 2010 [1]. It is
born out of the Environmental Informatics field, which is now comprised within
Sustainable Informatics. Within this discipline, Sustainable Software has received a
significant attention. Results have been mainly published in specialized venues, of
which a nice summary can be found in [2]. In this publication, Naumann et al.
combine many existing works, as well as environmental sciences knowledge, to lay
solid foundations for studying Sustainable Software. Their holistic study result in new
definitions for Sustainable Software and its Engineering, as well as in a framework
for designing sustainable software called the GreenSoft Model. It specifies where to
look for software impacts on sustainability and makes initial suggestions on how to
measure them and how to deal with them according to your process and role
regarding software. This is, to our knowledge, the most advanced and comprehensive
model of the genre to date.
However, while certainly containing useful material, we still consider it as a mostly
empty box, that will have to be filled with more concrete techniques and tools for
designing sustainable software. In particular, we noted that the question of the
complexity of the sustainability concept and how to integrate this complexity into
already complex software engineering is mentioned, but escaped, rather silently.
28

3. Sustainability: a complex concept.
The university of Namur (FUNDP) has recently set up an interdisciplinary research
group around sustainability. It is pursuing mainly 4 research directions, one of them
being centered on the definition of the sustainability concept. When the Computer
Sciences oriented authors of this paper invited this group to collaborate, they expected
to receive answers. Instead they realized there were no simple answers, and that
complex answers were not ready yet.
The Sustainability Research Group is composed of researchers in Human and Nature
Sciences, aiming at elaborating a map of research in “Sustainable development”.
What is in fact a research in Sustainability? What are the criteria to say that a research
concerns Sustainability? Realizing that each discipline had a specific viewpoint on
sustainability, they decided to start with having each discipline to present his
viewpoint and discuss it. Divergences and convergences are carefully kept aside for
later reconciliation. The first and only current result is that researchers are now aware
that a long time will be needed in order to answer these questions, due to the
intrinsically interdisciplinary nature of the sustainability concept. Our position is that
Requirements Engineers should follow on these results and collaborate in order to
translate them to their own discipline.

Notwithstanding this, research has already delivered frameworks to analyze
sustainability. The famous Life Cycle Analysis (LCA) framework, used in [2], is a
prominent example, but its scope is quite limited. More complex models can also be
found, see for example: [3–6]. They’re all incomplete as any model is, but here
particularly as they usually result from mono-disciplinary efforts. They however offer
interesting tools to requirements engineers, and we stand behind the position that
research in sustainable requirements should take the time to investigate these and
translate them to it’s body of knowledge, similarly to what Naumann et al. have
started to do with LCA and the GreenSoft Model.
4. Requirements Engineering and impacts on the software life-
cycle.
4.1. The GreenSoft Model
The first part of the GreenSoft model [2] recalls that software impacts sustainability
all along its lifecycle (Development, Usage, Disposal), at least at three levels:
First-order impacts are direct effects [like…] resource use and pollution from
mining, hardware production, power consumption, and disposal of electronic
equipment waste. Second-order impacts are effects that result indirectly from using
ICT, like energy and resource conservation by process optimization
(dematerialization effects), or resource conservation by substitution of material
products with their immaterial counterparts (substitution effects). Third-order
29

impacts are long term indirect effects that result from ICT usage, like changing life
styles that promote faster economic growth and, at worst, outweigh the formerly
achieved savings (rebound effects)[2].

Figure 1: Software Life Cycle and impacts on sustainability [2]
The paper also insists on the fact that second- and third-order effects might well be
the most important, but the harder to grasp. The distinction between software that has
a sustainability-related main purpose and other-purpose software is also highlighted.
It is argued that second- and third-order effects are nearly impossible to grasp in the
latter case.
In this section we use the first part of the GreenSoft Model to briefly see where
Requirements Engineers should take care about sustainability impacts. First we
discuss the phase (development, usage, disposal), then the level of impact (1st
, 2nd
or
3rd
order).
4.2. The Requirements Engineer’s Point of View
RE is obviously primarily concerned by the usage phase of the software. But RE can
also reduce the relative impact of the development and disposal phase: by enabling
software to last longer. This in turn relates to qualities such as reliability, adaptability,
maintainability or context-awareness of software. While specific development
paradigms such as Agile claim their share of the pie in this area [7], it is clear that the
fitness for purpose of the software is the prime quality that will save it from being
thrown in the bin too early. Consequently, a correct requirements engineering work
has a lot to do with software that lasts.
So far as software is concerned, fighting negative 1st
-order impacts means designing
lean software: software that will consume just what it needs in terms of energy and
hardware. While programming languages and techniques have a predominant impact
here, the requirements work also plays an important role. Keeping the software to
functionalities that are strictly needed is key. Variability management techniques can
also help software engineers to offer more customizable products, so users can select
what they need and only this, removing unused features and associated energy costs.
30

Caring about 2nd
- and 3rd
-order effects means designing software that induce more
sustainable human behaviours. For any software, the functionalities that we design
may have an impact on sustainability. The Requirements Engineer is the most
appropriate person to integrate sustainability at this time. But this won’t be easy, as
the complexity of software is multiplied by the complexity of sustainability and
human behaviour. For example, e-bay, which fosters reuse of physical goods (positive
impact), may very well foster over-consumption (negative rebound). It’s functionality
to show goods that are close to your home saves on transport impacts, but the one that
shows you results from far away has the reverse effect. E-bay fosters individual
exchanges between people, and provides a sense of community, bringing people
together, which seems to be positive. But is it really so? Social networking tools in
general, a prominent example, have a clear impact on social sustainability of our
society. But how can we measure this impact? How can we assess if it serves a more
or less sustainable society?
In an experience report, Mahaux et al. [8] show that Requirements Engineers can take
the time to assess at least second-order effects of a business-oriented software. They
experimented with very concrete adapted techniques and highlighted how
Requirements Engineers needed to talk to Sustainability specialists in order to master
the complexity of this domain and integrate it into their developments. Just as
Requirements Engineers do with other quality requirements like security [9], they
have to tailor specific techniques and craft the collaboration between Requirements
Engineers and other disciplines specialists to reach the desired quality levels. In [10],
Cabot et al. propose to consider sustainability as a high level goal amongst others, and
using goal-oriented techniques to help decision-making for Requirements Engineers
and stakeholders. They also observe that the first problem is the lack of standard
definitions for sustainability concepts, and suggest Requirements Engineers should
work on defining taxonomies for this concept.
Figure 2: Areas for action for Requirements Engineers

31

5. Conclusion
Requirements Engineers have a role to play in order to make software more
sustainable. It encompasses efforts to build lean and long lasting software, but also
software that helps systems using it to be more sustainable. To do so they first need to
connect with research that will let them understand what is a sustainable society.
Indeed, the complexity of this topic should not be underestimated and, while some
simplifying frameworks are useful and needed, integrating the real complexity of the
sustainability concept will require more work. Researchers from both disciplines
should work collaboratively to develop adequate frameworks for understanding
sustainability in RE and efficient tools to take decisions for building sustainable
software. How these interactions might work, which sustainability experts should be
integrated, which role plays the client who orders the software, in which part of the
RE process is this collaboration in particular useful… are good examples of the
coming research questions in this direction.
6. References
[1] Naumann, Stefan: Sustainability Informatics: A new Subfield of Applied
Informatics? In: Mûller, Andreas; Page, Bernd; Schreiber, Martin (Eds.): EnviroInfo
2008. Environmental Informatics and Industrial Ecology, 22nd International
Conference on Environmental Informatics. Aachen 2008
[2] S. Naumann, M. Dick, E. Kern, and T. Johann, “The GREENSOFT Model: A
reference model for green and sustainable software and its engineering,” Sustainable
Computing: Informatics and Systems, vol. 1, no. 4, pp. 294-304, Dec. 2011.
[3] P. Ekins, S. Simon, L. Deutsch, C. Folke, and R. De Groot, “A framework for the
practical application of the concepts of critical natural capital and strong
sustainability,” Ecological Economics, vol. 44, no. 2-3, pp. 165–185, 2003.
[4]S. López-Ridaura, O. Masera, and M. Astier, “Evaluating the sustainability of
complex socio-environmental systems. The MESMIS framework,” Ecological
indicators, vol. 2, no. 1-2, pp. 135–148, 2002.
[5]E. Ostrom, “A general framework for analyzing sustainability of social-ecological
systems,” Science, vol. 325, no. 5939, p. 419, 2009.
[6]“Reliable Prosperity - A pattern language for sustainability.” [Online]. Available:
http://www.reliableprosperity.net/. [Accessed: 26-Jan-2012].
[7]K. Tate, Sustainable Software Development: An Agile Perspective, 1st ed.
Addison-Wesley Professional, 2005.
[8]M. Mahaux, P. Heymans, and G. Saval, “Discovering Sustainability Requirements:
An Experience Report,” in procs REFSQ'11, pp. 19–33.
[9]D. Firesmith, “Engineering Safety and Security Related Requirements for Software
Intensive Systems,” in ICSE Companion, 2007, p. 169.
[10]J. Cabot, S. Easterbrook, J. Horkoff, L. Lessard, S. Liaskos, and J. N. Mazón,
“Integrating Sustainability in Decision-Making Processes: A Modelling Strategy,” in
31st International Conference on Software Engineering-Companion Volume, 2009.
ICSE-Companion 2009, 2009, pp. 207–210.
32

33

RE4ES: Support Environmental Sustainability
by Requirements Engineering
Birgit Penzenstadler1
, Bill Tomlinson2
and Debra Richardson2
1
Technische Universität München, Germany
penzenst@in.tum.de
2
University of California, Irvine, US
wmt@uci.edu, djr@ics.uci.edu
Abstract. [Motivation:] Environmental sustainability is an important
concern. Information and communication technology (ICT) innovation is
ambivalently positioned with regard to our rapid development and short-
ening innovation cycles. On one hand, information technology facilitates
the (excessive) usage of resources. On the other hand, ICT can also help
to significantly reduce human impact on the environment.
[Problem:] Environmental sustainability is currently not supported ex-
plicitly in requirements engineering (RE). This leads to the problem that
(a) environmental sustainability is not yet given sufficient importance
and (b) it is difficult to manifest in requirements design and therefore
hard to assess.
[Principal idea:] We need to combine the knowledge of RE, environ-
mental informatics, and further disciplines, to develop an RE approach
that tailors analysis, documentation, and assessment for ICT systems
where environmental sustainability is a first class quality objective.
[Contribution:] This paper is a research preview on an approach to
help requirements engineers handle sustainability as a first class qual-
ity objective. It elaborates on how we plan to refine and validate this
approach in the future.
Keywords: requirements, sustainability, environment, requirements
engineering, quality modeling
1 Introduction Motivation
The most cited definition of sustainability is to “meet the needs of the present
without compromising the ability of future generations to meet their own needs” [1].
Although our approach primarily aims at environmental sustainability, it must
also be socially (and economically) sustainable in order to have practical signif-
icance [2]. As Mahaux [3] pointed out, we need a toolbox for supporting it in
requirements engineering. We extend the idea of such a toolbox in this research
preview and provide some of our drafts.
Problem: The use of information and communications technology (ICT)
contributes significantly to the usage of our planet’s resources [4]. However, ICT
34

bears a lot of potential for “greening through IT” [5] by making our life more
environmentally sustainable by technological support for our daily life; this is
the context of our research. In contrast, Green IT or “greening of IT” is making
hardware and software of ICT systems more resource-efficient; we do not focus on
this. We must improve the environmental sustainability of humankind to protect
our living space for future generations. Missing is a comprehensive understanding
of how software engineering, and especially requirements engineering (RE), can
help in this endeavor.
Contribution: We are analyzing what and how RE can contribute to the
improvement of the environmental sustainability of ICT. We primarily focus on
the development of ICT systems that have environmental sustainability in their
explicit system vision (and abbreviate these systems with ICT4ES), because we
assume the stakeholders of such systems to be more willing to adapt their devel-
opment processes according to that quality objective. Our goal is to support the
ICT4ES development with an adequate requirements engineering approach that
integrates the knowledge of environmental informatics. This enables software
engineers to handle sustainability as first class quality objective. Our research
questions are:
RQ1: What are the implications for RE of ICT4ES, i.e., when making envi-
ronmental sustainability a first-class quality objective for development?
For ICT4ES as we defined the term, environmental sustainability is an overall
development goal. However, it is not clear how that impacts the requirements
for a system. We seek to understand what is necessary to be taken care of when
developing ICT4ES and how the business processes and business goals differ
from those of traditional products.
RQ2: How can the necessities resulting from ICT4ES be implemented in an
RE approach?
We aim at a toolbox to support the demands resulting from the goal of contribut-
ing to environmental sustainability. First, we analyze which artifacts are neces-
sary to document the newly arising demands and what their concrete contents
are. Then, we investigate which concepts have to be supported and which meth-
ods are required to elaborate these artifacts and how they have to be adapted.
RQ3: How can we assess the impacts of a given software system for environ-
mental sustainability, including both direct and indirect effects, and considering
different groups of stakeholders?
We elaborate metrics to measure environmental sustainability and provide an
answer as to how a system can be proven to fulfill the sustainability requirements
imposed upon it. Furthermore, we investigate an appropriate way to translate
the requirements into acceptance criteria and how these criteria can be incorpo-
rated into an overall quality model.
2 Related Work
Sustainability is beginning to play an important role in software engineering,
with the RE’08 keynote, the ICSE’09 Software Engineering for the Planet spe-
35

cial session, the CAiSE’10 panel, the WSRCC 2009, 2010, and 2011, and the
conference slogan for ICSE’12. The first author of this paper completed a sys-
tematic literature review on sustainability in software engineering [6].
Amsel et al. [7] discuss ideas on how to support sustainability in SE. Cabot
et al. [8] performed a case study for sustainability as goal for the ICSE organi-
zation with i* models to support decision making for future conference chairs.
Naumann et al. [9] investigate how web pages can be developed with little envi-
ronmental impact, i.e., energy-efficiently, and work on a respective guideline for
web developers. Mahaux et al. [3] performed a case study on a business infor-
mation system for an event management agencyto assess how well some current
RE techniques support modeling of specific sustainability requirements.
These works look at either a specific application domain or a specific devel-
opment technique and adapt them to support sustainability modeling, while this
project aims at an encompassing approach to be evaluated in various domains
of ICT4ES systems. No other work yet proposes solutions for how to support
quality modeling of environmental sustainability for software systems.
3 Approach to RE for ICT4ES
Our approach to RE for ICT4ES is planned in two phases: First, we conduct an
analysis of domains as well as values and goals of the respective stakeholders,
then we design a tailored RE method that supports the gathered specifics for
ICT4ES (see Fig. 1). All activities described in this section are in progress, which
means we have started but not yet completed them.
3.1 Analysis of Domains, Values, and Goals
Environmental sustainability can be supported by software systems in different
ways, e.g., (a) information systems for environmental sciences, including climate
models, earthquake warning, etc., (b) information systems that support green
business processes, for example environment-friendly event management, and (c)
embedded systems that lower our energy consumption. Therefore, we need to
analyze the different types of domains that need support in explicitly addressing
environmental sustainability in their software engineering approaches.
Based on the distinction of domains, we perform structured interviews in
industry and academia with representatives from different domains. The inter-
views are followed by a systematic analysis and an interpretation that draws
conclusions for the design of the envisioned method’s elements.
Starting with the results of the interview analysis, we elaborate a map of
values for environmental sustainability and we detail the goals in a taxonomy,
focusing on the ones that relate to requirements engineering for ICT4ES systems:
Value map for environmental sustainability in SE (RQ1) The value
map shall put the value of sustainability into relation with traditional software
engineering values as in the framework described by Khurum [10]. Her framework
36

relies on data gathered in interviews with practitioners and allows to create
impact evaluation patterns from value maps.
Goal taxonomy for sustainability in SE (RQ1) The goal taxonomy de-
composes and details the aspects of environmental sustainability from the point
of view of software engineering. The input is the value map and for each value
we can deduce supporting goals. Initially, most of these goals are independent of
the system to be developed. Each of the goals is then decomposed hierarchically
until the goals are sufficiently specific to be transformed into requirements.
Fig. 1. Environmental Sustainability in Requirements Engineering.
3.2 Design of a Tailored RE Approach
From the goal taxonomy, we gather requirements for artifacts, methods, and
models for the documentation of sustainability requirements arising by deduction
from the goal taxonomy with respect to a specific ICT4ES system. Based on these
requirements and the knowledge acquired in the earlier phases of the project,
we conduct an analysis and evaluation of different techniques, compare existing
approaches, and develop a tailored RE approach including a quality model that
provides indicators and metrics to assess environmental sustainability.
Sustainability requirements artifact model (RQ2) An artifact model
gives guidance on structure and content to be elaborated when documenting
sustainability requirements and related information like environmental impact,
stakeholders, rationale, etc. Based on our experience [11], we develop an artifact
model for representing sustainability requirements and related information.
37

Adapted analysis techniques (RQ2) To transition from goals to require-
ments and to adequately document these requirements according to an artifact
model, we elaborate analysis techniques and documentation methods that form
part of an RE approach tailored to ICT4ES. Solutions include adaptations of
creativity techniques, life cycle analysis, environmental impact assessment and
risk analysis techniques as well as handling of environmental information in form
of data, statistics, and models.
Fig. 2. Model-based Quality Assurance (adapted from [12]) Quality Model Excerpt.
Deduced quality model (RQ3) The quality model is built upon the input
from the value map and the goal taxonomy. A quality model is a model with
the objective to describe, assess and/or predict quality [12]. The activity-based
quality model is elaborated on the basis of concepts proposed in [13]. It includes
criteria for sustainability assessment as well as indicators and metrics to evaluate
and measure a software system’s compliance to the sustainability requirements.
Fig. 2 shows the model-based principle and an excerpt of the quality model draft.
Case studies (RQ1-3) The approach will be evaluated in industrial case
studies, including the value map, the goal taxonomy, the artifact model, the
analysis techniques, and the quality model. The qualitative evaluation will be
implemented as a comparative study. The case study already under way is on
car sharing; another one will be on an irrigation system.
4 Conclusion
In this research preview, we have introduced our ongoing research on a tailored
RE method for ICT systems for environmental sustainability. The analysis phase
investigates the domains and elaborates values and goals with the respective
stakeholders. The design phase provides a tailored artifact model with analysis
38

methods and a deduced quality model. Both will be evaluated in industrial case
studies. We are preparing a guideline for the industry interviews and evaluate
approaches from related disciplines in student seminars as described in [14] for
preliminary studies.
Our contribution will provide software engineers with a toolbox to handle
sustainability as first class quality objective. This enables “greening through
IT” — to produce ICT systems that have positive impact on their surrounding
eco-systems and therefore not only meet the needs of the present (by satisfying
traditional quality objectives) but at the same time preserve the ability of future
generations to meet their own needs (by meeting sustainability quality objec-
tives). As software systems have a profound influence on many different facets
of global civilization, including sustainability in the design of these systems has
the potential to have transformative impacts on the world in which we live.
Acknowledgments: We would like to thank Martin Mahaux for providing
feedback on an earlier version of this paper.
References
1. Brundtland et al.: Our Common Future. In: UN Conference on Environment and
Development. (1987)
2. Sverdrup, H., Svensson, M.G.E.: Defining the concept of sustainability. In: Systems
Approaches and Their Application. Springer (2005) 143–164
3. Mahaux, M., Heymans, P., Saval, G.: Discovering Sustainability Requirements: an
Experience Report. In: 17th REFSQ. (2011)
4. The Climate Group: Smart 2020: Enabling the low carbon economy in the infor-
mation age. Technical report, Global eSustainability Initiative (2008)
5. Tomlinson, B.: Greening through IT. MIT Press Association (2010)
6. Penzenstadler, B., Bauer, V., Calero, C., Franch, X.: Sustainability in Software
Engineering: A Systematic Literature Review. In: 16th Intl. Conf. on Evaluation
and Assessment in Software Engineering. (2012)
7. Amsel, N., Ibrahim, Z., Malik, A., Tomlinson, B.: Toward sustainable software
engineering. In: Proc. of the 33rd Intl. Conf. on Software Engineering. (2011)
8. Cabot et al.: Integrating sustainability in decision-making processes: A modelling
strategy. In: 31st Intl. Conf. on Software Engineering. (2009) 207 –210
9. Naumann, S., Dick, M., Kern, E., Johann, T.: The greensoft model: A reference
model for green and sustainable software and its engineering. Sustainable Com-
puting: Informatics and Systems (2011) –
10. Khurum, M., Gorschek, T.: Software value map - an exhaustive collection of value
aspects for the development of software intensive products (2011)
11. Fernandez, D.M., Lochmann, K., Penzenstadler, B., Wagner, S.: A case study on
the application of an artefact-based requirements engineering approach. In: 15th
Intl. Conf. on Evaluation and Assessment in Software Engineering. (2011)
12. Wagner, S., Deissenboeck, F., Winter, S.: Managing quality requirements using
activity-based quality models. In: Intl. Workshop on Software Quality. (2008)
13. Winter, S., Wagner, S., Deissenboeck, F.: A comprehensive model of usability. In:
Proc. of Engineering Interactive Systems. (2007)
14. Penzenstadler, B., Fleischmann, A.: Teach sustainability in software engineering?
In: 24th Intl. Conference on Software Engineering Education Training. (2011)
39

Writing Requirements for Electromobility and Smart Grids
Systems: Challenges and Opportunities
Jean-Charles Jacquemin1
, Martin Mahaux2
1
CERPE, University of Namur, Belgium,
2
PReCISE, University of Namur, Belgium,
{Martin.Mahaux, Jean-Charles.Jacquemin}@fundp.ac.be
Abstract. If they are to deliver their promises without creating the need to
replace the investments we made in the electric grids in the last decades, electric
vehicles, electric grids and their users will have to work together in a smart way.
We present some opportunities and challenges that lie behind this for
requirements engineers, and stand behind the position that this matter should be
part of their research agenda related to sustainability.
1. Introduction
The renewed interest in electromobility was considered some years ago as a simple
paradigm shift in the automotive sector. In this vision, an Internal Combustion Engine
(ICE) vehicle was simply transformed in an Electric Vehicle (EV) by removing the
fossil fuel engine to replace it by an electric motor. After all, that was the situation in
the early years of the XXth century. However the need to reduce both the imported oil
dependency and the emissions from the transportation sector changed this view [1].
In the same time, and for similar reasons, power utilities are also experiencing an
important shift. While they have built their reputation on the reliability and security of
supply through years of incremental innovations, as we move into the XXIst century
it is evident that the distribution systems concepts are approaching their limits. The
need to incorporate an ever-increasing amount of renewable sources - such as wind
and solar - as well as distributed generation is changing the game. Today, electric
distribution systems are still being designed in an hierarchical model similar to what
was the practice in Computer Networks during the 70’s, and it is widely recognized
that they will have to evolve to a “Energy Web” model, bringing some of the
attributes of the Internet to energy distribution. What is needed is more flexibility,
implementing features like “plug-and-play” and “peer-to-peer” operation, which we
have learned to take for granted in the Internet [2].
Distributed generation of renewable energy as well as electromobility appeared as two
problems for the current electric grid. Integrating adequate ICT systems into it,
40

making it a “Smart Grid”, has the potential to transform these two problems in a set of
opportunities. This is the promise that Smart Grids will have to deliver, and this will
demand smart requirements engineers.
2. Which new ICT systems ?
In this section we define briefly where new ICT systems will have to be integrated
into the grid, and what is so smart about it.
2.1. Smart charging.
The Electric Vehicles (EVs) will represent a new kind of load for the electric network,
with a stochastic behaviour in time and space. An overload of the power system (in its
generation, transmission or distribution components) may occur due to the
simultaneous charging of vehicles. Smart Grids may provide more clever solutions
than just oversizing the system; they will enable smart charging, supplying the
power according to the availabilities of the power system. Consequently, any charging
point will need information about these availabilities [3].
2.2. Storing renewable energies.
On the other side, the storage capacity represented by a float of EVs may, in the
future, become a strong enabler of the introduction of large amounts of renewable
energy into the system. Electric vehicles would be equipped with a plug for
connecting to the Mains and another to connect to the Net. When the vehicle will be
parked at night, at home, it will be connected with both plugs, and it will be connected
again, in the morning, when parked at the office’s garage. While parked, the vehicles
will keep receiving information about the incremental costs of energy. They will store
energy in batteries when it is cheap as there is a lot of wind and solar energy
available, and will sell back the energy when the price is high enough, due to the
scarcity of production. An energy reserve will be kept, in order to enable the users to
continue using the vehicle for the day-to-day needs. Parked in the garage, electric
vehicles will, in the future, help pay themselves by arbitrating on the price of energy.
A simulation of this principle in Belgium can be found in [4]. Again, many
intelligence and information is needed.
Battery swap stations are a particular case because the storage of renewable energies
is centralized in the station which can better accommodates the volatility of renewable
energy supplies [5]. Given the specific situation of the reserve of batteries in the
station, it can also have a significant role as a buffer for load fluctuations in the
network, while removing the EV user anxiety about the battery wear and tear. ICTs
are needed to correctly manage both the energy flows and the EV driver’s usage (both
in terms of energy consumption as financially) of the station.
41

2.3. Peer-to-peer charging stations
A third domain of prime interest is the necessity for EV users to have access to a
sufficient infrastructure of charge points. Public investment appears too costly, too
slow and inefficient. Given this fact, new initiatives of charge infrastructure sharing
appear as Plugshare [6] in the US, or Plugsurfing [7] in Europe. Both initiative use
ICTs to provide information on smartphone applications or on the Internet about
characteristics, status and location of private and public charging points and offer
GPS guidance as well as payment management services.
2.4. Connectivity in the EV
The last domain, less specific in some aspects to EVs only, is the integration of
advanced connectivity services in the e-mobility. It concerns bringing content into the
car, enabling seamless communications to and from it, and controlling your home
from your car. But also technologies helping the user to drive more safely and more
ecologically, including auto collision avoidance, lane drift assistance, parking, speed
monitoring, hands-free, text-to-voice, driver drowsiness detection, remote diagnosis
by the vehicle manufacturer and more [8]. According to Deloitte’s recent survey [9],
those features will be highly demanded by the next generation of drivers.
2.5. Efficient Electricity Markets
To be efficient, markets must get reliable information at the right time. On the supply
side of the market, they need information about the weather, to foresee renewable
energy generation, as well as information about which energy is stored where. The
detection of incorrect use of storage facilities, to avoid a possibly destabilizing
speculation for the only profit of one actor, will require more information. On the
other hand, patterns of EV drivers’ behavior must be estimated to correctly predict the
demand side of the market. Both market sides thus need constant flows of information
to build correct anticipations of equilibrium situations and price levels. The vision of
an important Electricity producer in Germany can be consulted in [10].
3. Writing Requirements for those new systems.
Redesigning the very complex electricity system will involve a huge requirements
effort. There are many stakeholders involved, and many aspects of our societies are
concerned. While it seems clear that most of the technological components are
available today, writing effective requirements for these systems still look like an
important challenge. Below we list a few of the challenging questions that live around
this system, grouped by the class of stakeholder they belong to. The rich picture
below gives an overview of these actors and their principal relations with the grid. It
is freely inspired from [10], [11].
42

Figure 1: EV-centered smart grid and its main actors
Regulator: How to ensure consumer choices and legal rules are respected in the
context of a liberalized electricity market, in particular the free choice of a given
producer, the free choice of a specified pricing scheme? How to deal with rapidly
evolving laws and regulations as we design our systems around it? How will we deal
with technological monopolies (e.g. charging/swapping stations)? How will we
enforce interoperability?
Driver: How will he manage his EV, minimizing its cost, maximizing its financial
return, and still using it as a reliable vehicle? How to deal with uncertainties (potential
mobility emergencies)? Will people allow to be deprived of their vehicle use if
rewarded enough? Or if no other choice? How to change a pre-assigned (dis)charging
scheme in case of uncertainties, in which timeframe? How to choose a provider?
Where to charge? Is the driver ready to make the daily effort needed to manage this
effectively? Or will he ask someone else to do this?
Power Utility: How to manage this new complexity and still ensure reliable and
green power to people in this dynamic environment, for the lower cost? How will he
be able to monitor the state of the system? Which available (un)conditional storage
capacity may be used on the spot? How to foresee the demand in electricity? How to
ensure revenues in this dynamic world?
Integrators: it is already clear that third party operators like integrators will take a
great importance in providing services to users and perhaps producers and or
distributors; the main question is: how to guarantee impartiality, integrity and
confidentiality on the data and their use?
Markets: When the grid needs to buy energy, where will it take it? From who? At
what price? When many users need energy, who will receive it first? At what price?
43

A Survey On Empirical Requirements Engineering Research Practices

A Survey On Empirical Requirements Engineering Research Practices

Recommended

Recommended

More Related Content

Similar to A Survey On Empirical Requirements Engineering Research Practices

Similar to A Survey On Empirical Requirements Engineering Research Practices (20)

More from Sharon Collins

More from Sharon Collins (20)

Recently uploaded

Recently uploaded (20)

A Survey On Empirical Requirements Engineering Research Practices