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2015 IEEE 23rd International Requirements Engineering Conference (RE),
August 24-28, 2015,
Ottawa, ON, Canada
RE:Next! Track
Tracing
Thu, Aug 27, 11:00 - 12:30, FSS 1007 (Chair: Patrick Mäder)
Inherent Characteristics of Traceability Artifacts: Less is More
Jane Huffman Hayes,
Giuliano Antoniol,
Bram Adams, and Yann-Gaël Guéhéneuc
(University of Kentucky, USA; Polytechnique Montréal, Canada)
This paper describes ongoing work to characterize the inherent ease with which a textual artifact pair can be traced using an automated technique. Software traceability approaches collect varied measures to build models that automatically recover links between pairs of natural language documents. Thus far, most of the approaches use a single-step model, such as logistic regression, to identify new traceability links; however, true traceability links are by far in the minority of what is retrieved for a typical artifact pair and this reduces the performance of such models. Instead, this paper formulates the problem of traceability links as the problem of finding, for a given logistic regression model (first step), the subsets of links in the training set giving the best accuracy (in terms of G-metric) on the test set (second step). Using hill climbing with random restart for subset selection, we found that for the ChangeStyle dataset, we can classify links with a precision up to about 83% and a recall up to about 42% using a training set as small as nine true candidate links (27%) and 136 false links (out of 503 wrong links). In order to get better performance and learn the best possible logistic regression classifier, we must “discard” elements in the trace dataset that increase noise and avoid learning on links that are not representative. This is preliminary work, but has promise as it shows that few correct examples may perform better than several poor examples. Keywords: traceability, machine learning, model, logistic regression
@InProceedings{RE15p196,
author = {Jane Huffman Hayes and Giuliano Antoniol and Bram Adams and Yann-Gaël Guéhéneuc},
title = {Inherent Characteristics of Traceability Artifacts: Less is More},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {196--201},
doi = {},
year = {2015},
}
Trace Links Explained: An Automated Approach for Generating Rationales
Jin Guo, Natawut Monaikul, and Jane Cleland-Huang
(DePaul University, USA)
Software Traceability is a critical element in all safety critical software systems. Trace links are created across diverse artifacts such as requirements, design, code, test cases, and hazards -- either manually or with the help of supporting tools. The links are then used to support a range of software engineering activities including impact analysis, compliance verification, and safety inspections. For traceability to effectively support these activities it is important for the meaning and rationale of each link to be clearly communicated. It is often insufficient to know that one artifact satisfies, realizes, or complies to another. Instead, it is important to know why and how it does so. Terms and phrases used to describe artifacts are connected through composition, synonymic, and generalization relationships which often can only be interpreted by domain experts. In this RE:Next! paper we propose a novel approach for utilizing domain-specific knowledge bases to generate trace link rationales. We illustrate our approach with examples of automatically generated rationales taken from the domain of Communication and Control of a Transportation system, and from a Medical Infusion pump domain.
@InProceedings{RE15p202,
author = {Jin Guo and Natawut Monaikul and Jane Cleland-Huang},
title = {Trace Links Explained: An Automated Approach for Generating Rationales},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {202--207},
doi = {},
year = {2015},
}
Goals and NFRs
Thu, Aug 27, 14:00 - 15:30, FSS 1007 (Chair: Jennifer Horkoff)
Handling Non-functional Requirements in Model-Driven Development: An Ongoing Industrial Survey
David Ameller,
Xavier Franch, Cristina Gómez, João Araujo, Richard Berntsson Svensson, Stefan Biffl, Jordi Cabot, Vittorio Cortellessa, Maya Daneva, Daniel Méndez Fernández, Ana Moreira, Henry Muccini, Antonio Vallecillo, Manuel Wimmer, Vasco Amaral, Hugo Brunelière, Loli Burgueño, Miguel Goulão, Bernhard Schätz, and Sabine Teufl
(Universitat Politècnica de Catalunya, Spain; Universidade Nova de Lisboa, Portugal; Blekinge Institute of Technology, Sweden; Chalmers University of Technology, Sweden; University of Gothenburg, Sweden; Vienna University of Technology, Austria; Open University of Catalonia, Spain; University of L'Aquila, Italy; University of Twente, Netherlands; TU München, Germany; University of Málaga, Spain; AtlanMod Team, France; Fortiss, Germany)
Model-Driven Development (MDD) is no longer a novel development paradigm. It has become mature from a research perspective and recent studies show its adoption in industry. Still, some issues remain a challenge. Among them, we are interested in the treatment of non-functional requirements (NFRs) in MDD processes. Very few MDD approaches have been reported to deal with NFRs (and they do it in a limited way). However, it is clear that NFRs need to be considered somehow in the final product of the MDD process. To better understand how NFRs are integrated into the existing MDD approaches, we have initiated the NFR4MDD project, a multi-national empirical study, based on interviews with companies working on MDD projects. Our project aims at surveying the state of the practice for this topic. In this paper, we summarize our research protocol and present the current status of our study. The discussion will focus on the peculiarities of our study's context and organization involving about 20 researchers from 8 European countries.
@InProceedings{RE15p208,
author = {David Ameller and Xavier Franch and Cristina Gómez and João Araujo and Richard Berntsson Svensson and Stefan Biffl and Jordi Cabot and Vittorio Cortellessa and Maya Daneva and Daniel Méndez Fernández and Ana Moreira and Henry Muccini and Antonio Vallecillo and Manuel Wimmer and Vasco Amaral and Hugo Brunelière and Loli Burgueño and Miguel Goulão and Bernhard Schätz and Sabine Teufl},
title = {Handling Non-functional Requirements in Model-Driven Development: An Ongoing Industrial Survey},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {208--213},
doi = {},
year = {2015},
}
Scalable Modeling and Analysis of Requirements Preferences: A Qualitative Approach using CI-Nets
Zachary J. Oster, Ganesh Ram Santhanam, and Samik Basu
(University of Wisconsin-Whitewater, USA; Iowa State University, USA)
We present a framework for reasoning with preferences in the context of Goal-Oriented Requirements Engineering (GORE). Our choice of preference language, conditional importance networks (CI-nets), is motivated by the occurrence in requirements engineering of qualitative preferences and tradeoffs involving sets of items; such preferences are expressed more naturally in CI-nets than in other representations. Building on our past experience with CI-nets, we are improving the scalability and usability of CI-nets for specifying and analyzing requirements preferences. We discuss our ongoing work and long-term plans, including efforts to develop more efficient methods to identify conflicting preferences among possible requirements, guide negotiation of resolutions to such conflicts, and improve traceability and comprehension of requirements preferences.
@InProceedings{RE15p214,
author = {Zachary J. Oster and Ganesh Ram Santhanam and Samik Basu},
title = {Scalable Modeling and Analysis of Requirements Preferences: A Qualitative Approach using CI-Nets},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {214--219},
doi = {},
year = {2015},
}
Rationalization of Goal Models in GRL using Formal Argumentation
Marc van Zee, Floris Bex, and Sepideh Ghanavati
(University of Luxembourg, Luxembourg; Utrecht University, Netherlands; Carnegie Mellon University, USA; Luxembourg Institute of Science and Technology, Luxembourg)
We apply an existing formal framework for practical reasoning with arguments and evidence to the Goal-oriented Requirements Language (GRL), which is part of the User Requirements Notation (URN). This formal framework serves as a rationalization for elements in a GRL model: using attack relations between arguments we can automatically compute the acceptability status of elements in a GRL model, based on the acceptability status of their underlying arguments and the evidence. We integrate the formal framework into the GRL metamodel and we set out a research to further develop this framework.
@InProceedings{RE15p220,
author = {Marc van Zee and Floris Bex and Sepideh Ghanavati},
title = {Rationalization of Goal Models in GRL using Formal Argumentation},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {220--225},
doi = {},
year = {2015},
}
Cognitive
Thu, Aug 27, 16:00 - 17:30, FSS 1007 (Chair: Robyn Lutz)
Cognitive Factors in Inconsistency Management
Irit Hadar and Anna Zamansky
(University of Haifa, Israel)
Inconsistency is a major challenge in requirements engineering, commonly perceived as a problem that needs to be eliminated on sight. However, in practice maintaining consistency at all times is an intractable problem. Accordingly, recent paradigms for inconsistency management acknowledge that it is sometimes desirable to tolerate inconsistency, e.g. to allow distributed teamwork and prevent premature commitment to design decisions. However, a successful adoption of inconsistency management paradigms in industry highly depends on the human factor: intolerant attitudes of practitioners toward inconsistency may pose significant barriers to a wider acceptance of these paradigms. Thus, a thorough analysis of cognitive factors is a key to overcoming these barriers. In this paper we report on our preliminary empirical findings highlighting existing perceptions and attitudes of practitioners toward inconsistency, and propose dimensions for their classification. Based on these results, we outline a general research program for exploring cognitive factors in inconsistency management.
@InProceedings{RE15p226,
author = {Irit Hadar and Anna Zamansky},
title = {Cognitive Factors in Inconsistency Management},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {226--229},
doi = {},
year = {2015},
}
Using Real Options to Manage Technical Debt in Requirements Engineering
Zahra Shakeri Hossein Abad and
Guenther Ruhe
(University of Calgary, Canada)
Abstract- Despite the importance of Requirements Engineering (RE) for the success of software products, most of the requirements decisions such as requirements specification and prioritization are still ad hoc and depend upon the managers' preferences and the trade-offs they make. The Technical Debt (TD) metaphor looks into the trade-offs between short term and long-term goals in software development projects that may lead to increased cost in the future. This problem is mainly due to the lack of a systematic and well-defined approach to manage the high level of uncertainty in requirements decisions.
In this paper, we propose to apply the real options thinking to develop a quantitative method for managing requirements decisions under uncertainty and, more specifically for managing requirements debt in software development projects. A real option is a right without an obligation to make a specific future decision depending on how uncertainty resolves. We demonstrate the application of real options in the context of requirements debt valuation by using the binomial model combined with dynamic programming. We provide an illustrative example to show how uncertainty creates option value and influences requirements decisions and finally outline a future research agenda.
@InProceedings{RE15p230,
author = {Zahra Shakeri Hossein Abad and Guenther Ruhe},
title = {Using Real Options to Manage Technical Debt in Requirements Engineering},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {230--235},
doi = {},
year = {2015},
}
QuantUn: Quantification of Uncertainty for the Reassessment of Requirements
Nelly Bencomo
(Aston University, UK)
Self-adaptive systems (SASs) should be able to adapt to new environmental contexts dynamically. The uncertainty that demands this runtime self-adaptive capability makes it hard to formulate, validate and manage their requirements. QuantUn is part of our longer-term vision of requirements reflection, that is, the ability of a system to dynamically observe and reason about its own requirements. QuantUn's contribution to the achievement of this vision is the development of novel techniques to explicitly quantify uncertainty to support dynamic re-assessment of requirements and therefore improve decision-making for self-adaption. This short paper discusses the research gap we want to fill, present partial results and also the plan we propose to fill the gap.
@InProceedings{RE15p236,
author = {Nelly Bencomo},
title = {QuantUn: Quantification of Uncertainty for the Reassessment of Requirements},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {236--240},
doi = {},
year = {2015},
}
Risks
Fri, Aug 28, 11:00 - 12:30, FSS 1007 (Chair: João Araújo)
Towards Reuse in Safety Risk Analysis Based on Product Line Requirements
Hermann Kaindl, Roman Popp, and David Raneburger
(Vienna University of Technology, Austria)
Risk analysis and requirements engineering for safety-critical systems are expensive and challenging, especially for the very high reliability required, e.g., in the automotive and railway industries. Currently, risk analysis is performed by safety engineers with little or no explicit reuse. Of course, these engineers build on their previous experience in this course, but explicit reuse of related artefacts, e.g., from a dedicated repository is not available according to our best knowledge. The key idea of our approach is reuse in risk analysis based on development and look-up of a repository built around product line requirements. We propose explicit reuse of related artefacts from previous risk analyses, such as information on failures, hazards and safety-related risks. Our assumption is that the risk analysis of a new product of the product line can utilize this information from similar existing products, if available. Therefore, we plan to build a repository of such artefacts and to facilitate its look-up in the course of doing risk analysis. Our innovative approach to extend product-line technology has the expected result of substantially less expensive development of safety-critical systems and shorter time-to-market in such domains through reuse of existing risk-analysis artefacts.
@InProceedings{RE15p241,
author = {Hermann Kaindl and Roman Popp and David Raneburger},
title = {Towards Reuse in Safety Risk Analysis Based on Product Line Requirements},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {241--246},
doi = {},
year = {2015},
}
An Environment-Driven Ontological Approach to Requirements Elicitation for Safety-Critical Systems
Jiale Zhou, Kaj Hänninen, Kristina Lundqvist, Yue Lu, Luciana Provenzano, and Kristina Forsberg
(Mälardalen University, Sweden; Bombardier Transportation, Sweden; Saab, Sweden)
The environment, where a safety critical system (SCS) operates, is an important source from which safety requirements of the SCS can originate. By treating the system under construction as a black box, the environment is typically documented as a number of assumptions, based on which a set of environmental safety requirements will be elicited. However, it is not a trivial task in practice to capture the environmental assumptions to elicit safety requirements. The lack of certain assumptions or too strict assumptions will either result in incomplete environmental safety requirements or waste many efforts on eliciting incorrect requirements. Moreover, the variety of operating environment for an SCS will further complicate the task, since the captured assumptions are at risk of invalidity, and consequently the elicited requirements need to be revisited to ensure safety has not been compromised by the change. This short paper presents an on-going work aiming to 1) systematically organize the knowledge of system operating environment and, 2) facilitate the elicitation of environmental safety requirements. We propose an ontological approach to achieve the objectives. In particular, we utilize conceptual ontologies to organize the environment knowledge in terms of relevant environment concepts, relations among them and axioms. Environmental assumptions are captured by instantiating the environment ontology. An ontological reasoning mechanism is also provided to support elicitation of safety requirements from the captured assumptions.
@InProceedings{RE15p247,
author = {Jiale Zhou and Kaj Hänninen and Kristina Lundqvist and Yue Lu and Luciana Provenzano and Kristina Forsberg},
title = {An Environment-Driven Ontological Approach to Requirements Elicitation for Safety-Critical Systems},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {247--251},
doi = {},
year = {2015},
}
Goals at Risk? Machine Learning at Support of Early Assessment
Paolo Avesani, Anna Perini,
Alberto Siena, and Angelo Susi
(Fondazione Bruno Kessler, Italy)
A relevant activity in the requirements engineering process consists in the identification, assessment and management of potential risks, which can prevent the system-to-be from meeting stakeholder needs. However, risk analysis techniques are often time- and resource- consuming activities, which may introduce in the requirements engineering process a significant overhead. To overcome this problem, we aim at supporting risk management activity in a semi-automated way, merging the capability to exploit existing risk-related information potentially present in a given organisation, with an automated ranking of the goals with respect to the level of risk the decision-maker estimates for them. In particular, this paper proposes an approach to address the general problem of risk decision-making, which combines knowledge about risks assessment techniques and Machine Learning to enable an active intervention of human evaluators in the decision process, learning from their feedback and integrating it with the organisational knowledge. The long term objective is that of improving the capacity of an organisation to be aware and to manage risks, by introducing new techniques in the field of risk management that are able to interactively and continuously extract useful knowledge from the organisation domain and from the decision-maker expertise.
@InProceedings{RE15p252,
author = {Paolo Avesani and Anna Perini and Alberto Siena and Angelo Susi},
title = {Goals at Risk? Machine Learning at Support of Early Assessment},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {252--255},
doi = {},
year = {2015},
}
Mass RE
Fri, Aug 28, 14:00 - 15:00, FSS 1007 (Chair: Anna Perini)
Democratic Mass Participation of Users in Requirements Engineering?
Timo Johann and
Walid Maalej
(University of Hamburg, Germany)
A large part of Requirements Engineering is concerned with involving system users, capturing their needs, and getting their feedback. As users are becoming more and more demanding, markets and technologies are evolving fast, and systems are getting more and more individual, a broad and systematic user involvement in Requirements Engineering is becoming more important than ever. This paper presents the idea of pushing user involvement in Requirements Engineering to its extreme by systematically delegating the responsibility for developing the requirements and deciding about future releases to the crowd of users. We summarize the pros and cons of this vision, its main challenges, and sketch promising solution concepts, which have been proposed and used in E-Participation and E-Democracy. We discussed our vision with ten experts from the fields of Requirements Engineering, politics, psychology, and market research, who were partly supportive partly skeptical.
@InProceedings{RE15p256,
author = {Timo Johann and Walid Maalej},
title = {Democratic Mass Participation of Users in Requirements Engineering?},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {256--261},
doi = {},
year = {2015},
}
Exploiting Online Human Knowledge in Requirements Engineering
Anas Mahmoud and Doris Carver
(Louisiana State University, USA)
Data-driven Natural Language Processing (NLP) methods have noticeably advanced in the past few years. These advances can be tied to the drastic growth of the quality of collaborative knowledge bases (KB) available on the World Wide Web. Such KBs contain vast amounts of up-to-date structured human knowledge and common sense data that can be exploited by NLP methods to discover otherwise-unseen semantic dimensions in text, aiding in tasks related to natural language understanding, classification, and retrieval. Motivated by these observations, we describe our research agenda for exploiting online human knowledge in Requirements Engineering (RE). The underlying assumption is that requirements are a product of the human domain knowledge that is expressed mainly in natural language. In particular, our research is focused on methods that exploit the online encyclopedia Wikipedia as a textual corpus. Wikipedia provides access to a massive number of real-world concepts organized in hierarchical semantic structures. Such knowledge can be analyzed to provide automated support for several exhaustive RE activities including requirements elicitation, understanding, modeling, traceability, and reuse, across multiple application domains. This paper describes our preliminary findings in this domain, current state of research, and prospects of our future work.
@InProceedings{RE15p262,
author = {Anas Mahmoud and Doris Carver},
title = {Exploiting Online Human Knowledge in Requirements Engineering},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {262--267},
doi = {},
year = {2015},
}
Frameworks
Fri, Aug 28, 14:00 - 15:00, FSS 1006 (Chair: Mehrdad Sabetzadeh)
Towards Engineering Transparency as a Requirement in Socio-technical Systems
Mahmood Hosseini, Alimohammad Shahri, Keith Phalp, and
Raian Ali
(Bournemouth University, UK)
The improvement and success of socio-technical systems depend on the joint optimisation of both the social and the technical parts. Improving the social part of a socio-technical system is a meticulous task, as social requirements are diverse and dynamic, and they usually evolve with time and context. Information transparency (henceforth, transparency) is one of the social requirements that can affect the overall attitude of the stakeholders present within a socio-technical system, and influence their other social requirements such as privacy, trust, collaboration and non-bias. In this paper, we advocate the need to engineer transparency as a first class requirement, propose a baseline model for transparency and show how this model can be a starting point for the analysis of transparency requirements of different stakeholders. We showcase our on-going research in the modelling and analysis of transparency as a requirement, discuss some of the challenges of transparency requirements elicitation, and present our future work.
@InProceedings{RE15p268,
author = {Mahmood Hosseini and Alimohammad Shahri and Keith Phalp and Raian Ali},
title = {Towards Engineering Transparency as a Requirement in Socio-technical Systems},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {268--273},
doi = {},
year = {2015},
}
Towards a General Formal Framework of Coherence Management in RE
Alexander Borgida,
Ivan Jureta, and Anna Zamansky
(Rutgers University, USA; University of Namur, Belgium; University of Haifa, Israel)
Coherence Management refers to all efforts one needs to invest, in order to ensure that information shown in, and implied by a representation of requirements makes sense as a whole, is coherent. Coherence Management is an umbrella term we use to cover, and more importantly, stimulate research on relationships between identification, measurement, and action on phenomena which reflect tensions between information in requirements representations. Such tensions exist between information which is, for example, logically inconsistent, or stakeholders disagree on, or signals tradeoffs (meaning that improvement on some requirements, for instance, necessarily means some quantifiable (or not) deterioration of others). These tensions are an important topic of research in Requirements Engineering, and various methods have been proposed for the identification, measurement, and action on logical inconsistency in requirements models, on negotiating disagreements, and on settling tradeoffs. Despite focusing on related phenomena, these methods are different and each come with their own specific definition of when a representation of requirements is incoherent and what to do about it. This makes it hard to compare existing methods, design new ones, and choose those to apply when doing RE. In this short communication we outline our research agenda for developing a unified formal framework for the systematization and classification of Coherence Management efforts in the context of RE, as well as exploring their compatibility.
@InProceedings{RE15p274,
author = {Alexander Borgida and Ivan Jureta and Anna Zamansky},
title = {Towards a General Formal Framework of Coherence Management in RE},
booktitle = {Proc.\ RE},
publisher = {IEEE},
pages = {274--277},
doi = {},
year = {2015},
}
proc time: 0.26