| 1. |
- Duboc, Leticia, et al.
(author)
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Do we really know what we are building? Raising awareness of potential sustainability effects of software systems in requirements engineering
- 2019
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In: Proceedings of the IEEE International Conference on Requirements Engineering. - : IEEE COMPUTER SOC. - 2332-6441 .- 1090-705X. ; 2019-September, s. 6-16
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Conference paper (peer-reviewed)abstract
- Integrating novel software systems in our society, economy, and environment can have far-reaching effects. As a result, software systems should be designed in such a way as to maintain or improve the sustainability of the socio-technical system of their destination. However, a paradigm shift is required to raise awareness of software professionals on the potential sustainability effects of software systems. While Requirements Engineering is considered the key to driving this change, requirements engineers lack the knowledge, experience and methodological support for doing so. This paper presents a question-based framework for raising awareness of the potential effects of software systems on sustainability, as the first step towards enabling the required paradigm shift. A feasibility study of the framework was carried out with two groups of computer science students. The results of the study indicate that the framework helps enable discussions about potential effects that software systems could have on sustainability.
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| 2. |
- Horkoff, Jennifer, 1980
(author)
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Non-functional requirements for machine learning: Challenges and new directions
- 2019
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In: Proceedings of the IEEE International Conference on Requirements Engineering. - : IEEE. - 2332-6441 .- 1090-705X. ; 2019-September, s. 386-391
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Conference paper (peer-reviewed)abstract
- Machine Learning (ML) provides approaches which use big data to enable algorithms to 'learn', producing outputs which would be difficult to obtain otherwise. Despite the advances allowed by ML, much recent attention has been paid to certain qualities of ML solutions, particularly fairness and transparency, but also qualities such as privacy, security, and testability. From a requirements engineering (RE) perspective, such qualities are also known as non-functional requirements (NFRs). In RE, the meaning of certain NFRs, how to refine those NFRs, and how to use NFRs for design and runtime decision making over traditional software is relatively well established and understood. However, in a context where the solution involves ML, much of our knowledge about NFRs no longer applies. First, the types of NFRs we are concerned with undergo a shift: NFRs like fairness and transparency become prominent, whereas other NFRs such as modularity may become less relevant. The meanings and interpretations of NFRs in an ML context (e.g., maintainability, interoperability, and usability) must be rethought, including how these qualities are decomposed into sub-qualities. Trade-offs between NFRs in an ML context must be re-examined. Beyond the changing landscape of NFRs, we can ask if our known approaches to understanding, formalizing, modeling, and reasoning over NFRs at design and runtime must also be adjusted, or can be applied as-is to this new area? Given these questions, this work outlines challenges and a proposed research agenda for the exploration of NFRs for ML-based solutions.
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| 3. |
- Li, Tong, et al.
(author)
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Towards effective assessment for social engineering attacks
- 2019
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In: Proceedings of the IEEE International Conference on Requirements Engineering. - : IEEE. - 2332-6441 .- 1090-705X. ; 2019-September, s. 392-397
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Conference paper (peer-reviewed)abstract
- Social engineering attacks have drawn more and more attention from both academia and industry, due to the serious threats they pose to information security via exploitation of human vulnerabilities. Unlike technology-based attacks, which have been investigated for decades, there is no efficient security requirements analysis approach for dealing with social engineering attacks. One major obstacle to this problem is the uncertainty of human behavior, making it difficult to effectively assess social engineering attacks. In this paper, we investigate the nature of social engineering attacks and identify their essential factors. Based on such findings, we formulate the problem of social engineering attack assessment, which can be quantitatively calculated using probabilistic model checking. Finally, we present a research agenda that details critical research directions and discusses corresponding challenges.© 2019 IEEE.
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| 4. |
- Mavin, Alistair, et al.
(author)
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Towards an Ontology of Requirements Engineering Approaches
- 2019
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In: Proceedings of the IEEE International Conference on Requirements Engineering. - 2332-6441 .- 1090-705X. - 9781728139128 ; 2019-September
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Conference paper (peer-reviewed)abstract
- Requirements are a key factor in determining the success or failure of the system development process. Requirements engineering is a creative problem-solving process whose primary purpose is to enable researchers and practitioners to apply appropriate theories, models, techniques and tools to understand and support the requirements processes more effectively. However, there is a multitude of ways to conduct the requirements engineering process and the quality of the requirements can be greatly influenced by the approaches employed. While consensus exists that no one approach works in all situations, how do practitioners and researchers select the most relevant and appropriate approach(es)? In order to understand this, we argue that a community-based effort is required to organise the plethora of requirements engineering approaches into an ontology. Such a structure would provide an opportunity to identify gaps and to improve the interfaces between approaches. Crowdsourcing the development and validation of such an ontology would facilitate its application across different system types and application domains.
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