| 1. |
- Habibullah, Khan Mohammad, et al.
(författare)
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Requirements and software engineering for automotive perception systems: an interview study
- 2024
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Ingår i: REQUIREMENTS ENGINEERING. - 0947-3602 .- 1432-010X.
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Tidskriftsartikel (refereegranskat)abstract
- Driving automation systems, including autonomous driving and advanced driver assistance, are an important safety-critical domain. Such systems often incorporate perception systems that use machine learning to analyze the vehicle environment. We explore new or differing topics and challenges experienced by practitioners in this domain, which relate to requirements engineering (RE), quality, and systems and software engineering. We have conducted a semi-structured interview study with 19 participants across five companies and performed thematic analysis of the transcriptions. Practitioners have difficulty specifying upfront requirements and often rely on scenarios and operational design domains (ODDs) as RE artifacts. RE challenges relate to ODD detection and ODD exit detection, realistic scenarios, edge case specification, breaking down requirements, traceability, creating specifications for data and annotations, and quantifying quality requirements. Practitioners consider performance, reliability, robustness, user comfort, and-most importantly-safety as important quality attributes. Quality is assessed using statistical analysis of key metrics, and quality assurance is complicated by the addition of ML, simulation realism, and evolving standards. Systems are developed using a mix of methods, but these methods may not be sufficient for the needs of ML. Data quality methods must be a part of development methods. ML also requires a data-intensive verification and validation process, introducing data, analysis, and simulation challenges. Our findings contribute to understanding RE, safety engineering, and development methodologies for perception systems. This understanding and the collected challenges can drive future research for driving automation and other ML systems.
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| 2. |
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| 3. |
- Habibullah, Khan Mohammad, 1990, et al.
(författare)
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Requirements Engineering for Automotive Perception Systems: An Interview Study
- 2023
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - 1611-3349 .- 0302-9743. - 9783031297854 ; 13975 LNCS, s. 189-205
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Konferensbidrag (refereegranskat)abstract
- Background: Driving automation systems (DAS), including autonomous driving and advanced driver assistance, are an important safety-critical domain. DAS often incorporate perceptions systems that use machine learning (ML) to analyze the vehicle environment. Aims: We explore new or differing requirements engineering (RE) topics and challenges that practitioners experience in this domain. Method: We have conducted an interview study with 19 participants across five companies and performed thematic analysis. Results: Practitioners have difficulty specifying upfront requirements, and often rely on scenarios and operational design domains (ODDs) as RE artifacts. Challenges relate to ODD detection and ODD exit detection, realistic scenarios, edge case specification, breaking down requirements, traceability, creating specifications for data and annotations, and quantifying quality requirements. Conclusions: Our findings contribute to understanding how RE is practiced for DAS perception systems and the collected challenges can drive future research for DAS and other ML-enabled systems.
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| 4. |
- Heyn, Hans-Martin, 1987, et al.
(författare)
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Automotive Perception Software Development : An Empirical Investigation into Data, Annotation, and Ecosystem Challenges
- 2023
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Ingår i: Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023. - : Institute of Electrical and Electronics Engineers Inc.. - 9798350301137 ; , s. 13-24
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Konferensbidrag (refereegranskat)abstract
- Software that contains machine learning algorithms is an integral part of automotive perception, for example, in driving automation systems. The development of such software, specifically the training and validation of the machine learning components, requires large annotated datasets. An industry of data and annotation services has emerged to serve the development of such data-intensive automotive software components. Wide-spread difficulties to specify data and annotation needs challenge collaborations between OEMs (Original Equipment Manufacturers) and their suppliers of software components, data, and annotations.This paper investigates the reasons for these difficulties for practitioners in the Swedish automotive industry to arrive at clear specifications for data and annotations. The results from an interview study show that a lack of effective metrics for data quality aspects, ambiguities in the way of working, unclear definitions of annotation quality, and deficits in the business ecosystems are causes for the difficulty in deriving the specifications. We provide a list of recommendations that can mitigate challenges when deriving specifications and we propose future research opportunities to overcome these challenges. Our work contributes towards the on-going research on accountability of machine learning as applied to complex software systems, especially for high-stake applications such as automated driving.
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| 5. |
- Knauss, Eric, 1977, et al.
(författare)
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Continuous Clarification and Emergent Requirements Flows in Open-Commercial Software Ecosystems
- 2018
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Ingår i: Requirements Engineering. - : Springer Science and Business Media LLC. - 0947-3602 .- 1432-010X. ; 23:1, s. 97-117
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Tidskriftsartikel (refereegranskat)abstract
- Software engineering practice has shifted from the development of products in closed environments towards more open and collaborative efforts. Software development has become significantly interdependent with other systems (e.g. services, apps) and typically takes place within large ecosystems of networked communities of stakeholder organizations. Such software ecosystems promise increased innovation power and support for consumer oriented software services at scale and are characterized by a certain openness of their information flows. While such openness supports project and reputation management, it also brings requirements engineering-related challenges within the ecosystem, such as managing dynamic, emergent contributions from the ecosystem stakeholders, as well as collecting their input while protecting their IP. In this paper we report from a study of requirements communication and management practices within IBM(R)'s Collaborative Lifecycle Management(R) product development ecosystem. Our research used multiple methods for data collection, including interviews within several ecosystem actors, on-site participatory observation, and analysis of online project repositories. We chart and describe the flow of product requirements information through the ecosystem, how the open communication paradigm in software ecosystems provides opportunities for 'just-in-time' RE - and which relies on emergent contributions from the ecosystem stakeholders-, as well as some of the challenges faced when traditional requirements engineering approaches are applied within such an ecosystem. More importantly, we discuss two tradeoffs brought about by the openness in software ecosystems: i) allowing open, transparent communication while keeping intellectual property confidential within the ecosystem, and ii) having the ability to act globally on a long-term strategy while empowering product teams to act locally to answer end-users' context specific needs in a timely manner. A sufficient level of openness facilitates contributions of emergent stakeholders. The ability to include important emergent contributors early in requirements elicitation appears to be a crucial asset in software ecosystems.
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| 6. |
- Knauss, Eric, 1977, et al.
(författare)
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Openness and Requirements: Opportunities and Tradeoffs in Software Ecosystems
- 2014
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Ingår i: Proceedings of 22nd International Requirements Engineering Conference (RE '14). - : IEEE. - 9781479930319 ; , s. 213 - 222
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Konferensbidrag (refereegranskat)abstract
- A growing number of software systems is characterized by continuous evolution as well as by significant interdependence with other systems (e.g. services, apps). Such software ecosystems promise increased innovation power and support for consumer oriented software services at scale, and are characterized by a certain openness of their information flows. While such openness supports project and reputation management, it also brings some challenges to Requirements Engineering (RE) within the ecosystem. We report from a mixed-method study of IBM®'s CLM® ecosystem that uses an open commercial development model. We analyzed data from from interviews within several ecosystem actors, participatory observation, and software repositories, to describe the flow of product requirements information through the ecosystem, how the open communication paradigm in software ecosystems provides opportunities for `just-in-time' RE, as well as some of the challenges faced when traditional requirements engineering approaches are applied within such an ecosystem. More importantly, we discuss two tradeoffs brought about the openness in software ecosystems: i) allowing open, transparent communication while keeping intellectual property confidential within the ecosystem, and ii) having the ability to act globally on a long-term strategy while empowering product teams to act locally to answer end-users' context specific needs in a timely manner.
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| 7. |
- Muhammad, Amna Pir, 1990, et al.
(författare)
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Continuous Experimentation and Human Factors An Exploratory Study
- 2024
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Ingår i: Lecture Notes in Computer Science. - : Springer. - 0302-9743 .- 1611-3349. ; 14483, s. 511-526
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Konferensbidrag (refereegranskat)abstract
- In today's rapidly evolving technological landscape, the success of tools and systems relies heavily on their ability to meet the needs and expectations of users. User-centered design approaches, with a focus on human factors, have gained increasing attention as they prioritize the human element in the development process. With the increasing complexity of software-based systems, companies are adopting agile development methodologies and emphasizing continuous software experimentation. However, there is limited knowledge on how to effectively execute continuous experimentation with respect to human factors within this context. This research paper presents an exploratory qualitative study for integrating human factors in continuous experimentation, aiming to uncover distinctive characteristics of human factors and continuous software experiments, practical challenges for integrating human factors in continuous software experiments, and best practices associated with the management of continuous human factors experimentation.
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| 8. |
- Pir Muhammad, Amna, 1990, et al.
(författare)
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Defining Requirements Strategies in Agile: A Design Science Research Study
- 2022
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 13709 LNCS, s. 73-89
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Konferensbidrag (refereegranskat)abstract
- Research shows that many of the challenges currently encountered with agile development are related to requirements engineering. Based on design science research, this paper investigates critical challenges that arise in agile development from an undefined requirements strategy. We explore potential ways to address these challenges and synthesize the key building blocks of requirements strategies. Our design science research rests on a multiple case study with three industrial cases in the domains of communication technology, security services, and automotive. We relied on a total of 20 interviews, two workshops, participant observation in two cases, and document analysis in each of the cases to understand concrete challenges and workflows. In each case, we define a requirements strategy in collaboration with process managers and experienced engineers. From this experience, we extract guidelines for defining requirements strategies in agile development.
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| 9. |
- Pir Muhammad, Amna, 1990, et al.
(författare)
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Managing Human Factors in Automated Vehicle Development: Towards Challenges and Practices
- 2023
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Ingår i: Proceedings of the IEEE International Conference on Requirements Engineering. - 2332-6441 .- 1090-705X. ; 2023-September, s. 347-352
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Konferensbidrag (refereegranskat)abstract
- Due to the technical complexity and social impact, automated vehicle (AV) development challenges the current state of automotive engineering practice. Research shows that it is important to consider human factors (HF) knowledge when developing AVs to make them safe and accepted. This study explores the current practices and challenges of the automotive industries for incorporating HF requirements during agile AV development. We interviewed ten industry professionals from several Swedish automotive companies, including HF experts and AV engineers. Based on our qualitative analysis of the semi-structured interviews, a number of current approaches for communicating and incorporating HF knowledge into agile AV development and associated challenges are discussed. Our findings may help to focus future research on issues that are critical to effectively incorporate HF knowledge into agile AV development.
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