| 1. |
- Knauss, Eric, 1977, et al.
(författare)
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Supporting Continuous Integration by Code-Churn Based Test Selection
- 2015
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Ingår i: RCoSE - 2nd International Workshop on Rapid Continuous Software Engineering @ ICSE 2015 Florence, Italy.
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Continuous integration promises advantages in large-scale software development by enabling software development organizations to deliver new functions faster. However, implementing continuous integration in large software development organizations is challenging because of organizational, social and technical reasons. One of the technical challenges is the ability to rapidly prioritize the test cases which can be executed quickly and trigger the most failures as early as possible. In our research we propose and evaluate a method for selecting a suitable set of functional regression tests on system level. The method is based on analysis of correlations between test-case failures and source code changes and is evaluated by combining semi-structured interviews and workshops with practitioners at Ericsson and Axis Communications in Sweden. The results show that using measures of precision and recall, the test cases can be prioritized. The prioritization leads to finding an optimal test suite to execute before the integration.
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| 2. |
- Habibullah, Khan Mohammad, et al.
(författare)
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Requirements and software engineering for automotive perception systems: an interview study
- 2024
-
Ingår i: REQUIREMENTS ENGINEERING. - 0947-3602 .- 1432-010X. ; 29:1, s. 25-48
-
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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| 3. |
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| 4. |
- Habibullah, Khan Mohammad, 1990, et al.
(författare)
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Requirements Engineering for Automotive Perception Systems: An Interview Study
- 2023
-
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
-
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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| 5. |
- 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
-
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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| 6. |
- Kasauli, Rashida, 1984, et al.
(författare)
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Agile Islands in a Waterfall Environment: Challenges and Strategies in Automotive
- 2020
-
Ingår i: ACM International Conference Proceeding Series. - New York, NY, USA : ACM. ; , s. 31-40
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Konferensbidrag (refereegranskat)abstract
- Driven by the need for faster time-to-market and reduced development lead-time, large-scale systems engineering companies are adopting agile methods in their organizations. This agile transformation is challenging and it is common that adoption starts bottom-up with agile software teams within the context of traditional company structures. This creates the challenge of agile teams working within a document-centric and plan-driven (or waterfall) environment. While it may be desirable to take the best of both worlds, it is not clear how that can be achieved especially with respect to managing requirements in large-scale systems. This paper presents an exploratory case study focusing on two departments of a large-scale systems engineering company (automotive) that is in the process of company-wide agile adoption. We present challenges that agile teams face while working within a larger plan-driven context and propose potential strategies to mitigate the challenges. Challenges relate to, e.g., development teams not being aware of the high-level requirements, difficulties to manage change of these requirements as well as their relationship to backlog items such as user stories. While we found strategies for solving most of the challenges, they remain abstract and empirical research on their effectiveness is currently lacking.
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| 7. |
- Kasauli, Rashida, 1984, et al.
(författare)
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Requirements Engineering Challenges in Large-Scale Agile System Development
- 2017
-
Ingår i: International Requirements Engineering Conference. - : IEEE. - 9781538631911 ; , s. 352-361
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Konferensbidrag (refereegranskat)abstract
- Agile methods have proven their value to accelerate delivery of high quality software products and services to customers. End-users have become used to regular updates that fix bugs and provide new features and for software products, short time-to-market has become an important business driver. In order to remain competitive, more and more companies imple- ment agile methods and their practices also for software-intense, large products, such as cars, telecommunication infrastructure, and embedded systems. Development of such system usually relies on plan-driven, stage-gate processes and is subject to safety and regulative concerns. Consequently, requirements engineering involves upfront and detailed analysis, which can be at odds with agile (software) development. In this paper, we present results from a multiple case study with two car manufacturers, a telecommunications company, and a technology company that are on the journey to introduce organization wide continuous integration and continuous delivery to customers. Based on 20 qualitative interviews, 5 focus groups, and 2 cross-company workshops, we discuss possible scopes of agile methods within system development, the consequences this has on the role of requirements, and the challenges that arise from the interplay of requirements engineering and agile methods in large-scale system development. These relate in particular to communicating and managing knowledge about a) customer value and b) the system under development. We argue that better alignment of a holistic requirements model with agile development practices promises rich gains in development speed, flexibility, and overall quality of software and systems.
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| 8. |
- Kasauli, Rashida, 1984, et al.
(författare)
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Safety-Critical Systems and Agile Development: A Mapping Study
- 2018
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Ingår i: Proceedings - 44th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2018. ; , s. 470-477
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Konferensbidrag (refereegranskat)abstract
- In the last decades, agile methods had a huge impact on how software is developed. In many cases, this has led to significant benefits, such as quality and speed of software deliv- eries to customers. However, safety-critical systems have widely been dismissed from benefiting from agile methods. Products that include safety critical aspects are therefore faced with a situation in which the development of safety-critical parts can significantly limit the potential speed-up through agile methods, for the full product, but also in the non-safety critical parts. For such products, the ability to develop safety-critical software in an agile way will generate a competitive advantage. In order to enable future research in this important area, we present in this paper a mapping of the current state of praxis based on a mixed method approach. Starting from a workshop with experts from six large Swedish product development companies we develop a lens for our analysis. We then present a systematic mapping study on safety-critical systems and agile development through this lens in order to map potential benefits, challenges, and solution candidates for guiding future research.
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| 9. |
- 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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| 10. |
- Knauss, Eric, 1977, et al.
(författare)
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Openness and Requirements: Opportunities and Tradeoffs in Software Ecosystems
- 2014
-
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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| 11. |
- Muhammad, Amna Pir, 1990, et al.
(författare)
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Continuous Experimentation and Human Factors An Exploratory Study
- 2024
-
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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| 12. |
- Pir Muhammad, Amna, 1990, et al.
(författare)
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Defining Requirements Strategies in Agile: A Design Science Research Study
- 2022
-
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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| 13. |
- Pir Muhammad, Amna, 1990, et al.
(författare)
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Managing Human Factors in Automated Vehicle Development: Towards Challenges and Practices
- 2023
-
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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| 14. |
- Pir Muhammad, Amna, 1990, et al.
(författare)
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Requirements Strategy for Managing Human Factors in Automated Vehicle Development
- 2024
-
Ingår i: Proceedings of the IEEE International Conference on Requirements Engineering. - 2332-6441 .- 1090-705X. ; , s. 180-192
-
Konferensbidrag (refereegranskat)abstract
- The integration of human factors (HF) knowledge is crucial when developing safety-critical systems, such as automated vehicles (AVs). Ensuring that HF knowledge is considered continuously throughout the AV development process is essential for several reasons, including efficacy, safety, and acceptance of these advanced systems. However, it is challenging to include HF as requirements in agile development. Recently, Requirements Strategies have been suggested to address requirements engineering challenges in agile development. By applying the concept of Requirements Strategies as a lens to the investigation of HF requirements in agile development of AVs, this paper arrives at three areas for investigation: a) ownership and responsibility for HF requirements, b) structure of HF requirements and information models, and c) definition of work and feature flows related to HF requirements. Based on 13 semi-structured interviews with professionals from the global automotive industry, we provide qualitative insights in these three areas. The diverse perspectives and experiences shared by the interviewees provide insightful views and helped to reason about the potential solution spaces in each area for integrating HF within the industry, highlighting the real-world practices and strategies used.
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| 15. |
- Alégroth, Emil, 1984, et al.
(författare)
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Teaching scrum – what we did, what we will do and what impedes us
- 2015
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Ingår i: Lecture Notes in Business Information Processing. - 1865-1348 .- 1865-1356. - 9783319186115 ; 212, s. 361-362
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This paper analyses the way we teach Scrum. We reflect on our intended learning outcomes, which challenges we find in teaching Scrum and which lessons we have learned during the last four years. We also give an outlook on the way we want to introduce and apply Scrum in our teaching and how we intend to improve the curriculum.
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| 16. |
- Averbakh, Anna, et al.
(författare)
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Dedicated Support for Experience Sharing in Distributed Software Projects
- 2014
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Ingår i: Proceedings of 26th International Conference on Software Engineering and Knowledge Engineering (SEKE '14). ; , s. 355-360
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Konferensbidrag (refereegranskat)abstract
- Systematic management of experience and knowledge in distributed software development promises huge increases in effectivity and efficiency. Yet, specific problems need to be overcome: Communication between partners is difficult and awareness about the knowledge available at different locations is impaired. Even motivated developers are often reluctant to share experiences, because they do not know where and how to submit them as well as if they are allowed to share sensitive information or intellectual property. If they submit, their experiences are often presented in a way not useful for others and cannot be easily refined into best practices. In this paper we identify barriers of knowledge sharing in a literature review and discuss how dedicated tool support and automated heuristic critiques can mitigate such problems by offering the following features and qualities: guidance of project participants in creating experiences that will more likely be helpful, positive influence of their motivation to share, and easily accessible and integrated into a trustworthy experience engineering processes. Preliminary evaluation with a prototype shows that this concept can increase willingness to submit experience as well as their quality.
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| 17. |
- Berger, Christian, 1980, et al.
(författare)
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The use of AI in AV human-factors research and human-factors requirements in AI-based AV design : Deliverable 2.4 in the EC ITN project SHAPE-IT
- 2023
-
Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The design of automated vehicles (AVs) today is being enabled by the rise of new technologies, actually in particular recent advances in Artificial Intelligence (AI). Navigating the challenges and potential of this technology is crucial for the organizations that develop AVs, as well as for societies that rely on smart transportation. In this report, we consider two perspectives on these technologies in AV research and design, with a particular focus on human factors (HF): (A) Human-Factors Requirements in AV Development, and (B) The Use of AI in Research about Vehicle-Human-Interaction. We describe each part separately; they are different enough to stand on their own, while both descriptions together make up this report. We start with the first perspective – investigating how AI can facilitate HF research and practical use of AI to predict human behaviour for use by HF designers. To support HF researchers and automation designers with tools for classifying and predicting interaction behaviours between AVs/vehicles and pedestrians in urban environments, we developed AI-based models (eg., Zhang et al., 2023) to predict the outcomes of pedestrian-vehicle interactions at unsignalised crossings. The models include random forest models, support vector machine models, and neural network models. The input consists of multiple features such as time to arrival (TTA), pedestrian waiting time, presence of a zebra crossing, and properties and personality traits of both pedestrians and drivers. The output consists of interaction outcomes such as crossing behaviour, crossing duration, and crossing initiation time. The predicted outcomes can contribute to a better understanding of the interactions. In addition, we analysed the interaction factors in order to support HF researchers and automation designers in their efforts to design safer interaction interface. We reviewed a large selection of papers that used AI to predict pedestrian behaviour and interactions (Zhang and Berger, 2023). We proposed a framework of AI-based tools for predicting pedestrian behaviours and summarized some guidelines for using AI—especially deep learning methods for pedestrian behaviour and interaction prediction. Furthermore, our own body of work (Zhang et al., 2021, Zhang and Berger, 2022a, Zhang and Berger, 2022b, Zhang et al., 2023) provides detailed steps for developing an example of an AI model. A key contribution of our research is metrics that allow the evaluation and assessment of AI’s success at classifying and predicting pedestrian-vehicle interactions. In our study, we compared AI models with traditional linear models (Zhang et al., 2023). Further, we compared the performance of AI models and traditional methods with fewer input factors; traditional methods perform well when there are fewer, while AI-based methods perform better when dealing with more input factors. This finding provides information for optimal model selection in different scenarios. To summarize, our findings suggest that AI can help us understand the intentions of human actors and predict their next steps when they interact with AVs. The second perspective investigates how HF research can facilitate AV development activities. We had anticipated that the reliance of AV on AI technology might play a major role in how developers need to think about HF (hence, this aspect is also reflected in the title of this report). Our reasoning was that AI-based AV provide a larger surface of interaction between humans and AVs, not only through the traditional human machine interface. However, early in the project we identified that there was a need to address not only the AI-based aspects of HF requirements in AV development, but also to address HF requirements overall in AV development – not the least within agile ways of working. We therefore decided to include AI-based AV development considerations as part of the larger scope of studying HF requirements in the context of AV development, with focus on agile processes. The agile angle was chosen as AV development increasingly incorporates agile and continuous development approaches. We find that it is conceptually unclear how to systematically incorporate HF in such a fast-paced environment. Further, the automotive industry used as our subject of study is lacking guidelines (as well as best practices) for incorporating HF into these ways of working. We propose the development and application of a HF requirements strategy to manage key implications, for which our research suggests useful templates and guidelines.
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| 18. |
- Brunotte, Wasja, et al.
(författare)
-
Welcome to the First International Workshop on Requirements Engineering for Explainable Systems (RE4ES)
- 2021
-
Ingår i: Proceedings of the IEEE International Conference on Requirements Engineering. - 2332-6441 .- 1090-705X. ; 2021-September, s. 157-158
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Konferensbidrag (refereegranskat)abstract
- Welcome to the First International Workshop on Requirements Engineering for Explainable Systems (RE4ES), where we aim to advance requirements engineering (RE) for explainable systems, foster interdisciplinary exchange, and build a community. On the one hand, we believe that the methods and techniques of the RE community can add much value to explainability research. On the other hand, we have to ensure that we develop techniques fitted to the needs of other communities.This first workshop explores synergies between the RE community and other communities already researching explainability.To this end, we have based our agenda on a mix of paper presentations from authors of different domains, one keynote from industry and one from research, as well as interactive activities to stimulate lively discussions.
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| 19. |
- de Oliveira Neto, Francisco Gomes, et al.
(författare)
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Challenges of Aligning Requirements Engineering and System Testing in Large-Scale Agile: A Multiple Case Study
- 2017
-
Ingår i: 2017 IEEE 25th International Requirements Engineering Conference Workshops (REW), 4-8 Sept. 2017, Lisbon, Portugal. - : IEEE. - 9781538634882
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Konferensbidrag (refereegranskat)abstract
- Abstract: As agile methods become more pervasive, agile practices are applied to more large-scale systems with a scope that goes beyond pure software. The expansion of agile in these contexts provides benefits, but creates new challenges. Widespread use of agile has changed the way we must think about practices both in Requirements Engineering (RE) and in System Testing (ST). Our experience shows that many challenges in the application of large-scale agile development relate to either RE or ST, and in particular to the alignment between these areas. In this paper we present large-scale agile-related challenges from a multiple case study which relate to REST alignment. We map our challenges to an existing framework for REST alignment, and make an initial attempt to suggest agile RE practices from the literature which may alleviate these challenges. Our results show that the interviewed companies need to first adopt more agile RE practices to enhance REST alignment and then leverage agile testing. Future work will look more towards evaluating these best practices.
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| 20. |
- Eliasson, Ulf, 1984, et al.
(författare)
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The Need of Complementing Plan-Driven Requirements Engineering with Emerging Communication: Experiences from Volvo Car Group
- 2015
-
Ingår i: 23rd IEEE International Requirements Engineering Conference, RE 2015, Ottawa, Canada, 24-28 August. - : IEEE. - 9781467369053
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Konferensbidrag (refereegranskat)abstract
- The automotive industry is currently going through an enormous change, transitioning from being pure hardware and mechanical companies to becoming more software focused. Currently, software development is embedded into a V-Model process that defines how software requirements are extracted from system requirements. In recent years, OEMs have come to recognize the importance and opportunities offered by software, which include better management and shorter time-to-market of distinguishing features. Strategies to better utilize software include in-house software development and new ways to collaborate with suppliers. However, in their effort to take advantage of these opportunities, engineers struggle with the formal process imposed on software development. In this paper, we investigate the impact of this struggle on the flow of requirements, including challenges and practices. We found that new ways of working with requirements had emerged that are partly not supported, partly hindered by the old tooling and processes for requirements engineering. Requirements flow both vertical and horizontal in the organization and across the supply-chain. Support for the new way of working should allow us to refine requirements iteratively throughout their life-cycle, handle the discussion of rationales, and to manage assumptions. We found strategies of achieving this to differ not only between OEMs, but also between different divisions inside the OEMs.
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| 21. |
- Evbota, Felix, et al.
(författare)
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Scaling up the Planning Game: Collaboration Challenges in Large Scale Agile Product Development
- 2016
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Ingår i: 17th International Conference on Agile Processes in Software Engineering and Extreme Programming, XP 2016, Edinburgh, United Kingdom, 24-27 May 2016. - Cham : Springer International Publishing. - 1865-1348 .- 1865-1356. - 9783319335148 ; , s. 28-38
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Konferensbidrag (refereegranskat)abstract
- One of the benefits of agile is close collaboration of customer and developer. This ensures good commitment and excellent knowledge flows of information about priorities and efforts. However, it is unclear if this benefit can be leveraged at scale. Clearly, it is infeasible to use practices such as planning game with several agile teams in the room. In this paper, we investigate how a large-scale agile organization manages, what challenges exist, and which opportunities can be leveraged. We found challenges in three areas: (i) the abil-ity to estimate, prioritize, and plan; (ii) the context of planning with respect to working environment, team build-up, and team spirit; and (iii) the ceremonial agreement which promises to allow leveraging abilities in a given context.
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| 22. |
- Fagerström, Martin, 1979, et al.
(författare)
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Verdict Machinery: On the need to automatically make sense of test results
- 2016
-
Ingår i: International Symposium on Software Testing and Analysis (ISSTA '16). - New York, NY, USA : ACM. - 9781450343909 ; , s. 225-234
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Konferensbidrag (refereegranskat)abstract
- Along with technological developments and increasing competition there is a major incentive for companies to produce and market high quality products before their competitors. In order to conquer a bigger portion of the market share, companies have to ensure the quality of the product in a shorter time frame. To accomplish this task companies try to automate their test processes as much as possible. It is critical to investigate and understand the problems that occur during different stages of test automation processes. In this paper we report on a case study on automatic analysis of non-functional test results.We discuss challenges in the face of continuous integration and deployment and provide improvement suggestions based on interviews at a large company in Sweden. The key contributions of this work are filling the knowledge gap in research about performance regression test analysis automation and providing warning signs and a road map for the industry.
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| 23. |
- Franch, Xavier, et al.
(författare)
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How do Practitioners Perceive the Relevance of Requirements Engineering Research?
- 2022
-
Ingår i: IEEE Transactions on Software Engineering. - : Institute of Electrical and Electronics Engineers Inc.. - 0098-5589 .- 1939-3520. ; 48:6, s. 1947-1964
-
Tidskriftsartikel (refereegranskat)abstract
- Context: The relevance of Requirements Engineering (RE) research to practitioners is vital for a long-term dissemination of research results to everyday practice. Some authors have speculated about a mismatch between research and practice in the RE discipline. However, there is not much evidence to support or refute this perception. Objective: This paper presents the results of a study aimed at gathering evidence from practitioners about their perception of the relevance of RE research and at understanding the factors that influence that perception. Method: We conducted a questionnaire-based survey of industry practitioners with expertise in RE. The participants rated the perceived relevance of 435 scientific papers presented at five top RE-related conferences. Results: The 153 participants provided a total of 2,164 ratings. The practitioners rated RE research as essential or worthwhile in a majority of cases. However, the percentage of non-positive ratings is still higher than we would like. Among the factors that affect the perception of relevance are the paper?s links to industry, the research method used, and respondents? roles. The reasons for positive perceptions were primarily related to the relevance of the problem and the soundness of the solution, while the causes for negative perceptions were more varied. The respondents also provided suggestions for future research, including topics researchers have studied for decades, like elicitation or requirement quality criteria. Conclusions: The study is valuable for both researchers and practitioners. Researchers can use the reasons respondents gave for positive and negative perceptions and the suggested research topics to help make their research more appealing to practitioners and thus more prone to industry adoption. Practitioners can benefit from the overall view of contemporary RE research by learning about research topics that they may not be familiar with, and compare their perception with those of their colleagues to self-assess their positioning towards more academic research. IEEE
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| 24. |
- Franch, Xavier, et al.
(författare)
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How do Practitioners Perceive the Relevance of Requirements Engineering Research? An Ongoing Study
- 2017
-
Ingår i: 2017 IEEE 25TH INTERNATIONAL REQUIREMENTS ENGINEERING CONFERENCE (RE). - : IEEE. - 2332-6441. - 9781538631911 ; , s. 382-387
-
Konferensbidrag (refereegranskat)abstract
- The relevance of Requirements Engineering (RE) research to practitioners is a prerequisite for problem-driven research in the area and key for a long-term dissemination of research results to everyday practice. To understand better how industry practitioners perceive the practical relevance of RE research, we have initiated the RE-Pract project, an international collaboration conducting an empirical study. This project opts for a replication of previous work done in two different domains and relies on survey research. To this end, we have designed a survey to be sent to several hundred industry practitioners at various companies around the world and ask them to rate their perceived practical relevance of the research described in a sample of 418 RE papers published between 2010 and 2015 at the RE, ICSE, FSE, ESEC/FSE, ESEM and REFSQ conferences. In this paper, we summarize our research protocol and present the current status of our study and the planned future steps.
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| 25. |
- Granli, William, et al.
(författare)
-
The Driving Forces of API Evolution
- 2015
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Ingår i: ESEC/FSE 2015 Workshops - 14th International Workshop on Principles of Software Evolution (IWPSE 2015) proceedings. - New York, NY, USA : ACM. - 9781450338165 ; , s. 28-37
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Evolving an Application Programming Interface (API) is a delicate activity, as modifications to them can significantly impact their users. The increasing use of APIs means that software development organisations must take an empirical and scientific approach to the way they manage the evolution of their APIs. If no attempt at analysing or quantifying the evolution of an API is made, there will be a diminished understanding of the evolution, and possible improvements to the maintenance strategy will be difficult to identify. We believe that long-standing software evolution theories can provide additional insight to the field of APIs, and can be of great use to companies maintaining APIs. In this case study, we conduct a qualitative investigation to understand what drives the evolution of an industry company's existing API, by examining two versions of the API interface. The changes were analysed based on two software evolution theories, and the extent to which we could reverse engineer the change decisions was determined by interviewing an architect of the API. The results of this analysis show that the largest driving force of the APIs evolution was the desire for new functionality. Our findings which show that changes happen sporadically, rather than continuously, appear to show that the law of Conservation of Organisational Stability was not a considerable factor for the evolution of the API. We also found that it is possible to reverse engineer change decisions and in doing so, identified that the feedback loop of an API is an important area of improvement.
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| 26. |
- Hammouda, Imed, et al.
(författare)
-
Continuous API-Design for Software Ecosystems
- 2015
-
Ingår i: Proceedings of 2nd International Workshop on Rapid and Continuous Software Engeering (RCoSE '15 @ ICSE). - : IEEE. - 9781467370677
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Today more and more software operates in a software ecosystem where software products and services are shared over a common technological platform between business actors. In such a setting, a software platforms’ API becomes the interface between the platform and its owner(s) on the one side and other actors and their extensions on the other side. In such ecosystem context, platform API fitness for application development has a huge impact on the success of the ecosystem. However, software ecosystems are usually evolving at a high pace given their dynamic structure and the continuously changing business strategies of ecosystem actors. The design of APIs for software ecosystems therefore has to co-evolve. In this position paper, we propose a continuous (re-)assessment method for platform APIs that takes into account ecosystem needs. We illustrate the method with insights from ongoing case studies.
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| 27. |
- Heyn, Hans-Martin, 1987, et al.
(författare)
-
A compositional approach to creating architecture frameworks with an application to distributed AI systems
- 2023
-
Ingår i: Journal of Systems and Software. - : Elsevier BV. - 0164-1212. ; 198
-
Tidskriftsartikel (refereegranskat)abstract
- Artificial intelligence (AI) in its various forms finds more and more its way into complex distributed systems. For instance, it is used locally, as part of a sensor system, on the edge for low-latency high-performance inference, or in the cloud, e.g. for data mining. Modern complex systems, such as connected vehicles, are often part of an Internet of Things (IoT). This poses additional architectural challenges. To manage complexity, architectures are described with architecture frameworks, which are composed of a number of architectural views connected through correspondence rules. Despite some attempts, the definition of a mathematical foundation for architecture frameworks that are suitable for the development of distributed AI systems still requires investigation and study. In this paper, we propose to extend the state of the art on architecture framework by providing a mathematical model for system architectures, which is scalable and supports co-evolution of different aspects for example of an AI system. Based on Design Science Research, this study starts by identifying the challenges with architectural frameworks in a use case of distributed AI systems. Then, we derive from the identified challenges four rules, and we formulate them by exploiting concepts from category theory. We show how compositional thinking can provide rules for the creation and management of architectural frameworks for complex systems, for example distributed systems with AI. The aim of the paper is not to provide viewpoints or architecture models specific to AI systems, but instead to provide guidelines based on a mathematical formulation on how a consistent framework can be built up with existing, or newly created, viewpoints. To put in practice and test the approach, the identified and formulated rules are applied to derive an architectural framework for the EU Horizon 2020 project “Very efficient deep learning in the IoT” (VEDLIoT) in the form of a case study.
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| 28. |
- Heyn, Hans-Martin, 1987, et al.
(författare)
-
An empirical investigation of challenges of specifying training data and runtime monitors for critical software with machine learning and their relation to architectural decisions
- 2024
-
Ingår i: Requirements Engineering. - 0947-3602 .- 1432-010X. ; 29, s. 97-117
-
Tidskriftsartikel (refereegranskat)abstract
- The development and operation of critical software that contains machine learning (ML) models requires diligence and established processes. Especially the training data used during the development of ML models have major influences on the later behaviour of the system. Runtime monitors are used to provide guarantees for that behaviour. Runtime monitors for example check that the data at runtime is compatible with the data used to train the model. In a first step towards identifying challenges when specifying requirements for training data and runtime monitors, we conducted and thematically analysed ten interviews with practitioners who develop ML models for critical applications in the automotive industry. We identified 17 themes describing the challenges and classified them in six challenge groups. In a second step, we found interconnection between the challenge themes through an additional semantic analysis of the interviews. We explored how the identified challenge themes and their interconnections can be mapped to different architecture views. This step involved identifying relevant architecture views such as data, context, hardware, AI model, and functional safety views that can address the identified challenges. The article presents a list of the identified underlying challenges, identified relations between the challenges and a mapping to architecture views. The intention of this work is to highlight once more that requirement specifications and system architecture are interlinked, even for AI-specific specification challenges such as specifying requirements for training data and runtime monitoring.
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| 29. |
- Heyn, Hans-Martin, 1987, et al.
(författare)
-
An Investigation of Challenges Encountered When Specifying Training Data and Runtime Monitors for Safety Critical ML Applications
- 2023
-
Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - : Springer. - 1611-3349 .- 0302-9743. ; 13975 LNCS, s. 206-222
-
Konferensbidrag (refereegranskat)abstract
- [Context and motivation] The development and operation of critical software that contains machine learning (ML) models requires diligence and established processes. Especially the training data used during the development of ML models have major influences on the later behaviour of the system. Runtime monitors are used to provide guarantees for that behaviour. [Question/problem] We see major uncertainty in how to specify training data and runtime monitoring for critical ML models and by this specifying the final functionality of the system. In this interview-based study we investigate the underlying challenges for these difficulties. [Principal ideas/results] Based on ten interviews with practitioners who develop ML models for critical applications in the automotive and telecommunication sector, we identified 17 underlying challenges in 6 challenge groups that relate to the challenge of specifying training data and runtime monitoring. [Contribution] The article provides a list of the identified underlying challenges related to the difficulties practitioners experience when specifying training data and runtime monitoring for ML models. Furthermore, interconnection between the challenges were found and based on these connections recommendation proposed to overcome the root causes for the challenges.
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| 30. |
- Heyn, Hans-Martin, 1987, et al.
(författare)
-
Requirement Engineering Challenges for AI-intense Systems Development
- 2021
-
Ingår i: ICSE '21: Proceedings of the 1st Workshop on AI Engineering – Software Engineering for AI.
-
Konferensbidrag (refereegranskat)abstract
- Availability of powerful computation and communication technology as well as advances in artificial intelligence enable a new generation of complex, AI-intense systems and applications. Such systems and applications promise exciting improvements on a societal level, yet they also bring with them new challenges for their development. In this paper we argue that significant challenges relate to defining and ensuring behaviour and quality attributes of such systems and applications. We specifically derive four challenge areas from relevant use cases of complex, AI-intense systems and applications related to industry, transportation, and home automation: understanding, determining, and specifying (i) contextual definitions and requirements,(ii) data attributes and requirements, (iii) performance definition and monitoring, and (iv) the impact of human factors on system acceptance and success. Solving these challenges will imply process support that integrates new requirements engineering methods into development approaches for complex, AI-intense systems and applications. We present these challenges in detail and propose a research roadmap.
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| 31. |
- Heyn, Hans-Martin, 1987, et al.
(författare)
-
Setting AI in Context: A Case Study on Defining the Context and Operational Design Domain for Automated Driving
- 2022
-
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. ; 13216 LNCS, s. 199-215
-
Konferensbidrag (refereegranskat)abstract
- [Context and motivation] For automated driving systems, the operational context needs to be known in order to state guarantees on performance and safety. The operational design domain (ODD) is an abstraction of the operational context, and its definition is an integral part of the system development process. [Question/problem] There are still major uncertainties in how to clearly define and document the operational context in a diverse and distributed development environment such as the automotive industry. This case study investigates the challenges with context definitions for the development of perception functions that use machine learning for automated driving. [Principal ideas/results] Based on qualitative analysis of data from semi-structured interviews, the case study shows that there is a lack of standardisation for context definitions across the industry, ambiguities in the processes that lead to deriving the ODD, missing documentation of assumptions about the operational context, and a lack of involvement of function developers in the context definition. [Contribution] The results outline challenges experienced by an automotive supplier company when defining the operational context for systems using machine learning. Furthermore, the study collected ideas for potential solutions from the perspective of practitioners.
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| 32. |
- Heyn, Hans-Martin, 1987, et al.
(författare)
-
Structural Causal Models as Boundary Objects in AI System Development
- 2022
-
Ingår i: Proceedings - 1st International Conference on AI Engineering - Software Engineering for AI, CAIN 2022. - New York, NY, USA : ACM.
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Artificial Intelligence (AI), and especially machine learning can be used to find statistical patterns in datasets with thousands of variables with ease. But an understanding of causality is difficult to learn for a machine. For humans however, realising causal relations is often not a difficult process, as we can refer to experience or scientific knowledge. Here we propose the use of structural causal models, represented through direct acyclic graphs, to design, determine, and communicate causal relations hidden beyond the statistical models of an AI. The idea is to make human insight in causal relations explicit and use this knowledge during AI system development. In a joint-industry project we discovered that structural causal models can serve as living boundary objects that facilitate coordination of domain experts, data scientists, systems engineers, and AI experts in AI system development.
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| 33. |
- Holtmann, Jörg, 1979, et al.
(författare)
-
Using boundary objects and methodological island (BOMI) modeling in large-scale agile systems development
- 2024
-
Ingår i: Software and Systems Modeling. - 1619-1374 .- 1619-1366. ; In Press
-
Tidskriftsartikel (refereegranskat)abstract
- Large-scale systems development commonly faces the challenge of managing relevant knowledge between different organizational groups, particularly in increasingly agile contexts. Here, there is a conflict between coordination and group autonomy, and it is challenging to determine what necessary coordination information must be shared by what teams or groups, and what can be left to local team management. We introduce a way to manage this complexity using a modeling framework based on two core concepts: methodological islands (i.e., groups using different development methods than the surrounding organization) and boundary objects (i.e., artifacts that create a common understanding across team borders). However, we found that companies often lack a systematic way of assessing coordination issues and the use of boundary objects between methodological islands. As part of an iterative design science study, we have addressed this gap by producing a modeling framework (BOMI: Boundary Objects and Methodological Islands) to better capture and analyze coordination and knowledge management in practice. This framework includes a metamodel, as well as a list of bad smells over this metamodel that can be leveraged to detect inter-team coordination issues. The framework also includes a methodology to suggest concrete modeling steps and broader guidelines to help apply the approach successfully in practice. We have developed Eclipse-based tool support for the BOMI method, allowing for both graphical and textual model creation, and including an implementation of views over BOMI instance models in order to manage model complexity. We have evaluated these artifacts iteratively together with five large-scale companies developing complex systems. In this work, we describe the BOMI framework and its iterative evaluation in several real cases, reporting on lessons learned and identifying future work. We have produced a matured and stable modeling framework which facilitates understanding and reflection over complex organizational configurations, communication, governance, and coordination of knowledge artifacts in large-scale agile system development.
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| 34. |
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| 35. |
- Horkoff, Jennifer, 1980, et al.
(författare)
-
Experiences applying e 3 value modeling in a cross-company study
- 2018
-
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. ; 11157 LNCS, s. 610-625
-
Konferensbidrag (refereegranskat)abstract
- Driven by business interests, (product/customer) value has become a critical topic in system and software engineering as well as enterprise planning. The conceptual modeling community has responded to this challenge with several modeling approaches, including e3 value modeling, focusing on capturing and analyzing value flows in value networks. This modeling approach has risen from practical e-commerce experiences and has been further studied in an academic context. In this experience paper, we report the advantages and disadvantages of applying e3 value modeling as part of a cross-company case study focusing on understanding the internal and external value of APIs from a strategic perspective. We found that value modeling was generally well-received and understood by the company representatives, but also found drawbacks when used in our context, including challenges in modeling internal value networks, capturing problematic or missing values, finding quantitative value measures, and showing underlying motivations for flows. Our findings can help to improve language aspects, methods and tools, and can help to guide future value analysis in similar contexts.
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| 36. |
- Horkoff, Jennifer, 1980, et al.
(författare)
-
Modeling support for strategic API planning and analysis
- 2018
-
Ingår i: Lecture Notes in Business Information Processing. - Cham : Springer International Publishing. - 1865-1356 .- 1865-1348. ; 336, s. 10-26
-
Konferensbidrag (refereegranskat)abstract
- APIs provide value beyond technical functionality. They enable and manage access to strategic business assets and play a key role in enabling software ecosystems. Existing work has begun to consider the strategic business value of software APIs, but such work has limited analysis capabilities and has not made use of established, structured modeling techniques from software and requirements engineering. Such modeling languages have been used for strategic analysis of ecosystems and value exchange. We believe these techniques expand analysis possibilities for APIs, and we apply them as part of a cross-company case study focused on strategic API planning and analysis. Results show that goal, value, and workflow modeling provide new, API-specific benefits that include mapping the API ecosystem, facilitating incremental API planning, understanding dynamic API-specific roles, identifying bottlenecks in API change workflows, and identifying API value.
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| 37. |
- Kaiser, M., et al.
(författare)
-
VEDLIoT: Very Efficient Deep Learning in IoT
- 2022
-
Ingår i: Proceedings of the 2022 Design, Automation and Test in Europe Conference and Exhibition, DATE 2022. - : IEEE. - 9783981926361
-
Konferensbidrag (refereegranskat)abstract
- The VEDLIoT project targets the development of energy-efficient Deep Learning for distributed AIoT applications. A holistic approach is used to optimize algorithms while also dealing with safety and security challenges. The approach is based on a modular and scalable cognitive IoT hardware platform. Using modular microserver technology enables the user to configure the hardware to satisfy a wide range of applications. VEDLIoT offers a complete design flow for Next-Generation IoT devices required for collaboratively solving complex Deep Learning applications across distributed systems. The methods are tested on various use-cases ranging from Smart Home to Automotive and Industrial IoT appliances. VEDLIoT is an H2020 EU project which started in November 2020. It is currently in an intermediate stage with the first results available.
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| 38. |
- Kasauli, Rashida, 1984, et al.
(författare)
-
Adding value every sprint: A case study on large-scale continuous requirements engineering
- 2017
-
Ingår i: CEUR Workshop Proceedings. - 1613-0073. ; 1796
-
Konferensbidrag (refereegranskat)abstract
- Agile development practices, such as continuous integration and continuous delivery, promise value through shorter time to market and increased exibility. While these practices have been widely adopted in small-scale, they have shown to be challenging to adopt in large-scale, system development. This is often due to a distance between customer and developer in large scale systems, and the need to break down value from the whole system into manageable parts. The notion of value is fundamental for agile methods, especially for practices such as continuous delivery to the customer. However, how value should be handled in development practices is not clearly understood. In this paper, we investigate how the notion of adding value in every sprint has been perceived in a large-scale system development. Based on an exploratory qualitative case study, the outcome shows that it is perceived beneficial by practitioners although it comes at a price and challenges exist.
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| 39. |
|
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| 40. |
- Kasauli, Rashida, 1984, et al.
(författare)
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Charting Coordination Needs in Large-Scale Agile Organisations with Boundary Objects and Methodological Islands
- 2020
-
Ingår i: Proceedings - 2020 IEEE/ACM International Conference on Software and System Processes, ICSSP 2020. - New York, NY, USA : ACM. ; , s. 51-60
-
Konferensbidrag (refereegranskat)abstract
- Large-scale system development companies are increasingly adopting agile methods. While this adoption may improve lead-times, such companies need to balance two trade-offs: (i) the need to have a uniform, consistent development method on system level with the need for specialised methods for teams in different disciplines (e.g., hardware, software, mechanics, sales, support); (ii) the need for comprehensive documentation on system level with the need to have lightweight documentation enabling iterative and agile work. With specialised methods for teams, isolated teams work within larger ecosystems of plan-driven culture, i.e., teams become agile “islands”. At the boundaries, these teams share knowledge which needs to be managed well for a correct system to be developed. While it is useful to support diverse and specialised methods, it is important to understand which islands are repeatedly encountered, the reasons or factors triggering their existence, and how best to handle coordination between them. Based on a multiple case study, this work presents a catalogue of islands and the boundary objects between them. We believe this work will be beneficial to practitioners aiming to understand their ecosystems and researchers addressing communication and coordination challenges in large-scale development.
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| 41. |
- Kasauli, Rashida, 1984, et al.
(författare)
-
Requirements engineering challenges and practices in large-scale agile system development
- 2021
-
Ingår i: Journal of Systems and Software. - : Elsevier BV. - 0164-1212. ; 172
-
Tidskriftsartikel (refereegranskat)abstract
- Context: Agile methods have become mainstream even in large-scale systems engineering companies that need to accommodate different development cycles of hardware and software. For such companies, requirements engineering is an essential activity that involves upfront and detailed analysis which can be at odds with agile development methods. Objective: This paper presents a multiple case study with seven large-scale systems companies, reporting their challenges, together with best practices from industry. We also analyze literature about two popular large-scale agile frameworks, SAFe (R) and LeSS, to derive potential solutions for the challenges. Methods: Our results are based on 20 qualitative interviews, five focus groups, and eight cross company workshops which we used to both collect and validate our results. Results: We found 24 challenges which we grouped in six themes, then mapped to solutions from SAFe (R), LeSS, and our companies, when available. Conclusion: In this way, we contribute a comprehensive overview of RE challenges in relation to largescale agile system development, evaluate the degree to which they have been addressed, and outline research gaps. We expect these results to be useful for practitioners who are responsible for designing processes, methods, or tools for large scale agile development as well as guidance for researchers.
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| 42. |
- Kasauli, Rashida, 1984, et al.
(författare)
-
Requirements engineering challenges and practices in large-scale agile system development
- 2022
-
Ingår i: Accelerating Digital Transformation: 10 Years of Software Center. - 9783031108730 ; , s. 293-350
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- Context: Agile methods have become mainstream even in large-scale systems engineering companies that need to accommodate different development cycles of hardware and software. For such companies, requirements engineering is an essential activity that involves upfront and detailed analysis which can be at odds with agile development methods. Objective: This paper presents a multiple case study with seven large-scale systems companies, reporting their challenges, together with best practices from industry. We also analyse literature about two popular large-scale agile frameworks, SAFe® and LeSS, to derive potential solutions for the challenges. Method: Our results are based on 20 qualitative interviews, five focus groups, and eight cross-company workshops which we used to both collect and validate our results. Results: We found 24 challenges which we grouped in six themes, then mapped to solutions from SAFe®, LeSS, and our companies, when available. Conclusion: In this way, we contribute a comprehensive overview of RE challenges in relation to large-scale agile system development, evaluate the degree to which they have been addressed, and outline research gaps. We expect these results to be useful for practitioners who are responsible for designing processes, methods, or tools for large scale agile development as well as guidance for researchers.
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| 43. |
- Kasauli, Rashidah, et al.
(författare)
-
Safety-Critical Systems and Agile Development: A Mapping Study
- 2018
-
Ingår i: 44TH EUROMICRO CONFERENCE ON SOFTWARE ENGINEERING AND ADVANCED APPLICATIONS (SEAA 2018). - 1089-6503. - 9781538673836
-
Konferensbidrag (refereegranskat)abstract
- Several studies report that the use of model-centric methods in the automotive domain is widespread and offers several benefits. However, existing work indicates that few modelling frameworks explicitly include requirements engineering (RE), and that natural language descriptions are still the status quo in RE. Therefore, we aim to increase the understanding of current and potential future use of models in RE, with respect to the automotive domain. In this paper, we report our findings from a multiple-case study with two automotive companies, collecting interview data from 14 practitioners. Our results show that models are used for a variety of different purposes during RE in the automotive domain, e.g., to improve communication and to handle complexity. However, these models are often used in an unsystematic fashion and restricted to few experts. A more widespread use of models is prevented by various challenges, most of which align with existing work on model use in a general sense. Furthermore, our results indicate that there are many potential benefits associated with future use of models during RE. Interestingly, existing research does not align well with several of the proposed use cases, e.g., restricting the use of models to informal notations for communication purposes. Based on our findings, we recommend a stronger focus on informal modelling and on using models for multi-disciplinary environments. Additionally, we see the need for future work in the area of model use, i.e., information extraction from models by non-expert modellers.
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| 44. |
- Katumba, Brian, et al.
(författare)
-
Agile Development in Automotive Software Development: Challenges and Opportunities
- 2014
-
Ingår i: Product-Focused Software Process Improvement, Lecture Notes in Computer Science. - Cham : Springer. - 9783319138343
-
Konferensbidrag (refereegranskat)abstract
- In modern cars, most of the functionalities are controlled by software. The increased significance of software-based functionality has resulted in various challenges for automotive industry, which is slowly transitioning towards being a software centric industry. Challenges include the definition of key competencies, processes, methods, tools, and organization settings to accommodate combined development of software and hardware. Based on qualitative research, this paper aims at understanding the applicability of agile methods to automotive software development. Our explorative case study with one of the development sections at Volvo Car Cooperation identified challenges in their software development process related to process perception and reactive mode, multi-tasking and frequent task switching, individualism and lack of complete knowledge, as well as long communication chains and low cross-function mind set. Moreover it prepares a transition of software development at this multinational automotive company towards agile by relating agile principles and practices to automotive software process challenges.
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| 45. |
- Knauss, Eric, 1977
(författare)
-
Constructive Master's Thesis Work in Industry: Guidelines for Applying Design Science Research
- 2021
-
Ingår i: Proc. of 43rd Int. Conf. on Software Eng. (ICSE), Joint Software Engineering Education and Training (JSEET) track.
-
Konferensbidrag (refereegranskat)abstract
- [Context:] Software engineering at large is an ap- plied field of work, study, and research. Consequently, software engineering researchers and practitioners rely on empirical evidence from the field. Thus, education of software engineers must include strong and applied education in empirical research methods. For most students, the master’s thesis is the last, but also most applied form of this education in their studies. [Problem:] Most theses in our context are done in collaboration with industry and require that concerns of stakeholders from academia and practice are carefully balanced. It is possible, yet difficult to do high-impact empirical work within the timeframe of a typical thesis. In particular, if this research aims to provide practical value to industry, academic quality can suffer. Even though constructive research methods such as Design Science Research exist, thesis projects repeatably struggle to apply them. [Principle solution idea:] Design science research has proven to enable balancing such concerns by providing room both for knowledge questions and design work. Yet, only limited experience exists in our field on how to make this research method work within the context of a master’s thesis. To enable running design science master’s theses in collaboration with industry, we complement existing method descriptions and guidelines with our own experience and pragmatic advice to students, examiners, and supervisors in academia and industry. [Method:] This paper itself is based on design science research. Based on 12 design science theses over the last seven years, we collect common pitfalls and good practice from analysing the theses, the student-supervisor interaction, the supervisor-industry interaction, the examiner feedback, and, where available, re- viewer comments on publications that are based on such theses. [Results:] We provide concrete advise for framing research questions, structuring a report, as well as for planning and conducting empirical work with practitioners.
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| 46. |
- Knauss, Eric, 1977, et al.
(författare)
-
Continuous Integration Beyond the Team: A Tooling Perspective on Challenges in the Automotive Industry
- 2016
-
Ingår i: Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM '16). - New York, NY, USA : ACM. - 1949-3770 .- 1949-3789. - 9781450344272
-
Konferensbidrag (refereegranskat)abstract
- The practice of Continuous Integration (CI) has a big impact on how software is developed today. Shortening integration and feedback cycles promises to increase software quality, feature throughput, and customer satisfaction. Thus, it is not a surprise that companies try to embrace CI in domains where it is rather difficult to implement. In this paper we present our findings from two rounds of interviews with a car manufacturer on the use of tools in system engineering and how these tools would support wider adoption of CI. Our findings suggest a complex tool landscape with immense requirements that are not easily fulfilled by existing tools; this holds also for tools that well support CI in other domains. From this notion, we fur- ther explore what makes the automotive domain challeng- ing when it comes to CI (namely complexity of system and value chain). We hope that our findings will help address such challenges.
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| 47. |
- Knauss, Eric, 1977, et al.
(författare)
-
EAM: Ecosystemability Assessment Method
- 2014
-
Ingår i: 2014 IEEE 22nd International Requirements Engineering Conference (RE), Aug 25-29, Karlskrona, Sverige. - : IEEE. - 1097-0592. - 9781479930333
-
Konferensbidrag (refereegranskat)abstract
- In this extended abstract, we present the ecosystemability assessment method as a means to assess the extent to which a software system, represented by its architecture and its development environment, supports the vision of ecosystem.
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| 48. |
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| 49. |
- Knauss, Eric, 1977, et al.
(författare)
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Patterns of Continuous Requirements Clarification
- 2014
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Ingår i: Requirements Engineering. - : Springer Science and Business Media LLC. - 0947-3602 .- 1432-010X. ; 20:4, s. 383-403
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Tidskriftsartikel (refereegranskat)abstract
- In software projects involving large and of- ten distributed teams, requirements evolve through the collaboration of many stakeholders, supported by online tools such as mailing lists, bug tracking systems, or online discussion forums. In this collaboration, requirements typically evolve from initial ideas, through clarification, to the implementation of a stable requirement. Deviations from this expected course might in- dicate requirements that are poorly understood, need further negotiation, or better alignment with project goals. If not addressed timely, such problems can surface late in the development cycle with negative consequences such as rework, missed schedules, or overrun budget. This paper presents an approach that provides project managers’ with timely awareness of such requirements-related risks, based on automatic analysis of stakeholders’ online requirements communication. We describe a clarification classifier that automatically analyzes requirements communication in a project and detects clarification events, a catalogue of clarification patterns, and a pattern matcher that suggests communication patterns based on our pattern catalogue. Our approach has been empirically constructed and evaluated in a case study in the IBM Rational Team Concert (RTC) project. We discuss the applicability of our approach in other projects as well as avenues for extending our pattern catalogue towards a theory of clarification patterns.
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- Knauss, Eric, 1977, et al.
(författare)
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Quality Requirements in Agile as a Knowledge Management Problem: More than Just-in-Time
- 2017
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Ingår i: 2nd International Workshop on Just-In-Time Requirements Engineering: Dealing with Non-Functional Requirements in Agile Software Development (JITRE@RE17). - : IEEE. - 9781538634882
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Konferensbidrag (refereegranskat)abstract
- Just-in-time (JIT) approaches have been suggested for managing non-functional requirements in agile projects. However, many non-functional requirements cannot be raised and met on the spot. In this position paper, we argue that effective JIT engineering of quality requirements depends on a solid foundation of long-term knowledge about all relevant quality requirements. We present two examples from projects related to safety and security and show that not all aspects of these quality requirements can be invented and changed just in time. Further, managing for example operationalization of quality requirements just in time depends on sufficient understanding of (i) customer value and (ii) the system under construction that must be shared by the engineering team. If a Learning Software Organization (LSO) intends to increase agility and speed up system development, it needs a holistic concept for managing this knowledge. We propose that a knowledge-management framework can facilitate JIT-RE by structuring, representing, and allowing updates of long-term knowledge about quality requirements. Such a knowledge-management framework should allow to map user value to system requirements and have important properties to allow JIT RE and sustainable evolution.
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