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  • 1.
    Abella, J.
    et al.
    Barcelona Supercomputing Center, Spain.
    Perez, J.
    BRTA Basque Research and Technology Alliance, Spain.
    Englund, Cristofer
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Zonooz, B.
    Navinfo Europe, Netherlands.
    Giordana, G.
    AIKO Srl, Italy.
    Donzella, C.
    Exida Development Srl, Italy.
    Cazorla, F. J.
    Barcelona Supercomputing Center, Spain.
    Mezzetti, E.
    Barcelona Supercomputing Center, Spain.
    Serra, I.
    Barcelona Supercomputing Center, Spain.
    Brando, A.
    Barcelona Supercomputing Center, Spain.
    Agirre, I.
    BRTA Basque Research and Technology Alliance, Spain.
    Eizaguirre, F.
    BRTA Basque Research and Technology Alliance, Spain.
    Bui, Thanh
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Arani, E.
    Navinfo Europe, Netherlands.
    Sarfraz, F.
    Navinfo Europe, Netherlands.
    Balasubramaniam, A.
    Navinfo Europe, Netherlands.
    Badar, A.
    Navinfo Europe, Netherlands.
    Bloise, I.
    AIKO Srl, Italy.
    Feruglio, L.
    AIKO Srl, Italy.
    Cinelli, I.
    AIKO Srl, Italy.
    Brighenti, D.
    Exida Engineering Srl, Italy.
    Cunial, D.
    Exida Engineering Srl, Italy.
    SAFEXPLAIN: Safe and Explainable Critical Embedded Systems Based on AI2023Inngår i: Proceedings -Design, Automation and Test in Europe, DATE, Institute of Electrical and Electronics Engineers Inc. , 2023Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Deep Learning (DL) techniques are at the heart of most future advanced software functions in Critical Autonomous AI-based Systems (CAIS), where they also represent a major competitive factor. Hence, the economic success of CAIS industries (e.g., automotive, space, railway) depends on their ability to design, implement, qualify, and certify DL-based software products under bounded effort/cost. However, there is a fundamental gap between Functional Safety (FUSA) requirements on CAIS and the nature of DL solutions. This gap stems from the development process of DL libraries and affects high-level safety concepts such as (1) explainability and traceability, (2) suitability for varying safety requirements, (3) FUSA-compliant implementations, and (4) real-time constraints. As a matter of fact, the data-dependent and stochastic nature of DL algorithms clashes with current FUSA practice, which instead builds on deterministic, verifiable, and pass/fail test-based software. The SAFEXPLAIN project tackles these challenges and targets by providing a flexible approach to allow the certification - hence adoption - of DL-based solutions in CAIS building on: (1) DL solutions that provide end-to-end traceability, with specific approaches to explain whether predictions can be trusted and strategies to reach (and prove) correct operation, in accordance to certification standards; (2) alternative and increasingly sophisticated design safety patterns for DL with varying criticality and fault tolerance requirements; (3) DL library implementations that adhere to safety requirements; and (4) computing platform configurations, to regain determinism, and probabilistic timing analyses, to handle the remaining non-determinism.

  • 2. Alégroth, Emil
    et al.
    Burden, Håkan
    Ericsson, Morgan
    Hammouda, Imed
    Knauss, Eric
    Steghöfer, Jan-Philipp
    Teaching Scrum - What We Did, What We Will Do and What Impedes Us2015Konferansepaper (Annet vitenskapelig)
    Fulltekst (pdf)
    fulltext
  • 3. Berntsson Svensson, Richard
    et al.
    Olsson, Thomas
    Regnell, Björn
    An investigation of how quality requirements are specified in industrial practice2013Inngår i: Information and Software Technology, Vol. 55, nr 7, s. 1224-1236Artikkel i tidsskrift (Fagfellevurdert)
  • 4.
    Besker, Terese
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Martini, Antonio
    University of Oslo, Norway.
    Bosch, Jan
    Chalmers University of Technology, Sweden.
    The use of incentives to promote technical debt management2022Inngår i: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 142, artikkel-id 106740Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Context When developing software, it is vitally important to keep the level of technical debt down since, based on several studies, it has been well established that technical debt can lower the development productivity, decrease the developers' morale and compromise the overall quality of the software, among others. However, even if researchers and practitioners working in today's software development industry are quite familiar with the concept of technical debt and its related negative consequences, there has been no empirical research focusing specifically on how software managers actively communicate and manage the need to keep the level of technical debt as low as possible. Objective This study aims to understand how software companies give incentives to manage technical debt. This is carried out by exploring how companies encourage and reward practitioners for actively keeping the level of technical debt down add whether the companies use any forcing or penalising initiatives when managing technical debt. Method As a first step, this paper reports the results of both an online survey providing quantitative data from 258 participants and interviews with 32 software practitioners. As a second step, this study sets out to specifically provide a detailed assessment of additional and in-depth analysis of technical debt management strategies based on an encouraging mindset and attitude from both managers and technical roles to understand how, when and by whom such strategies are adopted in practice. Results Our findings show that having a technical debt management strategy (specially based on encouragement) can significantly impact the amount of technical debt related to the software. Conclusion The result indicates that there is considerable unfulfilled potential to influence how software practitioners can further limit and reduce technical debt by adopting a strategy based explicitly on an encouraging mindset from managers where they also specifically dedicate time and resources for technical debt remediation activities.

  • 5.
    Borg, Markus
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Using Search-Based Software Testing to Guide the Strive for Robust Machine Learning Components: Lessons Learned Across Systems and Simulators in the Mobility Domain2022Inngår i: Proceedings - 2022 IEEE 14th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2022, Institute of Electrical and Electronics Engineers Inc. , 2022Konferansepaper (Fagfellevurdert)
  • 6.
    Borg, Markus
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Abdessalem, Raja
    University of Luxembourg, Luxembourg.
    Nejati, Shiva
    University of Luxembourg, Luxembourg; University of Ottawa, Canada.
    Jegeden, Francois
    ESI Group, France.
    Shin, Donghwan
    University of Luxembourg, Luxembourg.
    Digital Twins Are Not Monozygotic – Cross-Replicating ADAS Testing in Two Industry-Grade Automotive Simulators2021Inngår i: 2021 14th IEEE Conference on Software Testing, Verification and Validation (ICST), 2021, s. 383-393Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The increasing levels of software- and data-intensive driving automation call for an evolution of automotive soft-ware testing. As a recommended practice of the Verification and Validation (V&V) process of ISO/PAS 21448, a candidate standard for safety of the intended functionality for road vehicles, simulation-based testing has the potential to reduce both risks and costs. There is a growing body of research on devising test automation techniques using simulators for Advanced Driver-Assistance Systems (ADAS). However, how similar are the results if the same test scenarios are executed in different simulators? We conduct a replication study of applying a Search-Based Software Testing (SBST) solution to a real-world ADAS (PeVi, a pedestrian vision detection system) using two different commercial simulators, namely, TASS/Siemens PreScan and ESI Pro-SiVIC. Based on a minimalistic scene, we compare critical test scenarios generated using our SBST solution in these two simulators. We show that SBST can be used to effectively generate critical test scenarios in both simulators, and the test results obtained from the two simulators can reveal several weaknesses of the ADAS under test. However, executing the same test scenarios in the two simulators leads to notable differences in the details of the test outputs, in particular, related to (1) safety violations revealed by tests, and (2) dynamics of cars and pedestrians. Based on our findings, we recommend future V&V plans to include multiple simulators to support robust simulation-based testing and to base test objectives on measures that are less dependant on the internals of the simulators.

  • 7.
    Borg, Markus
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Bengtsson, J.
    Lund University, Sweden.
    Osterling, H.
    Lund University, Sweden.
    Hagelborn, A.
    NordAxon AB, Sweden.
    Gagner, Isabella
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Tomaszewski, Piotr
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice2022Inngår i: Proceedings - 1st International Conference on AI Engineering - Software Engineering for AI, CAIN 2022, Institute of Electrical and Electronics Engineers Inc. , 2022, s. 22-32Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Due to the migration megatrend, efficient and effective second-language acquisition is vital. One proposed solution involves AI-enabled conversational agents for person-centered interactive language practice. We present results from ongoing action research targeting quality assurance of proprietary generative dialog models trained for virtual job interviews. The action team elicited a set of 38 requirements for which we designed corresponding automated test cases for 15 of particular interest to the evolving solution. Our results show that six of the test case designs can detect meaningful differences between candidate models. While quality assurance of natural language processing applications is complex, we provide initial steps toward an automated framework for machine learning model selection in the context of an evolving conversational agent. Future work will focus on model selection in an MLOps setting.

  • 8.
    Borg, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Chatzipetrou, Panagiota
    Blekinge Institute of Technology, Sweden; Örebro University, Sweden.
    Wnuk, Krzysztof
    Blekinge Institute of Technology, Sweden.
    Alégroth, Emil
    Blekinge Institute of Technology, Sweden.
    Gorschek, Tony
    Blekinge Institute of Technology, Sweden.
    Papatheocharous, Efi
    RISE - Research Institutes of Sweden, ICT, SICS.
    Shah, Syed
    iZettle, Sweden.
    Axelsson, Jakob
    RISE - Research Institutes of Sweden, ICT, SICS.
    Selecting Software Component Sourcing Options: Detailed Survey Description and Analysis2018Rapport (Annet vitenskapelig)
    Abstract [en]

    Component-based software engineering (CBSE) is a common approach to develop and evolve contemporary software systems. When evolving a system based on components, make-or-buy decisions are frequent, i.e., whether to develop components internally or to acquire them fromexternal sources. In CBSE, several different sourcing options are available: 1) developing software in-house, 2) outsourcing development, 3) buying commercial-off-the-shelf software, and 4) integrating open source software components. Unfortunately, there is little available research on howorganizations select component sourcing options (CSO) in industry practice. In this work, we seek to contribute empirical evidence to CSO selection. Method: We conduct a cross-domain survey on CSO selection in industry, implemented as an online questionnaire. Based on 188 responses, we find that most organizations consider multiple CSOs during software evolution, and that the CSO decisions in industry are dominated by expert judgment. When choosing between candidate components, functional suitability acts as an initial filter, then reliability is the most important quality. We stress that future solution-oriented work on decision support has to account for the dominance of expert judgment in industry. Moreover, we identify considerable variation in CSO decision processes in industry. Finally, we encourage software development organizations to reflect on their decision processes when choosing whether to make or buy components, and we recommend using our survey for a first benchmarking.

    Fulltekst (pdf)
    fulltext
  • 9.
    Borg, Markus
    et al.
    RISE Research Institutes of Sweden. Lund University, Sweden.
    Henriksson, Jens
    Semcon AB, Sweden.
    Socha, Kasper
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system. Lund University, Sweden.
    Lennartsson, Olof
    Infotiv AB, Sweden.
    Sonnsjö Lönegren, Elias
    Infotiv AB, Sweden.
    Bui, Thanh
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Tomaszewski, Piotr
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Sathyamoorthy, S R
    QRTECH AB, Sweden.
    Brink, Sebastian
    Combitech AB, Sweden.
    Helali Moghadam, Mahshid
    RISE Research Institutes of Sweden.
    Ergo, SMIRK is safe: a safety case for a machine learning component in a pedestrian automatic emergency brake system2023Inngår i: Software quality journal, ISSN 0963-9314, E-ISSN 1573-1367, Vol. 31, nr 2, s. 335-Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Integration of machine learning (ML) components in critical applications introduces novel challenges for software certification and verification. New safety standards and technical guidelines are under development to support the safety of ML-based systems, e.g., ISO 21448 SOTIF for the automotive domain and the Assurance of Machine Learning for use in Autonomous Systems (AMLAS) framework. SOTIF and AMLAS provide high-level guidance but the details must be chiseled out for each specific case. We initiated a research project with the goal to demonstrate a complete safety case for an ML component in an open automotive system. This paper reports results from an industry-academia collaboration on safety assurance of SMIRK, an ML-based pedestrian automatic emergency braking demonstrator running in an industry-grade simulator. We demonstrate an application of AMLAS on SMIRK for a minimalistic operational design domain, i.e., we share a complete safety case for its integrated ML-based component. Finally, we report lessons learned and provide both SMIRK and the safety case under an open-source license for the research community to reuse. © 2023, The Author(s).

  • 10.
    Borg, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Olsson, Thomas
    RISE - Research Institutes of Sweden, ICT, SICS.
    Franke, Ulrik
    RISE - Research Institutes of Sweden, ICT, SICS.
    Assar, Saïd
    IMT Business School, Sweden.
    Digitalization of Swedish Government Agencies: Detailed Census Description and Analysis2018Rapport (Annet vitenskapelig)
    Abstract [en]

    Software engineering is at the core of the digitalization of society. Ill-informed decisions can have major consequences, as made evident in the 2017 government crisis in Sweden, originating in a data breach caused by an outsourcing deal made by the Swedish Transport Agency. Many Government Agencies (GovAgs) in Sweden are rapidly undergoing a digital transition, thus it is important to overview how widespread, and mature, software development is in this part of the public sector. We present a software development census of Swedish GovAgs, complemented by document analysis and a survey. We show that 39.2% of the GovAgs develop software internally, some matching the number of developers in large companies. Our findings suggest that the development largely resembles private sector counterparts, and that established best practices are implemented. Still, we identify improvement potential in the areas of strategic sourcing, openness, collaboration across GovAgs, and quality requirements. The Swedish Government has announced the establishment of a new digitalization agency next year, and our hope is that the software engineering community will contribute its expertise with a clear voice.

    Fulltekst (pdf)
    fulltext
  • 11. Burden, Håkan
    Hållbar Utveckling som Projekt i Mjukvaruutveckling2016Konferansepaper (Fagfellevurdert)
    Fulltekst (pdf)
    fulltext
  • 12.
    Burden, Håkan
    et al.
    RISE - Research Institutes of Sweden, ICT, Viktoria. Chalmers University of Technology, Sweden.
    Steghöfer, Jan-Philipp
    Chalmers University of Technology, Sweden.
    Teaching and Fostering Reflection in Software Engineering Project Courses2019Inngår i: Agile and Lean Concepts for Teaching and Learning: Bringing Methodologies from Industry to the Classroom / [ed] Parsons, David; MacCallum, Kathryn, Springer Singapore , 2019, s. 231-262Kapittel i bok, del av antologi (Annet vitenskapelig)
    Abstract [en]

    Re ection is an important part of agile software processes as witnessed, e.g., by the Sprint Retrospectives in Scrum or by the various learning feedback loops in XP. Engineering education also emphasises the importance of re ective practice, e.g., in Kolb's learning cycle and Schon's re ection-in/on-action. Our contribution in this chapter is a toolkit for re ective practice that shows how re ection can be used by software engineering students for two purposes: to re ect on the application of a software process and to re ect on their learning process. In order to help students understand the purpose of re ection and how to approach re ection, we follow a cognitive apprenticeship approach in which the teachers re ect about the events in the course, their own goals, and how they are aligned with the teaching. Students are asked to re-

    ect during supervisions and as part of their written assignments from the very beginning of the course. We thus combine a meta-cognitive approach where re ection is taught as a learning strategy with a common software engineering practice of continuous improvement through re ection. We evaluate the re ective model and a course design based on it through the student, teacher, and theoretical lenses based on empirical data.

  • 13.
    Burden, Håkan
    et al.
    RISE - Research Institutes of Sweden, ICT, Viktoria. Chalmers University of Technology, Sweden.
    Steghöfer, Jan-Philipp
    Chalmers University of Technology, Sweden.
    Hagvall Svensson, Oskar
    Chalmers University of Technology, Sweden.
    Facilitating Entrepreneurial Experiences through a Software Engineering Project Course2019Inngår i: 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering Education andTraining (ICSE-SEET), IEEE , 2019, s. 28-37Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Skills and competencies in entrepreneurship, suchas the ability to generate innovative ideas and the courage toengage with stakeholders and society, have gained importance inengineering curricula. In this case study paper, we report on howwe have integrated entrepreneurial experiences into a softwareengineering project course and made the creation of value andreflection on the application of a structured process the heart andsoul of the course. Based on current research on entrepreneurshipeducation as well as the definition of entrepreneurial competenciesused by the European Union, we show how the learningobjectives, the teaching moments, the integration of externalstakeholders, and the assessment work together to create anentrepreneurial environment in which students are encouragedand rewarded to work in an entrepreneurial way. Based on datafrom reflection reports, course evaluations, and interviews wediscuss the pros and cons of our approach and how the studentperception and expectations often run counter to the motivationsof the course design. We thus contribute guidance for otherteachers based on our own experiences in relation to the findingsof our peers.

    Fulltekst (pdf)
    fulltext
  • 14.
    Burden, Håkan
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Stenberg, Susanne
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Sustainable AI and Disruptive Policy – AI Regulatory Sandboxes2023Rapport (Annet vitenskapelig)
    Abstract [en]

    The rapid pace of digitalization and the new opportunities for value creation has raised a concern that regulation is lagging behind and becoming an obstacle. A number of tools have been proposed in order to facilitate innovation that is aligned with existing or upcoming policies.

    A specific case of both facilitating and regulating innovation is the EU’s proposed regulation of AI systems. The act not only poses legal requirements on providers and users of AI systems but also includes measures for facilitating innovation – the concept of regulatory sandboxes is defined with specific purposes together with legal exempts.

    At the time of releasing our paper, the trilogue has reached a political agreement. This means the proposed AI Act will be, even though we do not yet have the final wording. By mapping the negotiation mandates of the European Commission, the European Parliament and the Council of the European Union against Swedish experiences of facilitating innovation and regulatory compliance in relation to AI, we still suggest launching pilots for regulatory sandboxes without delay.

    Based on our own experiences from conducting policy labs and those reported on by others from their regulatory trials, we conclude that it takes time to grow confidence in defining a research agenda with other stakeholders and then strike the balance between facilitation and surveillance of innovation. Something that will require institutional learning and capacity building.

    The mandate to foster and facilitate regulatory compliance as well as innovation, given to the public sector through the AI Act’s regulatory sandboxes, is disruptive. It changes the role and responsibilities for some national authorities, requiring the acquisition of new competences and resources, as well as for the private sector. When they team up with a competent authority the mandate to act becomes larger, as does the responsibility with regards to which kinds of innovation to drive.

    Conducting trials in the current window of opportunity, between now and when the AI Act is in force, will create experiences that policy makers and stakeholders can draw on when creating the detailed guidelines for organising regulatory sandboxes. Adopting an incremental and iterative process enables a transition from learning the basics of selecting a case and finding relevant partners to detailing how to process data and sharing responsibilities and rewards.

    Fulltekst (pdf)
    RegulatorySandboxes-RISE
  • 15. Chen, Lei
    et al.
    Englund, Cristofer
    RISE., Swedish ICT, Viktoria.
    CHOREM: Choreographing services for emergency managemen2016Inngår i: ITS World Congress 2016, 2016Konferansepaper (Fagfellevurdert)
  • 16. Doerr, Joerg
    et al.
    Kerkow, Daniel
    Koenig, Tom
    Olsson, Thomas
    Suzuki, Takeshi
    Non-functional requirements in industry - Three case studies adopting an experience-based NFR method2005Konferansepaper (Fagfellevurdert)
  • 17.
    Ferrari, Fabiano C.
    et al.
    Federal University of São Carlos, Brazil.
    Durelli, Vinicius H. S.
    Federal University of São João del-Rei, Brazil.
    Andler, Sten F.
    University of Skövde, Sweden.
    Offutt, Jeff
    University at Albany, USA.
    Saadatmand, Mehrdad
    RISE Research Institutes of Sweden, Digitala system, Industriella system.
    Müllner, Nils
    DLR German Aerospace Center, Germany.
    On transforming model‐based tests into code: A systematic literature review2023Inngår i: Software testing, verification & reliability, ISSN 0960-0833, E-ISSN 1099-1689, Vol. 33, nr 8, artikkel-id e1860Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    Model-based test design is increasingly being applied in practice and studied in research. Model-based testing (MBT) exploits abstract models of the software behaviour to generate abstract tests, which are then transformed into concrete tests ready to run on the code. Given that abstract tests are designed to cover models but are run on code (after transformation), the effectiveness of MBT is dependent on whether model coverage also ensures coverage of key functional code. In this article, we investigate how MBT approaches generate tests from model specifications and how the coverage of tests designed strictly based on the model translates to code coverage. We used snowballing to conduct a systematic literature review. We started with three primary studies, which we refer to as the initial seeds. At the end of our search iterations, we analysed 30 studies that helped answer our research questions. More specifically, this article characterizes how test sets generated at the model level are mapped and applied to the source code level, discusses how tests are generated from the model specifications, analyses how the test coverage of models relates to the test coverage of the code when the same test set is executed and identifies the technologies and software development tasks that are on focus in the selected studies. Finally, we identify common characteristics and limitations that impact the research and practice of MBT: (i) some studies did not fully describe how tools transform abstract tests into concrete tests, (ii) some studies overlooked the computational cost of model-based approaches and (iii) some studies found evidence that bears out a robust correlation between decision coverage at the model level and branch coverage at the code level. We also noted that most primary studies omitted essential details about the experiments.

  • 18.
    Helali Moghadam, Mahshid
    et al.
    Mälardalen University, Sweden.
    Borg, Markus
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Mousavirad, Seyed
    Hakim Sabzevari University, Iran.
    Deeper at the SBST 2021 Tool Competition: ADAS Testing Using Multi-Objective Search2021Inngår i: Proceedings - 2021 IEEE/ACM 14th International Workshop on Search-Based Software Testing, SBST 2021, Institute of Electrical and Electronics Engineers Inc. , 2021, s. 40-41Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Deeper is a simulation-based test generator that uses an evolutionary process, i.e., an archive-based NSGA-II augmented with a quality population seed, for generating test cases to test a deep neural network-based lane-keeping system. This paper presents Deeper briefly and summarizes the results of Deeper's participation in the Cyber-physical systems (CPS) testing competition at SBST 2021. 

  • 19.
    Helali Moghadam, Mahshid
    et al.
    RISE Research Institutes of Sweden. Mälardalen University, Sweden.
    Borg, Markus
    RISE Research Institutes of Sweden.
    Saadatmand, Mehrdad
    RISE Research Institutes of Sweden.
    Mousavirad, Seyed
    Universidade da Beira Interior, Portugal.
    Bohlin, Markus
    RISE Research Institutes of Sweden. Mälardalen University, Sweden.
    Lisper, Björn
    Mälardalen University, Sweden.
    Machine learning testing in an ADAS case study using simulation-integrated bio-inspired search-based testing2024Inngår i: Journal of Software: Evolution and Process, ISSN 2047-7473, E-ISSN 2047-7481, nr 5, artikkel-id e2591Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This paper presents an extended version of Deeper, a search-based simulation-integrated test solution that generates failure-revealing test scenarios for testing a deep neural network-based lane-keeping system. In the newly proposed version, we utilize a new set of bio-inspired search algorithms, genetic algorithm (GA), (Formula presented.) and (Formula presented.) evolution strategies (ES), and particle swarm optimization (PSO), that leverage a quality population seed and domain-specific crossover and mutation operations tailored for the presentation model used for modeling the test scenarios. In order to demonstrate the capabilities of the new test generators within Deeper, we carry out an empirical evaluation and comparison with regard to the results of five participating tools in the cyber-physical systems testing competition at SBST 2021. Our evaluation shows the newly proposed test generators in Deeper not only represent a considerable improvement on the previous version but also prove to be effective and efficient in provoking a considerable number of diverse failure-revealing test scenarios for testing an ML-driven lane-keeping system. They can trigger several failures while promoting test scenario diversity, under a limited test time budget, high target failure severity, and strict speed limit constraints. 

    Fulltekst (pdf)
    fulltext
  • 20.
    Helali Moghadam, Mahshid
    et al.
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Saadatmand, Mehrdad
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Borg, Markus
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Bohlin, Markus
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Lisper, Björn
    Mälardalen University, Sweden.
    Adaptive Runtime Response Time Control in PLC-based Real-Time Systems using Reinforcement Learning2018Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Timing requirements such as constraints on response time are key characteristics of real-time systems and violations of these requirements might cause a total failure, particularly in hard real-time systems. Runtime monitoring of the system properties is of great importance to check the system status and mitigate such failures. Thus, a runtime control to preserve the system properties could improve the robustness of the system with respect to timing violations. Common control approaches may require a precise analytical model of the system which is difficult to be provided at design time. Reinforcement learning is a promising technique to provide adaptive model-free control when the environment is stochastic, and the control problem could be formulated as a Markov Decision Process. In this paper, we propose an adaptive runtime control using reinforcement learning for real-time programs based on Programmable Logic Controllers (PLCs), to meet the response time requirements. We demonstrate through multiple experiments that our approach could control the response time efficiently to satisfy the timing requirements.

  • 21.
    Helali Moghadam, Mahshid
    et al.
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Saadatmand, Mehrdad
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Borg, Markus
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Bohlin, Markus
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Lisper, Björn
    Mälardalen University, Sweden.
    Learning-based Response Time Analysis in Real-Time Embedded Systems: A Simulation-based Approach2018Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Response time analysis is an essential task to verify the behavior of real-time systems. Several response time analysis methods have been proposed to address this challenge, particularly for real-time systems with different levels of complexity. Static analysis is a popular approach in this context, but its practical applicability is limited due to the high complexity of the industrial real-time systems, as well as many unpredictable run-time events in these systems. In this work-in-progress paper, we propose a simulation-based response time analysis approach using reinforcement learning to find the execution scenarios leading to the worst-case response time. The approach learns how to provide a practical estimation of the worst-case response time through simulating the program without performing static analysis. Our initial study suggests that the proposed approach could be applicable in the simulation environments of the industrial real-time control systems to provide a practical estimation of the execution scenarios leading to the worst-case response time.

  • 22.
    Helali Moghadam, Mahshid
    et al.
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Saadatmand, Mehrdad
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Borg, Markus
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Bohlin, Markus
    RISE - Research Institutes of Sweden (2017-2019), ICT, SICS.
    Lisper, Björn
    Mälardalen University, Sweden.
    Learning-Based Self-Adaptive Assurance of Timing Properties in a Real-Time Embedded System2018Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Providing an adaptive runtime assurance technique to meet the performance requirements of a real-time system without the need for a precise model could be a challenge. Adaptive performance assurance based on monitoring the status of timing properties can bring more robustness to the underlying platform. At the same time, the results or the achieved policy of this adaptive procedure could be used as feedback to update the initial model, and consequently for producing proper test cases. Reinforcement-learning has been considered as a promising adaptive technique for assuring the satisfaction of the performance properties of software-intensive systems in recent years. In this work-in-progress paper, we propose an adaptive runtime timing assurance procedure based on reinforcement learning to satisfy the performance requirements in terms of response time. The timing control problem is formulated as a Markov Decision Process and the details of applying the proposed learning-based timing assurance technique are described.

  • 23.
    Henriksson, Jens
    et al.
    Semcon, Sweden.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Englund, Cristofer
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Automotive Safety and Machine Learning: Initial Results from a Study on How to Adapt the ISO 26262 Safety Standard2018Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Machine learning (ML) applications generate a continuous stream of success stories from various domains. ML enables many novel applications, also in safety-critical contexts. However, the functional safety standards such as ISO 26262 did not evolve to cover ML. We conduct an exploratory study on which parts of ISO 26262 represent the most critical gaps between safety engineering and ML development. While this paper only reports the first steps toward a larger research endeavor, we report three adaptations that are critically needed to allow ISO 26262 compliant engineering, and related suggestions on how to evolve the standard.

  • 24.
    Heyn, Hans Martin
    et al.
    University of Gothenburg, Sweden.
    Habibullah, Khan M
    University of Gothenburg, Sweden.
    Knauss, Eric
    University of Gothenburg, Sweden.
    Horkoff, Jennifer
    University of Gothenburg, Sweden.
    Borg, Markus
    RISE Research Institutes of Sweden.
    Knauss, Alessia
    Zenseact AB, Sweden.
    Li, Polly J
    Kognic AB, Sweden.
    Automotive Perception Software Development: An Empirical Investigation into Data, Annotation, and Ecosystem Challenges2023Inngår i: Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023, Institute of Electrical and Electronics Engineers Inc. , 2023, s. 13-24Konferansepaper (Fagfellevurdert)
    Abstract [en]

    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. 

    Fulltekst (pdf)
    fulltext
  • 25.
    Jagstedt, Siri
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Hedvall, Klas
    Lindlöf, Ludvig
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Ramirez Hernandez, Tabea
    Agile Management Practices for Solutions Development: Managerial Challenges in an  Interorganizational Context2021Inngår i: Proceedings of Spring Servitization Conference, 2021Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Purpose: Solutions development among several actors gives rise to a tension between  stability, that is, the need to standardise and synchronise development activities, and  agility, meaning the need to respond and adapt to a changing environment, which is  represented, for example, in agile management practices. This study focuses on agile  solutions development in an interorganisational context to investigate and characterise  this agility-stability tension. 

    Design/Methodology/Approach: This study bases its insights on findings derived from  two focus groups and interviews with managers and specialists within the area of study. 

    Findings: The findings show strong challenges deriving from the agility-stability tension.  These can be organised in a typology of artefacts, roles, and processes. 

    Originality/Value: The results of this study contribute to the servitization literature on  co-creation, solutions development, and agile management practices, by providing a  novel understanding of the challenges arising in interorganisational solutions  development through the identification and characterisation of the agility-stability  tension.

  • 26.
    Jagstedt, Siri
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system. Karlstad University, Sweden.
    Mellegård, Niklas
    Ictech, Sweden.
    Lind, Kenneth
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Dependencies as a barrier for continuous innovation in cyber-physical systems2023Inngår i: International Journal of Technology Management, ISSN 0267-5730, E-ISSN 1741-5276, Vol. 93, nr 3-4, s. 194-219Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In the automotive domain, as an example of cyber-physical systems, continuous software deployment is actively explored to deliver increasingly capable features to existing fleets of vehicles. The distributed nature of software coupled with tight hardware integration and potentially tremendous variability between vehicles make ensuring compatibility of updated software a significant challenge – both technically and managerially. While the automotive industry commonly forms larger multi-brand organisations to utilise economies of scale, processes for continuous deployment contradictory assumes a single organisation with full control. This paper sets out to shed light on challenges of adopting continuous deployment in the context of such a multi-brand cyber-physical systems organisation. Following a case study, the paper describes a tension between the managerial perspective concerned with platform strategies, and the engineering perspective responsible for developing products from those platforms. The paper highlights software dependencies as a barrier to continuous innovation of cyber-physical systems in multi-brand organisations.

  • 27.
    Jagstedt, Siri
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Mellegård, Niklas
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Lind, Kenneth
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Managing Dependencies to enable Continuous Innovation in an automotive multi-brand organisation2021Inngår i: Proc. of 22nd CINet Conference., 2021Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Software is an enabler for continuously delivering product innovations to customers. In the automotive domain, continuous software deployment is actively investigated to deliver increasingly capable features to existing fleets of vehicles. The distributed nature of vehicle software coupled with tight hardware integration and a potentially tremendous variability between vehicle individuals makes ensuring compatibility of updated software a significant challenge—both technically and managerially. Agile development processes address such challenges with short development cycles, informal inter-team communication, and tool-support for continuous integration and automated testing. This, however, normally assumes a single organisation with full control of their processes, while the automotive industry commonly forms larger multi-brand organisations to utilise economy of scale—a case not sufficiently investigated by current literature. In this paper we identify and describe organisational challenges with managing software dependencies in the context of a multi-brand automotive organisation. Through an exploratory, qualitative case[1]study we characterise software dependencies to link their technical nature with managerial challenges facing the organisations, which can support an organisation to formulate efficient management strategies.

  • 28.
    Linåker, Johan
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Robles, Gregorio
    Universidad Rey Juan Carlos, Spain.
    Bryant, Deborah
    Open Source Initiative, USA.
    Sashiko, Muto
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Open Source Software in the Public Sector: 25 Years and Still in Its Infancy2023Inngår i: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 40, nr 4, s. 39-44Artikkel, forskningsoversikt (Fagfellevurdert)
    Abstract [en]

    The proliferation of Open Source Software (OSS) adoption and collaboration has surged within industry, resulting in its ubiquitous presence in commercial offerings and shared digital infrastructure. However, in the public sector, both awareness and adoption of OSS is still in its infancy due to a number of obstacles including regulatory, cultural, and capacity-related challenges. This special issue is a call for action, highlighting the necessity for both research and practice to narrow the gap, selectively transfer and adapt existing knowledge, as well as generate new knowledge to enable the public sector to fully harness the potential benefits OSS has to offer. 

  • 29.
    Linåker, Johan
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Runeson, Per
    Lund University, Sweden.
    Zuiderwijk, Anneke
    Delft University of Technology, Netherlands.
    Brock, Aamanda
    OpenUK, UK.
    Collaborative Aspects of Open Data in Software Engineering2022Inngår i: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 39, nr 1, s. 31-35Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Engineers require high-quality data for the design and implementation of today's software, especially in the context of machine learning (ML). This puts an emphasis on the need for the publication and sharing of data from and between organizations, public as well as private. Following the paradigm of open innovation, open data provide a mechanism to increase the availability of information, offering utility and improving innovation and user choice through the inevitable interoperability this enables. 

  • 30.
    Martini, Antonio
    et al.
    University of Oslo, Norway.
    Besker, Terese
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Posch, Torsten
    Siemens AG, Germany.
    Bosch, Jan
    Chalmers University of Technology, Sweden.
    TD Pulse: Assessing the Systematic Management of Technical Debt2023Inngår i: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 40, nr 3, s. 54-62Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Technical Debt requires the management of several technical and non-technical aspects: process, organization, tools, etc. Software companies must identify where TD is not well managed and where to improve. Based on ten years of research and practice, we have created an effective approach, TD Pulse, to assess Technical Debt Management in large software companies and find critical improvement areas. The approach was used by 232 and evaluated by more than 200 practitioners in three large companies, including Siemens and Zenseact. The results show that our approach is valuable and lightweight. We also share lessons learned from the whole assessment experience. 

  • 31.
    Mellegård, Niklas
    et al.
    RISE - Research Institutes of Sweden (2017-2019), ICT, Viktoria.
    Burden, Håkan
    RISE - Research Institutes of Sweden (2017-2019), ICT, Viktoria.
    Levin, Daniel
    Volvo Car Corporation, Sweden.
    Lind, Kenneth
    HiMinds Göteborg AB, Sweden.
    Magazinius, Ana
    RISE - Research Institutes of Sweden (2017-2019), ICT, Viktoria.
    Contrasting Big Bang with Continuous Integration Through Defect Reports2020Inngår i: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 37, nr 3, s. 14-20Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Continuous integration promises earlier defect detection, quality improvements and more customer value delivered faster. But what evidence is there? In this longitudinal case study we examined the development of software for the advanced safety and driver support component of a Swedish vehicle manufacturer in two consecutive projects, where the first was developed in a big bang fashion, typical to a traditional waterfall process, while the second project utilized continuous integration. By contrasting the two projects, we evaluated the introduction of continuous integration and supplement earlier claims based on interview studies with a quantitative analysis of defect reports.

  • 32.
    Mellegård, Niklas
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Burden, Håkan
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Levin, Daniel
    Volvo, Sweden.
    Lind, Kenneth
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Magazinius, Ana
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Contrasting Big Bang with Continuous Integration through Defect Reports2021Inngår i: 2021 IEEE 18th International Conference on Software Architecture Companion (ICSA-C), 2021, s. 29-29Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Continuous integration promises earlier defect detection, quality improvements, and more customer value delivered faster. In this case study, we examined development of software for the advanced safety and driver support component of a Swedish vehicle manufacturer in two consecutive projects.

  • 33.
    Olsson, Thomas
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Road Data Lab – Creating an open data ecosystem2022Rapport (Annet vitenskapelig)
    Abstract [en]

    The overall goal of the Road Data Lab (RoDL) project is to establish a community platform around open data for roads. The community today consists of AI Sweden who provide a technical platform for storing and sharing data as well as legal knowledge and expertise, community cooperation with several partner organizations and other data labs spearheaded by RISE, and the continued work on open data in general with Lund University and others. We have also during the project made a number of data sets available, from the project partners and others. Lastly, we conducted a hackathon with data from the project as a way to disseminate knowledge of our data and promote utilization. We have published 4 data sets as part of RoDL: The Volvo highway data set, the Zenseact data, Hövding data, and a synthetic dataset for pedestrian detection. The datasets are made available under different open licenses. Working with open innovation and open data have an impact on business models. Open-source software is today established and organizations have experience for what part of their software to make openly available. This is not the case for data. One goal of RoDL was to investigate obstacles and solutions for organizations in terms of the business of open data. However, we could only scratch the surface of this problem – mainly from a license perspective. We see a need for future work to better understand and have solutions for organizations in their analysis of the business of open data.

    Fulltekst (pdf)
    fulltext
  • 34.
    Olsson, Thomas
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Sentilles, Séverine
    Mälardalen University, Sweden.
    Papatheocharous, Efi
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    A systematic literature review of empirical research on quality requirements2022Inngår i: Requirements Engineering, ISSN 0947-3602, E-ISSN 1432-010X, Vol. 27, nr 2, s. 249-271Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Quality requirements deal with how well a product should perform the intended functionality, such as start-up time and learnability. Researchers argue they are important and at the same time studies indicate there are deficiencies in practice. Our goal is to review the state of evidence for quality requirements. We want to understand the empirical research on quality requirements topics as well as evaluations of quality requirements solutions. We used a hybrid method for our systematic literature review. We defined a start set based on two literature reviews combined with a keyword-based search from selected publication venues. We snowballed based on the start set. We screened 530 papers and included 84 papers in our review. Case study method is the most common (43), followed by surveys (15) and tests (13). We found no replication studies. The two most commonly studied themes are (1) differentiating characteristics of quality requirements compared to other types of requirements, (2) the importance and prevalence of quality requirements. Quality models, QUPER, and the NFR method are evaluated in several studies, with positive indications. Goal modeling is the only modeling approach evaluated. However, all studies are small scale and long-term costs and impact are not studied. We conclude that more research is needed as empirical research on quality requirements is not increasing at the same rate as software engineering research in general. We see a gap between research and practice. The solutions proposed are usually evaluated in an academic context and surveys on quality requirements in industry indicate unsystematic handling of quality requirements.

  • 35.
    Olsson, Thomas
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Wnuk, Krzysztof
    Blekinge Institute of Technology, Sweden.
    Jansen, Slinger
    LUT University, Finland.
    A validated model for the scoping process of quality requirements: a multi-case study2021Inngår i: Empirical Software Engineering, ISSN 1382-3256, E-ISSN 1573-7616, Vol. 26, nr 2Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Quality requirements are vital to developing successful software products. However, there exist evidence that quality requirements are managed mostly in an “ad hoc” manner and down-prioritized. This may result in insecure, unstable, slow products, and unhappy customers. We have developed a conceptual model for the scoping process of quality requirements – QREME – and an assessment model – Q-REPM – for companies to benchmark when evaluating and improving their quality requirements practices. Our model balances an upfront forward-loop with a data-driven feedback-loop. Furthermore, it addresses both strategic and operational decisions. We have evaluated the model in a multi-case study at two companies in Sweden and three companies in The Netherlands. We assessed the scoping process practices for quality requirements and provided improvement recommendations for which practices to improve. The study confirms the existence of the constructs underlying QREME. The companies perform, in the median, 24% of the suggested actions in Q-REPM. None of the companies work data-driven with their quality requirements, even though four out of five companies could technically do so. Furthermore, on the strategic level, quality requirements practices are not systematically performed by any of the companies. The conceptual model and assessment model capture a relevant view of the quality requirements practices and offer relevant improvement proposals. However, we believe there is a need for coupling quality requirements practices to internal and external success factors to motive companies to change their ways of working. We also see improvement potential in the area of business intelligence for QREME in selecting data sources and relevant stakeholders.

    Fulltekst (pdf)
    fulltext
  • 36.
    Petersen, Kai
    et al.
    Blekinge Institute of Technology, Sweden; University of Applied Sciences Flensburg, Germany.
    Carlson, Jan
    Mälardalen University, Sweden.
    Papatheocharous, Efi
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Wnuk, Krzysztof
    Blekinge Institute of Technology, Sweden.
    Context checklist for industrial software engineering research and practice2021Inngår i: Computer Standards & Interfaces, ISSN 0920-5489, E-ISSN 1872-7018, Vol. 78, artikkel-id 103541Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The relevance of context is particularly stressed in case studies, where it is said that “case study is an empirical method aimed at investigating contemporary phenomena in their context”. In this research, we classify context information and provide a context checklist for industrial software engineering. The checklist serves the purpose of (a) supporting researchers and practitioners in characterizing the context in which they are working; (b) supporting researchers with a checklist to identify relevant contextual information to elicit and report during primary and secondary studies. We utilized a systematic approach for constructing the classification of context information and provided a detailed definition for each item. We collected feedback from researchers as well as practitioners. The usefulness of the checklist was perceived more positively by researchers than practitioners, though they highlighted benefits (raising awareness of the importance of context and usefulness for management). The understandability was perceived positively by both practitioners and researchers. The checklist may serve as a “meta-model”, forming the basis for specific adaptations for different research areas, and as input for researchers deciding which context information to extract in systematic reviews. The checklist may also help researchers in reporting context in research papers.

  • 37.
    Poncelet, Clément
    et al.
    Uppsala University,Sweden.
    Sagonas, Konstantinos
    Uppsala University, Sweden; National Technical University of Athens, Greece.
    Tsiftes, Nicolas
    RISE Research Institutes of Sweden, Digitala system, Datavetenskap. KTH Royal Institute of Technology, Sweden.
    So Many Fuzzers, So Little Time: Experience from Evaluating Fuzzers on the Contiki-NG Network (Hay)Stack2022Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Fuzz testing (“fuzzing”) is a widely-used and effective dynamic technique to discover crashes and security vulnerabilities in software, supported by numerous tools, which keep improving in terms of their detection capabilities and speed of execution. In this paper, we report our findings from using state-of-the-art mutation-based and hybrid fuzzers (AFL, Angora, Honggfuzz, Intriguer, MOpt-AFL, QSym, and SymCC) on a non-trivial code base, that of Contiki-NG, to expose and fix serious vulnerabilities in various layers of its network stack, during a period of more than three years. As a by-product, we provide a Git-based platform which allowed us to create and apply a new, quite challenging, open-source bug suite for evaluating fuzzers on real-world software vulnerabilities. Using this bug suite, we present an impartial and extensive evaluation of the effectiveness of these fuzzers, and measure the impact that sanitizers have on it. Finally, we offer our experiences and opinions on how fuzzing tools should be used and evaluated in the future.

    Fulltekst (pdf)
    So-Many-Fuzzers@ASE-22.pdf
  • 38.
    Robles, Gregorio
    et al.
    Universidad Rey Juan Carlos, Spain.
    Chaudron, Michel R.V.
    TU Eindhoven, Netherlands.
    Jolak, Rodi
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Hebig, Regina
    Universität Rostock, Germany.
    A reflection on the impact of model mining from GitHub2023Inngår i: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 164, artikkel-id 107317Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Context: Since 1998, the ACM/IEEE 25th International Conference on Model Driven Engineering Languages and Systems (MODELS) has been studying all aspects surrounding modeling in software engineering, from languages and methods to tools and applications. In order to enable empirical studies, the MODELS community developed a need for having examples of models, especially of models used in real software development projects. Such models may be used for a range of purposes, but mostly related to domain analysis and software design (at various levels of abstraction). However, finding such models was very difficult. The most used ones had their origin in academic books or student projects, which addressed “artificial” applications, i.e., were not base on real-case scenarios. To address this issue, the authors of this reflection paper, members of the modeling and of the mining software repositories fields, came together with the aim of creating a dataset with an abundance of modeling projects by mining GitHub. As a scoping of our effort we targeted models represented using the UML notation because this is the lingua franca in practice for software modeling. As a result, almost 100k models from 22k projects were made publicly available, known as the Lindholmen dataset. Objective: In this paper, we analyze the impact of our research, and compare this to what we envisioned in 2016. We draw practical lessons gained from this effort, reflect on the perils and pitfalls of the dataset, and point out promising avenues of research. Method: We base our reflection on the systematic analysis of recent research literature, and especially those papers citing our dataset and its associated publications. Results: What we envisioned in the original research when making the dataset available has to a major extent not come true; however, fellow researchers have found alternative uses of the dataset. Conclusions: By understanding the possibilities and shortcomings of the current dataset, we aim to offer the research community i) future research avenues of how the data can be used; and ii) raise awareness of the limitations, not only to point out threats to validity of research, but also to encourage fellow researchers to find ideas to overcome them. Our reflections can also be helpful to researchers who want to perform similar mining efforts.

  • 39.
    Rudmark, Daniel
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Andersson, Magnus
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Feedback Loops in Open Data Ecosystems2022Inngår i: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 39, nr 1Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Public agencies are increasingly publishing open data to increase transparency and fuel data-driven innovation. For these organizations, maintaining sufficient data quality is key to continuous re-use but also heavily dependent on feedback loops being initiated between data publishers and users. This paper reports from a longitudinal engagement with Scandinavian transportation agencies, where such feedback loops have been successfully established. Based on these experiences, we propose four distinct types of data feedback loops in which both data publishers and re-users play critical roles.

    Fulltekst (pdf)
    fulltext
  • 40.
    Rudmark, Daniel
    et al.
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system. University of Gothenburg, Sweden.
    Lindman, Juho
    University of Gothenburg, Sweden.
    Tryti, Andreas
    Entur AS, Norway.
    Dammen, Brede
    Entur AS, Norway.
    Beyond Procurement: How Entur Navigated the Open Source Journey to Advance Public Transport2023Inngår i: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 40, nr 4, s. 62-70Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This report describes how software professionals at the Norwegian public transport organization Entur use open source processes and tools to leverage digital transformation. Moving software acquisition from procurement to open source and in-house development can deliver value but also entails challenges. 

  • 41.
    Runeson, Per
    et al.
    Lund University, Sweden.
    Olsson, Thomas
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Linåker, Johan
    Lund University, Sweden.
    Open Data Ecosystems — An empirical investigation into an emerging industry collaboration concept2021Inngår i: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 182, artikkel-id 111088Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Software systems are increasingly depending on data, particularly with the rising use of machine learning, and developers are looking for new sources of data. Open Data Ecosystems (ODE) is an emerging concept for data sharing under public licenses in software ecosystems, similar to Open Source Software (OSS). It has certain similarities to Open Government Data (OGD), where public agencies share data for innovation and transparency. We aimed to explore open data ecosystems involving commercial actors. Thus, we organized five focus groups with 27 practitioners from 22 companies, public organizations, and research institutes. Based on the outcomes, we surveyed three cases of emerging ODE practice to further understand the concepts and to validate the initial findings. The main outcome is an initial conceptual model of ODEs’ value, intrinsics, governance, and evolution, and propositions for practice and further research. We found that ODE must be value driven. Regarding the intrinsics of data, we found their type, meta-data, and legal frameworks influential for their openness. We also found the characteristics of ecosystem initiation, organization, data acquisition and openness be differentiating, which we advise research and practice to take into consideration. © 2021 The Author(s)

  • 42.
    Saadatmand, Mehrdad
    et al.
    RISE Research Institutes of Sweden, Digitala system, Industriella system.
    Abbas, Muhammad
    RISE Research Institutes of Sweden, Digitala system, Industriella system. Mälardalen University, Sweden.
    Enoiu, Eduard Paul
    Mälardalen University, Sweden.
    Schlingloff, Bernd-Holger
    Fraunhofer, Germany.
    Afzal, Wasif
    Mälardalen University, Sweden.
    Dornauer, Benedikt
    University of Innsbruck, Austria.
    Felderer, Michael
    University of Innsbruck, Austria.
    SmartDelta project: Automated quality assurance and optimization across product versions and variants2023Inngår i: Microprocessors and microsystems, ISSN 0141-9331, E-ISSN 1872-9436, s. 104967-104967, artikkel-id 104967Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Software systems are often built in increments with additional features or enhancements on top of existing products. This incremental development may result in the deterioration of certain quality aspects. In other words, the software can be considered an evolving entity emanating different quality characteristics as it gets updated over time with new features or deployed in different operational environments. Approaching software development with this mindset and awareness regarding quality evolution over time can be a key factor for the long-term success of a company in today’s highly competitive market of industrial software-intensive products. Therefore, it is important to be able to accurately analyze and determine the quality implications of each change and increment to a software system. To address this challenge, the multinational SmartDelta project develops automated solutions for the quality assessment of product deltas in a continuous engineering environment. The project provides smart analytics from development artifacts and system executions, offering insights into quality degradation or improvements across different product versions, and providing recommendations for the next builds. This paper presents the challenges in incremental software development tackled in the scope of the SmartDelta project, and the solutions that are produced and planned in the project, along with the industrial impact of the project for software-intensive industrial systems.

    Fulltekst (pdf)
    fulltext
  • 43.
    Saadatmand, Mehrdad
    et al.
    RISE Research Institutes of Sweden, Digitala system, Industriella system.
    Enoiu, Eduard P
    Mälardalen University, Sweden.
    Schlingloff, Holger
    Fraunhofer, Gerany.
    Felderer, Michael
    University of Innsbruck, Austria.
    Afzal, Wasif
    Mälardalen University, Sweden.
    SmartDelta: Automated Quality Assurance and Optimization in Incremental Industrial Software Systems Development2022Inngår i: Proceedings - 2022 25th Euromicro Conference on Digital System Design, DSD 2022, Institute of Electrical and Electronics Engineers Inc. , 2022, s. 754-760Konferansepaper (Fagfellevurdert)
    Abstract [en]

    A common phenomenon in software development is that as a system is being built and incremented with new features, certain quality aspects of the system begin to deteriorate. Therefore, it is important to be able to accurately analyze and determine the quality implications of each change and increment to a system. To address this topic, the multinational SmartDelta project develops automated solutions for quality assessment of product deltas in a continuous engineering environment. The project will provide smart analytics from development artifacts and system executions, offering insights into quality degradation or improvements across different product versions, and providing recommendations for next builds. 

  • 44.
    Saadatmand, Mehrdad
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Hansson, Hans
    RISE - Research Institutes of Sweden, ICT, SICS. Mälardalen University.
    Thane, Henrik
    Safety Integrity AB.
    Hänninen, Kaj
    Mälardalen University.
    Inadequate Risk Analysis Might Jeopardize The Functional Safety of Modern Systems2016Rapport (Annet vitenskapelig)
    Abstract [en]

    In the early 90s, researchers began to focus on security as an important property to address in combination with safety. Over the years, researchers have proposed approaches to harmonize activities within the safety and security disciplines. Despite the academic efforts to identify interdependencies and to propose combined approaches for safety and security, there is still a lack of integration between safety and security practices in the industrial context, as they have separate standards and independent processes often addressed and assessed by different organizational teams and authorities. Specifically, security concerns are generally not covered in any detail in safety standards potentially resulting in successfully safety-certified systems that still are open for security threats from e.g., malicious intents from internal and external personnel and hackers that may jeopardize safety. In recent years security has again received an increasing attention of being an important issue also in safety assurance, as the open interconnected nature of emerging systems makes them susceptible to security threats at a much higher degree than existing more confined products.This article presents initial ideas on how to extend safety work to include aspects of security during the context establishment and initial risk assessment procedures. The ambition of our proposal is to improve safety and increase efficiency and effectiveness of the safety work within the frames of the current safety standards, i.e., raised security awareness in compliance with the current safety standards. We believe that our proposal is useful to raise the security awareness in industrial contexts, although it is not a complete harmonization of safety and security disciplines, as it merely provides applicable guidance to increase security awareness in a safety context.

    Fulltekst (pdf)
    fulltext
  • 45.
    Saadatmand, Mehrdad
    et al.
    RISE Research Institutes of Sweden, Digitala system, Industriella system.
    Truscan, D.
    Åbo Akademi University, Finland.
    Enoiu, E.
    Mälardalen University, Sweden.
    Message from the ITEQS 2022 Workshop Chairs2022Inngår i: Proceedings - 2022 IEEE 14th International Conference on Software TestingArtikkel i tidsskrift (Annet vitenskapelig)
  • 46.
    Seitz, Ludwig
    et al.
    Combitech AB, Sweden.
    Tiloca, Marco
    RISE Research Institutes of Sweden, Digitala system, Datavetenskap.
    Gunnarsson, Martin
    RISE Research Institutes of Sweden, Digitala system, Datavetenskap.
    Höglund, Rikard
    RISE Research Institutes of Sweden, Digitala system, Datavetenskap.
    Secure Software Updates for IoT Based on Industry Requirements2023Inngår i: Proceedings of the 9th International Conference on Information Systems Security and Privacy, SCITEPRESS - Science and Technology Publications , 2023, s. 698-705Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper analyzes the problem and requirements of securely distributing software updates over the Internet, to devices in an Industrial Control System (ICS) and more generally in Internet of Things (IoT) infrastructures controlling a physical system, such as power grids and water supply systems. We present a novel approach that allows to securely distribute software updates of different types, e.g., device firmware and customer applications, and from sources of different type, e.g., device operators, device manufacturers and third-party library providers. Unlike previous works on this topic, our approach keeps the device operator in control of the update process, while ensuring both authenticity and confidentiality of the distributed software updates.

  • 47.
    Stancek, Martin
    et al.
    Gratex International a.s., Slovakia.
    Polasek, Ivan
    Gratex International a.s., Slovakia; Comenius University, Slovakia.
    Zalabai, Tibor
    Gratex International a.s., Slovakia.
    Vincur, Juraj
    Comenius University, Slovakia.
    Jolak, Rodi
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Chaudron, Michel
    Eindhoven University of Technology, Netherlands.
    Collaborative software design and modeling in virtual reality2024Inngår i: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 166, artikkel-id 107369Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Context: Software engineering is becoming more and more distributed. Developers and other stakeholders are often located in different locations, departments, and countries and operating within different time zones. Most online software design and modeling tools are not adequate for distributed collaboration since they do not support awareness and lack features for effective communication. Objective: The aim of our research is to support distributed software design activities in Virtual Reality (VR). Method: Using design science research methodology, we design and evaluate a tool for collaborative design in VR. We evaluate the collaboration efficiency and recall of design information when using the VR software design environment compared to a non-VR software design environment. Moreover, we collect the perceptions and preferences of users to explore the opportunities and challenges that were incurred by using the VR software design environment. Results: We find that there is no significant difference in the efficiency and recall of design information when using the VR compared to the non-VR environment. Furthermore, we find that developers are more satisfied with collaboration in VR. Conclusion: The results of our research and similar studies show that working in VR is not yet faster or more efficient than working on standard desktops. It is very important to improve the interface in VR (gestures with haptics, keyboard and voice input), as confirmed by the difference in results between the first and second evaluation. 

    Fulltekst (pdf)
    fulltext
  • 48.
    Tornhill, Adam
    et al.
    CodeScene, Sweden.
    Borg, Markus
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Code Red: The Business Impact of Code Quality - A Quantitative Study of 39 Proprietary Production Codebases2022Inngår i: Proceedings - International Conference on Technical Debt 2022, TechDebt 2022, Institute of Electrical and Electronics Engineers Inc. , 2022, s. 11-20Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Code quality remains an abstract concept that fails to get traction at the business level. Consequently, software companies keep trading code quality for time-to-market and new features. The resulting technical debt is estimated to waste up to 42% of developers' time. At the same time, there is a global shortage of software developers, meaning that developer productivity is key to software businesses. Our overall mission is to make code quality a business concern, not just a technical aspect. Our first goal is to understand how code quality impacts 1) the number of reported defects, 2) the time to resolve issues, and 3) the predictability of resolving issues on time. We analyze 39 proprietary production codebases from a variety of domains using the CodeScene tool based on a combination of source code analysis, version-control mining, and issue information from Jira. By analyzing activity in 30,737 files, we find that low quality code contains 15 times more defects than high quality code. Furthermore, resolving issues in low quality code takes on average 124% more time in development. Finally, we report that issue reso-lutions in low quality code involve higher uncertainty manifested as 9 times longer maximum cycle times. This study provides evi-dence that code quality cannot be dismissed as a technical concern. With 15 times fewer defects, twice the development speed, and substantially more predictable issue resolution times, the business advantage of high quality code should be unmistakably clear. 

  • 49.
    Vercammen, Sten
    et al.
    University of Antwerp, Belgium.
    Demeyer, Serge
    University of Antwerp, Belgium.
    Borg, Markus
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    F-ASTMut mutation optimisations techniques using the Clang front-end[Formula presented]2023Inngår i: Software Impacts, ISSN 2665-9638, Vol. 16, artikkel-id 100500Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    F-ASTMut is an open-source mutation testing research tool for the C language family based on manipulation of the abstract syntax tree. The tool is designed for detailed measurements, analysis, and tuning of optimisation techniques. The goal of F-ASTMut is to analyse the speedups of optimisation techniques to ultimately enable mutation testing in industrial settings. Currently, F-ASTMut features four optimisation techniques; an exclusion scheme for invalid mutants, a test-suit-scope reduction to only cover relevant mutants, mutant schemata, and split-stream mutation testing. The implementation relies on the Clang front-end, allowing future work to extend or build on top of our solution. © 2023 The Author(s)

  • 50.
    Vercammen, Sten
    et al.
    University of Antwerp, Belgium.
    Demeyer, Serge
    University of Antwerp, Belgium.
    Borg, Markus
    RISE Research Institutes of Sweden, Digitala system, Mobilitet och system.
    Claessens, Robbe
    University of Antwerp, Belgium.
    Flaky mutants; Another concern for mutation testing2021Inngår i: Proceedings - 2021 IEEE 14th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2021, Institute of Electrical and Electronics Engineers Inc. , 2021, s. 284-285Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Software testing is the dominant method for quality assurance and control in software engineering. Test suites serve as quality gates to safeguard against programming faults. But not every test suite is written equally. We usually gauge its quality using metrics such as code coverage. These assess how much of the code base has been covered. However, they do not tell if the tests actually test and verify the intentions. Mutation testing does this by deliberately injecting faults into the system under test and verifying how many of them the test suite can detect. For every injected fault that is not detected by the test suite, an additional test should be written. In the academic community, mutation testing is acknowledged as the most promising technique for automated assessment of the strength of a test suite.

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