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  • 1.
    Bjarnason, Elizabeth
    et al.
    Lund University, Sweden.
    Borg, Markus
    RISE., Swedish ICT, SICS, Security Lab.
    Aligning Requirements and Testing - Working Together Toward the Same Goal2017Inngår i: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 34, nr 1, s. 20-23, artikkel-id 7819382Artikkel i tidsskrift (Annet vitenskapelig)
    Abstract [en]

    The proper alignment of requirements engineering and testing (RET) can be key to software's success. Three practices can provide effective RET alignment: using test cases as requirements, harvesting trace links, and reducing distances between requirements engineers and testers. The Web extra https://youtu.be/M65ZKxfxqME is an audio podcast of author Elizabeth Bjarnason reading the the Requirements column she cowrote with Markus Borg.

  • 2.
    Bjarnason, Elizabeth
    et al.
    Lund University, Sweden.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Aligning Requirements and Testing: Working Together toward the Same Goal2017Inngår i: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 34, nr 1, s. 20-23, artikkel-id 7819382Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    The proper alignment of requirements engineering and testing (RET) can be key to software's success. Three practices can provide effective RET alignment: using test cases as requirements, harvesting trace links, and reducing distances between requirements engineers and testers. The Web extra https://youtu.be/M65ZKxfxqME is an audio podcast of author Elizabeth Bjarnason reading the the Requirements column she cowrote with Markus Borg. © 2017 IEEE.

  • 3.
    Bjarnason, Elizabeth
    et al.
    Lund University, Sweden.
    Borg, Markus
    RISE., Swedish ICT, SICS, Security Lab. Lund University, Sweden.
    Lindvall, Bertil
    Lund University, Sweden.
    Supervising for Independence – A Case Study of Master Science Projects in Higher Education2015Inngår i: LU:s femte högskolepedagogiska utvecklingskonferens, 2015, 12Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Students completing a Swedish Master's degree in engineering should have knowledge and skills to independently solve engineering issues. This autonomy should be developed and demonstrated within the M.Sc. project course. But, how can supervisors encourage independence? We have explored this in a case study through semi-structured interviews with students, supervisors and examiners of two M.Sc. projects. We investigated their view of independence, and how supervision correlates to independence. The results identify areas relevant to independence, namely supervision roles and relationships, student characteristics, M.Sc. process, and view on independence. The results confirm previous findings that students' knowledge of and motivation for the topic support independence. The supervisor's role is to guide and support through frequent peer-level discussions and to act as a discussion partner, while the student should have the main responsibility for the project. We conclude that it is important for supervisors to encourage students to take ownership of their M.Sc. projects and to design their own solutions, while providing the overall process and timelines.

  • 4. Bjarnason, Elizabeth
    et al.
    Borg, Markus
    RISE., Swedish ICT, SICS, Security Lab.
    Lindvall, Bertil
    Supervising Towards Independence2016Annet (Annet vitenskapelig)
    Abstract [en]

    Supervising a student can be compared to teaching someone to drive a car. The student is in the driver's seat while the supervisor provides structure and guidance, and can intervene in risky and unsafe situations. It is a learning process in which the student gradually gains experience and sufficient skill to obtain a driving license, and to drive without an instructor. Similarly, a student attending the MSc project course at the technical faculty of Lund University is to "develop and demonstrate knowledge and ability required to autonomously work as an engineer" (from MSc course plan). But what factors affect a MSc project, and how can we as supervisors support students in their learning process towards independence? We performed a case study of two completed MSc projects where we interviewed the student, the supervisor and the examiner for each case. In this article we present the main conclusions drawn from the cross-case analysis of this study. Details on the studied cases and the results on which these conclusions are based can be found in our previous publication of this study.

  • 5.
    Bjarnason, Elizabeth
    et al.
    Lund University, Sweden.
    Unterkalmsteiner, Michael
    Blekinge Institute of Technology, Sweden.
    Borg, Markus
    RISE., Swedish ICT, SICS, Security Lab.
    Engström, Emelie
    Lund University, Sweden.
    A Multi-Case Study of Agile Requirements Engineering and the Use of Test Cases as Requirements2016Inngår i: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 77, s. 61-79Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    [Context] It is an enigma that agile projects can succeed "without requirements" when weak requirements engineering is a known cause for project failures. While agile development projects often manage well without extensive requirements test cases are commonly viewed as requirements and detailed requirements are documented as test cases. [Objective] We have investigated this agile practice of using test cases as requirements to understand how test cases can support the main requirements activities, and how this practice varies. [Method] We performed an iterative case study at three companies and collected data through 14 interviews and 2 focus groups. [Results] The use of test cases as requirements poses both benefits and challenges when eliciting, validating, verifying, and managing requirements, and when used as a documented agreement. We have identified five variants of the test-cases-as-requirements practice, namely de facto, behaviour-driven, story-test driven, stand-alone strict and stand-alone manual for which the application of the practice varies concerning the time frame of requirements documentation, the requirements format, the extent to which the test cases are a machine executable specification and the use of tools which provide specific support for the practice of using test cases as requirements. [Conclusions] The findings provide empirical insight into how agile development projects manage and communicate requirements. The identified variants of the practice of using test cases as requirements can be used to perform in-depth investigations into agile requirements engineering. Practitioners can use the provided recommendations as a guide in designing and improving their agile requirements practices based on project characteristics such as number of stakeholders and rate of change.

  • 6.
    Borg, Markus
    RISE., Swedish ICT, SICS, Security Lab. Lund University, Sweden.
    TuneR: A Framework for Tuning Software Engineering Tools with Hands-on Instructions in R2016Inngår i: Journal of Software: Evolution and Process, ISSN 2047-7473, E-ISSN 2047-7481, Vol. 28, nr 6, s. 427-459Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Numerous tools automating various aspects of software engineering have been developed, and many of the tools are highly configurable through parameters. Understanding the parameters of advanced tools often requires deep understanding of complex algorithms. Unfortunately, suboptimal parameter settings limit the performance of tools and hinder industrial adaptation, but still few studies address the challenge of tuning software engineering tools. We present TuneR, an experiment framework that supports finding feasible parameter settings using empirical methods. The framework is accompanied by practical guidelines of how to use R to analyze the experimental outcome. As a proof-of-concept, we apply TuneR to tune ImpRec, a recommendation system for change impact analysis in a software system that has evolved for more than two decades. Compared with the output from the default setting, we report a 20.9% improvement in the response variable reflecting recommendation accuracy. Moreover, TuneR reveals insights into the interaction among parameters, as well as nonlinear effects. TuneR is easy to use, thus the framework has potential to support tuning of software engineering tools in both academia and industry.

  • 7.
    Borg, Markus
    et al.
    RISE., Swedish ICT, SICS, Security Lab.
    Alégroth, Emil
    Blekinge Institute of Technology, Sweden.
    Runeson, Per
    Lund University, Sweden.
    Software Engineers' Information Seeking Behavior in Change Impact Analysis: An Interview Study2017Inngår i: ICPC '17 Proceedings of the 25th International Conference on Program Comprehension, IEEE Press, 2017, s. 12-22Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Software engineers working in large projects must navigate complex information landscapes. Change Impact Analysis (CIA) is a task that relies on engineers' successful information seeking in databases storing, e.g., source code, requirements, design descriptions, and test case specifications. Several previous approaches to support information seeking are task-specific, thus understanding engineers' seeking behavior in specific tasks is fundamental. We present an industrial case study on how engineers seek information in CIA, with a particular focus on traceability and development artifacts that are not source code. We show that engineers have different information seeking behavior, and that some do not consider traceability particularly useful when conducting CIA. Furthermore, we observe a tendency for engineers to prefer less rigid types of support rather than formal approaches, i.e., engineers value support that allows flexibility in how to practically conduct CIA. Finally, due to diverse information seeking behavior, we argue that future CIA support should embrace individual preferences to identify change impact by empowering several seeking alternatives, including searching, browsing, and tracing.

  • 8.
    Borg, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Bjarnason, Elizabeth
    Lund University, Sweden.
    Unterkalmsteiner, Michael
    Blekinge Institute of Technology, Sweden.
    Yu, Tingting
    University of Kentucky, USA.
    Gay, Gregory
    University of South Carolina, USA.
    Felderer, Michael
    University of Innsbruck, Austria.
    Summary of the 4th International Workshop on Requirements Engineering and Testing (RET 2017)2018Inngår i: Software Engineering Notes: an Informal Newsletter of The Specia, ISSN 0163-5948, E-ISSN 1943-5843, Vol. 42, nr 4, s. 28-31Artikkel i tidsskrift (Annet vitenskapelig)
  • 9.
    Borg, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Brytting, Andreas
    KTH Royal Institute of Technology, Sweden.
    Hansson, Daniel
    Verifyter AB, Sweden.
    An Analytical View ofTest Results Using CityScapes2018Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    t— In this paper we map test results from a real ASIC project on to the file structure of the design under test andpresent it as a cityscape. In the cityscape each house is a file where its height reflects the number of commits to that file. Thecolor reflects the fraction of bad commits.We identify error prone areas (red "bad" neighborhoods) as well as the most active areas (tall "downtown" areas). Thecityscape also allows us to identify potential test coverage holes (tall green buildings) where there are a lot of activities but nofailures.

  • 10.
    Borg, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Brytting, Andreas
    KTH Royal Institute of Technology, Sweden.
    Hansson, Daniel
    Verifyter AB, Sweden.
    Enabling Visual Design Verification Analytics– From Prototype Visualizations to anAnalytics Tool using the Unity Game Engine2018Konferansepaper (Annet vitenskapelig)
    Abstract [en]

    The ever-increasing architectural complexity in contemporary ASIC projects turns Design Verification (DV)into a highly advanced endeavor. Pressing needs for short time-to-market has made automation a key solution in DV.However, recurring execution of large regression suites inevitably leads to challenging amounts of test results. Following thedesign science paradigm, we present an action research study to introduce visual analytics in a commercial ASIC project. Wedevelop a cityscape visualization tool using the game engine Unity. Initial evaluations are promising, suggesting that the tooloffers a novel approach to identify error-prone parts of the design, as well as coverage holes.

  • 11.
    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 component sourcing options: A survey of software engineering's broader make-or-buy decisions2019Inngår i: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 112, s. 18-34Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Context: 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 from external 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. Objective: Unfortunately, there is little available research on how organizations 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. Results: 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. Conclusion: 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.

  • 12.
    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.

  • 13.
    Borg, Markus
    et al.
    RISE., Swedish ICT, SICS, Security Lab.
    de la Vara, José Luis
    Carlos III University of Madrid, Spain.
    Wnuk, Krzysztof
    Blekinge Institute of Technology, Sweden.
    Practitioners' Perspectives on Change Impact Analysis for Safety-Critical Software - A Preliminary Analysis2016Inngår i: Computer Safety, Reliability, and Security: SAFECOMP 2016 Workshops / [ed] Amund Skavhaug, Jérémie Guiochet, Erwin Schoitsch, Friedemann Bitsch, 2016, 11, Vol. 9923, s. 346-358Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Safety standards prescribe change impact analysis (CIA) during evolution of safety-critical software systems. Although CIA is a fundamental activity, there is a lack of empirical studies about how it is performed in practice. We present a case study on CIA in the context of an evolving automation system, based on 14 interviews in Sweden and India. Our analysis suggests that engineers on average spend 50-100 hours on CIA per year, but the effort varies considerably with the phases of projects. Also, the respondents presented different connotations to CIA and perceived the importance of CIA differently. We report the most pressing CIA challenges, and several ideas on how to support future CIA. However, we show that measuring the effect of such improvement solutions is non-trivial, as CIA is intertwined with other development activities. While this paper only reports preliminary results, our work contributes empirical insights into practical CIA.

  • 14.
    Borg, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Englund, Cristofer
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Duran, Boris
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Traceability and Deep Learning: Safety-critical Systems with Traces Ending in Deep Neural Networks2017Konferansepaper (Annet vitenskapelig)
  • 15. Borg, Markus
    et al.
    Englund, Cristofer
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Wnuk, Krzysztof
    Blekinge Institute of Technology, Sweden.
    Duran, Boris
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Levandowski, Christoffer
    QRTECH AB, Sweden.
    Gao, Shenjian
    Blekinge Institute of Technology, Sweden.
    Tan, Yanwen
    Blekinge Institute of Technology, Sweden.
    Kaijser, Henrik
    AB Volvo, Sweden.
    Lönn, Henrik
    AB Volvo, Sweden.
    Törnqvist, Jonas
    QRTECH AB, Sweden.
    Safely Entering the Deep: A Review of Verification and Validation for Machine Learning and a Challenge Elicitation in the Automotive Industry2019Inngår i: Journal of Automotive Software Engineering, Vol. 1, nr 1, s. 1-13Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Deep neural networks (DNNs) will emerge as a cornerstone in automotive software engineering. However, developing systems with DNNs introduces novel challenges for safety assessments. This paper reviews the state-of-the-art in verification and validation of safety-critical systems that rely on machine learning. Furthermore, we report from a workshop series on DNNs for perception with automotive experts in Sweden, confirming that ISO 26262 largely contravenes the nature of DNNs. We recommend aerospace-to-automotive knowledge transfer and systems-based safety approaches, for example, safety cage architectures and simulated system test cases.

  • 16.
    Borg, Markus
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Garousi, Vahid
    Wageningen University, Netherlands.
    Mahmoud, Anas
    Louisiana State University, US.
    Olsson, Thomas
    RISE - Research Institutes of Sweden, ICT, SICS.
    Stalberg, Oskar
    Plausible Concept, Sweden.
    Video Game Development in a Rush: A Survey of the Global Game Jam Participants2019Inngår i: IEEE Transactions on Games, ISSN 2475-1502Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Video game development is a complex endeavor, often involving complex software, large organizations, and aggressive release deadlines. Several studies have reported that periods of “crunch time” are prevalent in the video game industry, but there are few studies on the effects of time pressure. We conducted a survey with participants of the Global Game Jam (GGJ), a 48-hour hackathon. Based on 198 responses, the results suggest that: (1) iterative brainstorming is the most popular method for conceptualizing initial requirements; (2) continuous integration, minimum viable product, scope management, version control, and stand-up meetings are frequently applied development practices; (3) regular communication, internal playtesting, and dynamic and proactive planning are the most common quality assurance activities; and (4) familiarity with agile development has a weak correlation with perception of success in GGJ. We conclude that GGJ teams rely on ad hoc approaches to development and face-to-face communication, and recommend some complementary practices with limited overhead. Furthermore, as our findings are similar to recommendations for software startups, we posit that game jams and the startup scene share contextual similarities. Finally, we discuss the drawbacks of systemic “crunch time” and argue that game jam organizers are in a good position to problematize the phenomenon.

  • 17.
    Borg, Markus
    et al.
    RISE., Swedish ICT, SICS, Security Lab.
    Lennerstad, Iben
    Lund University, Sweden.
    Ros, Rasmus
    Lund University, Sweden.
    Bjarnason, Elizabeth
    Lund University, Sweden.
    On using active learning and self-training when mining performance discussions on stack overflow2017Inngår i: EASE'17 Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering. ACM International Conference Proceeding Series, 2017, s. 308-313Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Abundant data is the key to successful machine learning. However, supervised learning requires annotated data that are often hard to obtain. In a classification task with limited resources, Active Learning (AL) promises to guide annotators to examples that bring the most value for a classifier. AL can be successfully combined with self-training, i.e., extending a training set with the unlabelled examples for which a classifier is the most certain. We report our experiences on using AL in a systematic manner to train an SVM classifier for Stack Overflow posts discussing performance of software components. We show that the training examples deemed as the most valuable to the classifier are also the most difficult for humans to annotate. Despite carefully evolved annotation criteria, we report low inter-rater agreement, but we also propose mitigation strategies. Finally, based on one annotator's work, we show that self-training can improve the classification accuracy. We conclude the paper by discussing implication for future text miners aspiring to use AL and self-training.

  • 18.
    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, France.
    Digitalization of Swedish Government Agencies: A Perspective Through the Lens of a Software Development Census2018Inngår i: Proceedings of the 40th International Conference on Software Engineering: Software Engineering in Society, 2018, s. 37-46Konferansepaper (Fagfellevurdert)
    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.

  • 19.
    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.

  • 20.
    Borg, Markus
    et al.
    RISE., Swedish ICT, SICS, Security Lab.
    Olsson, Thomas
    RISE - Research Institutes of Sweden, ICT, SICS.
    Svensson, John
    Boliden, Sweden.
    From LiDAR to Underground Maps via 5G - Business Models Enabling a System-of-Systems Approach to Mapping the Kankberg Mine2017Rapport (Annet vitenskapelig)
    Abstract [en]

    With ever-increasing productivity targets in mining operations, there is a growing interest in mining automation. The PIMM project addresses the fundamental challenge of network communication by constructing a pilot 5G network in the underground mine Kankberg. In this report, we discuss how such a 5G network could constitute the essential infrastructure to organize existing systems in Kankberg into a system-of-systems (SoS). In this report, we analyze a scenario in which LiDAR equipped vehicles operating in the mine are connected to existing mine mapping and positioning solutions. The approach is motivated by the approaching era of remote controlled, or even autonomous, vehicles in mining operations. The proposed SoS could ensure continuously updated maps of Kankberg, rendered in unprecedented detail, supporting both productivity and safety in the underground mine. We present four different SoS solutions from an organizational point of view, discussing how development and operations of the constituent systems could be distributed among Boliden and external stakeholders, e.g., the vehicle suppliers, the hauling company, and the developers of the mapping software. The four scenarios are compared from both technical and business perspectives, and based on trade-off discussions and SWOT analyses. We conclude our report by recommending continued research along two future paths, namely a closer cooperation with the vehicle suppliers, and further feasibility studies regarding establishing a Kankberg software ecosystem.

  • 21.
    Borg, Markus
    et al.
    RISE., Swedish ICT, SICS, Security Lab.
    Olsson, Thomas
    RISE - Research Institutes of Sweden, ICT, SICS.
    Svensson, John
    Boliden, Sweden.
    Piggybacking on an Autonomous Hauler: Business Models Enabling a System-of-Systems Approach to Mapping an Underground Mine2017Konferansepaper (Fagfellevurdert)
    Abstract [en]

    With ever-increasing productivity targets in mining operations, there is a growing interest in mining automation. In future mines, remote-controlled and autonomous haulers will operate underground guided by LiDAR sensors. We envision reusing LiDAR measurements to maintain accurate mine maps that would contribute to both safety and productivity. Extrapolating from a pilot project on reliable wireless communication in Boliden's Kankberg mine, we propose establishing a system-of-systems (SoS) with LIDAR-equipped haulers and existing mapping solutions as constituent systems. SoS requirements engineering inevitably adds a political layer, as independent actors are stakeholders both on the system and SoS levels. We present four SoS scenarios representing different business models, discussing how development and operations could be distributed among Boliden and external stakeholders, e.g., the vehicle suppliers, the hauling company, and the developers of the mapping software. Based on eight key variation points, we compare the four scenarios from both technical and business perspectives. Finally, we validate our findings in a seminar with participants from the relevant stakeholders. We conclude that to determine which scenario is the most promising for Boliden, trade-offs regarding control, costs, risks, and innovation must be carefully evaluated. 

  • 22.
    Borg, Markus
    et al.
    RISE., Swedish ICT, SICS, Security Lab.
    Petter, Gulin
    Lund University, Sweden.
    Linus, Olofsson
    Lund University, Sweden.
    Do Take it Personal: It's Not What You Say, It's Who (and Where) You Are!2016Inngår i: Tiny Transactions on Computer Science, Vol. 4Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Issue management in market-driven software projects is constantly under time pressure. A limited set of developers must share their time between developing features for the next release and resolving reported issues. Project managers need to find the appropriate balance between a high quality product and fast time to market. We study a telecom company in Sweden developing embedded systems for a consumer market. The project managers report that developers resolve approximately 10% of the issues reported during a project. Consequently, it is critical to properly prioritize the issues to receive the best possible return on investment, and above all to remove all bugs that might impact the market's reception of the product. We use machine learning to investigate what features of an issue report are the best predictors of changes to production code during its corresponding resolution. After removing all features jeopardizing the confidentiality of individual engineers, the issue reports are characterized by 19 features (apart from text). We extract 80,000 issue reports, an equal mix of positive and negative examples, and train a Bayesian Network classifier [2], obtaining 73% classification accuracy. Moreover, it reveals that the feature with the highest predictive value is from which physical site the issue was submitted. The general priority feature however, is only ranked 17 out of 19, whereas the submitting team is ranked 12. Our findings confirm a suspicion in the company: the priority set by the issue submitter is indeed a poor predictor of a future code change.

  • 23.
    Chatzipetrou, Panagiota
    et al.
    Örebro University, Sweden.
    Alégroth, Emil
    Blekinge Institute of Technology, Sweden.
    Papatheocharous, Eli
    University of Cyprus, Cyprus.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Gorschek, Tony
    Blekinge Institute of Technology, Sweden.
    Wnuk, Krzysztof
    Blekinge Institute of Technology, Sweden.
    Component selection in software engineering - Which attributes are the most important in the decision process?2018Inngår i: Proceedings - 44th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2018, 2018, s. 198-205Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Component-based software engineering is a common approach to develop and evolve contemporary software systems where different component sourcing options are available: 1)Software developed internally (in-house), 2)Software developed outsourced, 3)Commercial of the shelf software, and 4) Open Source Software. However, there is little available research on what attributes of a component are the most important ones when selecting new components. The object of the present study is to investigate what matters the most to industry practitioners during component selection. We conducted a cross-domain anonymous survey with industry practitioners involved in component selection. First, the practitioners selected the most important attributes from a list. Next, they prioritized their selection using the Hundred-Dollar ($100) test. We analyzed the results using Compositional Data Analysis. The descriptive results showed that Cost was clearly considered the most important attribute during the component selection. Other important attributes for the practitioners were: Support of the component, Longevity prediction, and Level of off-the-shelf fit to product. Next, an exploratory analysis was conducted based on the practitioners' inherent characteristics. Nonparametric tests and biplots were used. It seems that smaller organizations and more immature products focus on different attributes than bigger organizations and mature products which focus more on Cost. .

  • 24.
    Chatzipetrou, Panagiota
    et al.
    Örebro University, Sweden.
    Papatheocharous, Efi
    RISE - Research Institutes of Sweden, ICT, SICS.
    Wnuk, Krysztof
    Blekinge Institute of Technology, Sweden.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Alegroth, Emil
    Blekinge Institute of Technology, Sweden.
    Gorschek, Tony
    Blekinge Institute of Technology, Sweden.
    Component attributes and their importance in decisions and component selection2019Inngår i: Software quality journal, ISSN 0963-9314, E-ISSN 1573-1367, s. 1-27Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Component-based software engineering is a common approach in the development and evolution of contemporary software systems. Different component sourcing options are available, such as: (1) Software developed internally (in-house), (2) Software developed outsourced, (3) Commercial off-the-shelf software, and (4) Open-Source Software. However, there is little available research on what attributes of a component are the most important ones when selecting new components. The objective of this study is to investigate what matters the most to industry practitioners when they decide to select a component. We conducted a cross-domain anonymous survey with industry practitioners involved in component selection. First, the practitioners selected the most important attributes from a list. Next, they prioritized their selection using the Hundred-Dollar ($100) test. We analyzed the results using compositional data analysis. The results of this exploratory analysis showed that cost was clearly considered to be the most important attribute for component selection. Other important attributes for the practitioners were: support of the componentlongevity prediction, and level of off-the-shelf fit to product. Moreover, several practitioners still consider in-house software development to be the sole option when adding or replacing a component. On the other hand, there is a trend to complement it with other component sourcing options and, apart from cost, different attributes factor into their decision. Furthermore, in our analysis, nonparametric tests and biplots were used to further investigate the practitioners’ inherent characteristics. It seems that smaller and larger organizations have different views on what attributes are the most important, and the most surprising finding is their contrasting views on the cost attribute: larger organizations with mature products are considerably more cost aware.

  • 25.
    Cicchetti, Antonio
    et al.
    Mälardalen University, Sweden.
    Borg, Markus
    RISE., Swedish ICT, SICS, Security Lab.
    Sentilles, Severine
    Mälardalen University, Sweden.
    Wnuk, Krzysztof
    Blekinge Institute of Technology, Sweden.
    Carlsson, Jan
    Mälardalen University, Sweden.
    Papatheocharous, Efi
    RISE., Swedish ICT, SICS, Software and Systems Engineering Laboratory.
    Towards Software Assets Origin Selection Supported by a Knowledge Repository2016Inngår i: 2016 1st International Workshop on Decision Making in Software ARCHitecture (MARCH), 2016, 10, s. 22-29Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Software architecture is no more a mere system specification as resulting from the design phase, but it includes the process by which its specification was carried out. In this respect, design decisions in component-based software engineering play an important role: they are used to enhance the quality of the system, keep the current market level, keep partnership relationships, reduce costs, and so forth. For non trivial systems, a recurring situation is the selection of an asset origin, that is if going for in-house, outsourcing, open-source, or COTS, when in the need of a certain missing functionality. Usually, the decision making process follows a case-by-case approach, in which historical information is largely neglected. This solution avoids the overhead of keeping detailed documentation about past decisions, but hampers consistency among multiple, possibly related, decisions. The ORION project aims at developing a decision support framework in which historical decision information plays a pivotal role: it is used to analyse current decision scenarios, take well-founded decisions, and store the collected data for future exploitation. In this paper, we outline the potentials of such a knowledge repository, including the information it is intended to be stored in it, and when and how to retrieve it within a decision case.

  • 26.
    Cito, Jurgen
    et al.
    University of Zurich, Switzerland.
    Wettinger, Johannes
    University of Stuttgart, Germany.
    Lwakatare, Lucy
    University of Oulu, Finland.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Li, Fei
    Siemens AG, Austria.
    Feedback from operations to software development—a devops perspective on runtime metrics and logs2019Inngår i: Lect. Notes Comput. Sci., 2019, s. 184-195Konferansepaper (Fagfellevurdert)
    Abstract [en]

    DevOps achieve synergy between software development and operations engineers. This synergy can only happen if the right culture is in place to foster communication between these roles. We investigate the relationship between runtime data generated during production and how this data can be used as feedback in the software development process. For that, we want to discuss case study organizations that have different needs on their operations-to-development feedback pipeline, from which we abstract and propose a more general, higher-level feedback process. Given such a process, we discuss a technical environment required to support this process. We sketch out different scenarios in which feedback is useful in different phases of the software development life-cycle.

  • 27.
    de la Vara, José Luis
    et al.
    Carlos III University of Madrid, Spain.
    Borg, Markus
    RISE., Swedish ICT, SICS, Security Lab.
    Wnuk, Krzysztof
    Blekinge Institute of Technology, Sweden.
    Moonen, Leon
    Certus Centre for Software V&V, Norway.
    An Industrial Survey of Safety Evidence Change Impact Analysis Practice2016Inngår i: IEEE Transactions on Software Engineering, ISSN 0098-5589, E-ISSN 1939-3520, Vol. 42, nr 12, s. 1095-1117Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In many application domains, critical systems must comply with safety standards. This involves gathering safety evidence in the form of artefacts such as safety analyses, system specifications, and testing results. These artefacts can evolve during a system's lifecycle, creating a need for impact analysis to guarantee that system safety and compliance are not jeopardised. Although extensive research has been conducted on change impact analysis and on safety evidence management, the knowledge about how safety evidence change impact analysis is addressed in practice is limited. This paper reports on a survey targeted at filling this gap by analysing the circumstances under which safety evidence change impact analysis is addressed, the tool support used, and the challenges faced. We obtained 97 valid responses representing 16 application domains, 28 countries, and 47 safety standards. The results suggest that most practitioners deal with safety evidence change impact analysis during system development and mainly from system specifications. Furthermore, the level of automation in the process is low and insufficient tool support is the most frequent challenge. Other notable findings include that the different artefact types used as safety evidence seem to co-evolve, the evolution of safety case should probably be better managed, and no commercial impact analysis tool has been reported as used for all artefact types. Finally, we identified over 20 areas where the state of the practice in safety evidence change impact analysis can be improved.

  • 28.
    Helali Moghadam, Mahshid
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Saadatmand, Mehrdad
    RISE - Research Institutes of Sweden, ICT, SICS.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Bohlin, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Lisper, Björn
    Mälardalen University, Sweden.
    Adaptive Run-time 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.

  • 29.
    Helali Moghadam, Mahshid
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Saadatmand, Mehrdad
    RISE - Research Institutes of Sweden, ICT, SICS.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Bohlin, Markus
    RISE - Research Institutes of Sweden, 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.

  • 30.
    Helali Moghadam, Mahshid
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS.
    Saadatmand, Mehrdad
    RISE - Research Institutes of Sweden, ICT, SICS.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Bohlin, Markus
    RISE - Research Institutes of Sweden, 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.

  • 31.
    Helali Moghadam, Mahshid
    et al.
    RISE - Research Institutes of Sweden, ICT, SICS. Mälardalen University, Sweden.
    Saadatmand, Mehrdad
    RISE - Research Institutes of Sweden, ICT, SICS.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Bohlin, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Lisper, Björn
    Mälardalen University, Sweden.
    Machine Learning to Guide Performance Testing: An Autonomous Test Framework2019Inngår i: ICST Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems ITEQS'19, 2019, 2019Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Satisfying performance requirements is of great importance for performance-critical software systems. Performance analysis to provide an estimation of performance indices and ascertain whether the requirements are met is essential for achieving this target. Model-based analysis as a common approach might provide useful information but inferring a precise performance model is challenging, especially for complex systems. Performance testing is considered as a dynamic approach for doing performance analysis. In this work-in-progress paper, we propose a self-adaptive learning-based test framework which learns how to apply stress testing as one aspect of performance testing on various software systems to find the performance breaking point. It learns the optimal policy of generating stress test cases for different types of software systems, then replays the learned policy to generate the test cases with less required effort. Our study indicates that the proposed learning-based framework could be applied to different types of software systems and guides towards autonomous performance testing.

  • 32.
    Henriksson, Jens
    et al.
    Semcon AB, Sweden.
    Berger, Christian
    University of Gothenburg, Sweden; Chalmers Institute of Technology, Sweden.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Tornberg, Lars
    Volvo Cars, Sweden.
    Englund, Cristofer
    RISE - Research Institutes of Sweden, ICT, Viktoria.
    Sathyamoorthy, Sankar
    QRTech AB, Sweden.
    Ursing, Stig
    Semcon AB, Sweden.
    Towards Structured Evaluation of Deep Neural Network Supervisors2019Inngår i: Proceedings - 2019 IEEE International Conference on Artificial Intelligence Testing, AITest 2019, Institute of Electrical and Electronics Engineers Inc. , 2019, s. 27-34Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Deep Neural Networks (DNN) have improved the quality of several non-safety related products in the past years. However, before DNNs should be deployed to safety-critical applications, their robustness needs to be systematically analyzed. A common challenge for DNNs occurs when input is dissimilar to the training set, which might lead to high confidence predictions despite proper knowledge of the input. Several previous studies have proposed to complement DNNs with a supervisor that detects when inputs are outside the scope of the network. Most of these supervisors, however, are developed and tested for a selected scenario using a specific performance metric. In this work, we emphasize the need to assess and compare the performance of supervisors in a structured way. We present a framework constituted by four datasets organized in six test cases combined with seven evaluation metrics. The test cases provide varying complexity and include data from publicly available sources as well as a novel dataset consisting of images from simulated driving scenarios. The latter we plan to make publicly available. Our framework can be used to support DNN supervisor evaluation, which in turn could be used to motive development, validation, and deployment of DNNs in safety-critical applications.

  • 33.
    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.

  • 34.
    Jonsson, Leif
    et al.
    Linköping University, Sweden; Ericsson AB, Sweden.
    Borg, Markus
    RISE., Swedish ICT, SICS, Security Lab. Lund University, Sweden.
    Broman, David
    KTH Royal Institute of Technology, Sweden; UC Berkeley, US.
    Sandahl, Kristian
    Linköping University, Sweden.
    Eldh, Sigrid
    Ericsson AB, Sweden.
    Runeson, Per
    Lund University, Sweden.
    Automated Bug Assignment: Ensemble-based Machine Learning in Large Scale Industrial Contexts2016Inngår i: Journal of Empirical Software Engineering, ISSN 1382-3256, E-ISSN 1573-7616, Vol. 21, nr 4, s. 1533-1578Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Bug report assignment is an important part of software maintenance. In particular, incorrect assignments of bug reports to development teams can be very expensive in large software development projects. Several studies propose automating bug assignment techniques using machine learning in open source software contexts, but no study exists for large-scale proprietary projects in industry. The goal of this study is to evaluate automated bug assignment techniques that are based on machine learning classification. In particular, we study the state-of-the-art ensemble learner Stacked Generalization (SG) that combines several classifiers. We collect more than 50,000 bug reports from five development projects from two companies in different domains. We implement automated bug assignment and evaluate the performance in a set of controlled experiments. We show that SG scales to large scale industrial application and that it outperforms the use of individual classifiers for bug assignment, reaching prediction accuracies from 50 % to 89 % when large training sets are used. In addition, we show how old training data can decrease the prediction accuracy of bug assignment. We advice industry to use SG for bug assignment in proprietary contexts, using at least 2,000 bug reports for training. Finally, we highlight the importance of not solely relying on results from cross-validation when evaluating automated bug assignment.

  • 35.
    Larsson, Jacob
    et al.
    Capgemini, Sweden.
    Borg, Markus
    RISE., Swedish ICT, SICS, Security Lab.
    Olsson, Thomas
    RISE - Research Institutes of Sweden, ICT, SICS.
    Testing Quality Requirements of a System-of-Systems in the Public Sector - Challenges and Potential Remedies2016Inngår i: CEUR Workshop Proceedings: Joint Proceedings of the REFSQ 2016 Co-Located Events, 2016, 8, Vol. 1564Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Quality requirements is a difficult concept in software projects, and testing software qualities is a well-known challenge. Without proper management of quality requirements, there is an increased risk that the software product un-der development will not meet the expectations of its future users. In this pa-per, we share experiences from testing quality requirements when developing a large system-of-systems in the public sector in Sweden. We complement the experience reporting by analyzing documents from the case under study. As a final step, we match the identified challenges with solution proposals from the literature. We report five main challenges covering inadequate re-quirements engineering and disconnected test managers. Finally, we match the challenges to solutions proposed in the scientific literature, including in-tegrated requirements engineering, the twin peaks model, virtual plumblines, the QUPER model, and architecturally significant requirements. Our experi-ences are valuable to other large development projects struggling with testing of quality requirements. Furthermore, the report could be used by as input to process improvement activities in the case under study.

  • 36.
    Modeus, Gabriel
    et al.
    Swedsoft, Sweden.
    Sandgren, Patrik
    Teknikföretagen, Sweden.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Andersson, Frida
    Teknikföretagen, Sweden.
    Wiel-Berggren, Gustav
    Teknikföretagen, Sweden.
    Rosendahl, Maria
    Teknikföretagen, Sweden.
    Mjukvara är Sveriges nya infrastruktur: här är nästa steg2019Rapport (Annet vitenskapelig)
    Abstract [en]

    I Sverige bedriver hela 35 procent av företagen egen mjukvaruutveckling.1 Data och mjukvarahar kommit att genomsyra i stort sett hela näringslivet och den offentliga sektorn – både iden operativa driften, men även i utvecklings- och innovationsarbetet.Det här är en utveckling som har gått mycket snabbt, vilket illustreras väl av att utgifter förmjukvara hos företag i Sverige har fördubblats från 25 miljarder kr år 2014 till 50 miljarder kr år2019.2 Men samtidigt som digitaliseringen accelererar och efterfrågan på mjukvaruutvecklingoch nya datatjänster blir allt större så kräver en fortsatt hög innovationstakt att lagstiftningenoch utbildningsväsendet anpassar sig efter det fält där en allt större del av svensk tillväxt skapas

  • 37.
    Trubiani, Catia
    et al.
    Gran Sasso Science Institute, Italy.
    Jamshidi, Pooyan
    University of South Carolina, USA.
    Cito, Jurgen
    Massachusetts Institute Technology, USA.
    Shang, Weiyi
    Concordia University, Canada.
    Jiang, Zhen Ming
    York University, Canada.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Performance Issues?: Hey DevOps, Mind the Uncertainty!2019Inngår i: IEEE Software, ISSN 0740-7459, E-ISSN 1937-4194, Vol. 36, nr 2, s. 110-117, artikkel-id 8501933Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    DevOps is a novel trend that aims to bridge the gap between software development and operation teams. When applied to the performance evaluation process, it brings new challenges since developers need to be aware of the deployment settings and application runtime characteristics. At the operational stage, several uncertainties, e.g., workload fluctuations and resource availability, may affect the performance analysis. The goal of this paper is to identify the uncertain parameters and quantify their propagation to performance analysis results, in order to bring upfront the main system criticisms. To this end, we make use of a popular big data system showing that the sources of uncertainty may span on different characteristics and the performance analysis results can be heavily affected by these uncertainties. The paper contributes as an experience report aiming to better identify performance uncertainties through a case study. It provides a step-by-step guide to practitioners for controlling system uncertainties.

  • 38.
    Vercammen, Sten
    et al.
    University Antwerpen, Belgium.
    Demeyer, Serge
    University Antwerpen, Belgium.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Eldh, Sigrid
    Ericsson AB, Sweden.
    Speeding Up Mutation Testing via the Cloud: Lessons Learned for Further Optimisations2018Inngår i: Proceedings of the 12th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, 2018, artikkel-id 26Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Background: Mutation testing is the state-of-the-art technique for assessing the fault detection capacity of a test suite. Unfortunately, it is seldom applied in practice because it is computationally expensive. We witnessed 48 hours of mutation testing time on a test suite comprising 272 unit tests and 5,258 lines of test code for testing a project with 48,873 lines of production code. Aims: Therefore, researchers are currently investigating cloud solutions, hoping to achieve sufficient speed-up to allow for a complete mutation test run during the nightly build. Method: In this paper we evaluate mutation testing in the cloud against two industrial projects. Results: With our proof-of-concept, we achieved a speed-up between 12x and 12.7x on a cloud infrastructure with 16 nodes. This allowed to reduce the aforementioned 48 hours of mutation testing time to 3.7 hours. Conclusions: We make a detailed analysis of the delays induced by the distributed architecture, point out avenues for further optimisation and elaborate on the lessons learned for the mutation testing community. Most importantly, we learned that for optimal deployment in a cloud infrastructure, tasks should remain completely independent. Mutant optimisation techniques that violate this principle will benefit less from deploying in the cloud.

  • 39.
    Vercammen, Sten
    et al.
    University of Antwerp, Belgium.
    Ghafari, Mohammad
    University of Bern, Switzerland.
    Demeyer, Serge
    University of Antwerp, Belgium.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Goal-oriented Mutation Testing with Focal Methods2018Inngår i: Proceedings of the 9th ACM SIGSOFT International Workshop on Automating TEST Case Design, Selection, and Evaluation, 2018, s. 23-30Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Mutation testing is the state-of-the-art technique for assessing the fault-detection capacity of a test suite. Unfortunately, mutation testing consumes enormous computing resources because it runs the whole test suite for each and every injected mutant. In this paper we explore fine-grained traceability links at method level (named focal methods), to reduce the execution time of mutation testing and to verify the quality of the test cases for each individual method, instead of the usually verified overall test suite quality. Validation of our approach on the open source Apache Ant project shows a speed-up of 573.5x for the mutants located in focal methods with a quality score of 80%.

  • 40.
    Wnuk, K.
    et al.
    Blekinge Institute of Technology, Sweden.
    Borg, Markus
    RISE - Research Institutes of Sweden, ICT, SICS.
    Gorschek, T.
    Blekinge Institute of Technology, Sweden.
    Towards new ways of evaluating methods of supporting requirements management and traceability using signal-to-noise ratio2019Inngår i: ENASE 2019 - Proceedings of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering, SciTePress , 2019, s. 330-339Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Developing contemporary software solutions requires many processes and people working in synergy to achieve a common goal. Any misalignment between parts of the software production cycle can severely impede the quality of the development process and its resulting products. In this paper, we focus on improving means for measuring the quality of methods used to support finding similarities between software product artifacts, especially requirements. We propose a new set of measures, Signal-to-Noise ratios which extends the commonly used precision and recall measures. We test the applicability of all three types of SNR on two methods for finding similar requirements: the normalized compression distance (NCD) originating from the domain of information theory, and the Vector Space Model originating from computer linguistics. The results obtained present an interesting property of all types of SNR, all the values are centered around 1 which confirms our hypothesis that the analyzed methods can only limit the search space for the analysis. The analyst may still have difficulties in manually assessing the correct links among the incorrect ones.

  • 41.
    Wnuk, Krzysztof
    et al.
    Blekinge Institute of Technology, Sweden.
    Borg, Markus
    RISE., Swedish ICT, SICS, Security Lab.
    Muhammad Sulaman, Sardar
    Lund University, Sweden.
    An Industrial Case Study on Measuring the Quality of the Requirements Scoping Process2016Inngår i: Product-Focused Software Process Improvement / [ed] Pekka Abrahamsson, Andreas Jedlitschka, Anh Nguyen Duc, Michael Felderer, Sousuke Amasaki, Tommi Mikkonen, 2016, Vol. 10027, s. 487-494Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Decision making and requirements scoping occupy central roles in helping to develop products that are demanded by the customers and ensuring company strategies are accurately realized in product scope. Many companies experience continuous and frequent scope changes and fluctuations but struggle to measure the phenomena and correlate the measurement to the quality of the requirements process. We present the results from an exploratory interview study among 22 participants working with requirements management processes at a large company that develops embedded systems for a global market. Our respondents shared their opinions about the current set of requirements management process metrics as well as what additional metrics they envisioned as useful. We present a set of metrics that describe the quality of the requirements scoping process. The findings provide practical insights that can be used as input when introducing new measurement programs for requirements management and decision making.

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