Preprints of my papers are available below, as well as presentation slides and data. Please refer to my Google Scholar Profile for an easily browsable publication overview.
The following papers are currently in my publication pipeline:
In Preparation: - A paper on truck factors in closed-source software - A comparative study on technical debt metrics Under Review: - A paper on the value of software quality Under Revision: - A longitudinal evaluation of automated issue assignment at Ericsson. In Print: -
Book chapters
M. Borg and P. Runeson. Changes, Evolution and Bugs – Recommendation Systems for Issue Management, In R. Robillard, W. Maalej, R. Walker, and T. Zimmermann (Eds.), Recommendation Systems in Software Engineering, pp. 407-509, Springer, 2014. (link, preprint)
Journal papers
[J24] S. Vercammen, S. Demeyer, M. Borg, N. Pettersson, and G. Hedin. Mutation Testing Optimisations Using the Clang Front-end, Journal of Software: Testing, Verification, and Reliability, 34(1), 2024. (open access)
[J23] M. Helali Moghadam, M. Borg, M. Saadatmand, S. Jalaleddin Mousavirad, M. Bohlin, and B. Lisper. Machine Learning Testing in an ADAS Case Study Using Simulation-Integrated Bio-Inspired Search-Based Testing, Journal of Software: Evolution and Process, early access, 2023. (open access)
[J22] S. Vercammen, S. Demeyer, and M. Borg. F-ASTMut Mutation Optimisations Techniques Using the Clang Front-End, Software Impacts, 2023. (open access)
[J21] M. Borg, J. Henriksson, K. Socha, O. Lennartsson, E. Sonnsjö Lönegren, T. Bui, P. Tomaszewski, S. Raman Sathyamoorthy, S. Brink, and M. Helali Moghadam. SMIRK: A Machine Learning-Based Pedestrian Automatic Emergency Braking System with a Complete Safety Case, Software Quality Journal, 2023. (open access)
[J20] M. Röding, P. Tomaszewski, S. Yu, M. Borg, and J. Rönnols. Machine Learning-Accelerated Small-Angle X-ray Scattering Analysis of Disordered Two- and Three-Phase Materials, Frontiers in Materials, Sec. Computational Materials Science, 2022. (open access)
[J19] K. Socha, M. Borg, and J. Henriksson. SMIRK: A Machine Learning-Based Pedestrian Automatic Emergency Braking System with a Complete Safety Case, Software Impacts, Volume 13, 2022. (open access)
[J18] C. Wohlin, E. Papatheocharous, J. Carlson, K. Petersen, E. Alégroth, J. Axelsson, D. Badampudi, M. Borg, A. Cicchetti, F. Ciccozzi, T. Olsson, S. Sentilles, M. Svahnberg, K. Wnuk, and T. Gorschek. Towards Evidence‐Based Decision‐Making for Identification and Usage of Assets in Composite Software: A Research Roadmap, Journal of Software: Evolution and Process, 2021. (open access)
[J17] M. Helali Moghadam, M. Saadatmand, M. Borg, M. Bohlin, and B. Lisper. An Autonomous Performance Testing Framework using Self-Adaptive Fuzzy Reinforcement Learning, Software Quality Journal, 30(1), pp. 127-159, 2022. (open access)
[J16] J. Henriksson, C. Berger, M. Borg, L. Tornberg, S. Sathyamoorthy, C. Englund. Performance Analysis of Out-of-Distribution Detection on Trained Neural Networks, Information and Software Technology, Volume 130, 2021. (link)
[J15] M. Borg, V. Garousi, A. Mahmoud, T. Olsson, and O. Stålberg. Video Game Development in a Rush: A Survey of the Global Game Jam Participants, IEEE Transactions on Games, 12(3), September 2020. (link, preprint)
[J14] V. Garousi, M. Borg, and M. Oivo. Practical Relevance of Software Engineering Research: Synthesizing the Debate, Empirical Software Engineering, 25, pp. 1687-1754, 2020. (open access)
[J13] P. Chatzipetrou, E. Papatheocharous, K. Wnuk, M. Borg, E. Alégroth, and T. Gorschek. Component Attributes and Their Importance in Decisions and Component Selection, Software Quality Journal, September 2019. (open access)
[J12] M. Borg, P. Chatzipetrou, K. Wnuk, E. Alégroth, T. Gorschek, E. Papatheocharous, S. Shah, and J. Axelsson. Selecting Component Sourcing Options: A Survey of Software Engineering’s Broader Make-or-Buy Decisions, Information and Software Technology, Volume 112, pp. 18-34, 2019. (Journal first presentation at ICSME’20) (link, video)
[J11] M. Borg, C. Englund, K. Wnuk, B. Duran, C. Levandowski, S. Gao, Y. Tan, H. Kaijser, H. Lönn, and J. Törnqvist. Safely Entering the Deep: A Review of Verification and Validation for Machine Learning and a Challenge Elicitation in the Automotive Industry, Journal of Automotive Software Engineering, 1(1), pp. 1-19, 2019. (open access)
[J10] C. Trubiani, P. Jamshidi, J. Cito, W. Shang, Z. Jiang, M Borg. Performance Issues? Hey DevOps, Mind the Uncertainty!, IEEE Software, 36(2), pp. 110-117, 2016. (Journal first presentation at FSE’19) (link, preprint)
[J9] M. Borg, K. Wnuk, B. Regnell, and P. Runeson. Supporting Change Impact Analysis Using a Recommendation System: An Industrial Case Study in a Safety-Critical Context, IEEE Transactions on Software Engineering, 43(6), pp. 675-700, 2017. (Journal first presentation at ICSE’17) (link, preprint, slides)
[J8] J. de la Vara, M. Borg, K. Wnuk, and L. Moonen. An Industrial Survey of Safety Evidence Change Impact Analysis Practice, IEEE Transactions on Software Engineering, 42(12), pp. 1095-1117, 2016. (link, preprint)
[J7] E. Bjarnason, M. Unterkalmsteiner, M. Borg, and E. Engström. A Multi-Case Study of Agile Requirements Engineering and the Use of Test Cases as Requirements, Information and Software Technology, 77, pp. 61-79, 2016. (link, preprint)
[J6] M. Borg. TuneR: A Framework for Tuning Software Engineering Tools with Hands-On Instructions in R, Journal of Software: Evolution and Process, 28(6), pp. 427–459, 2016. (link, preprint, data)
[J5] L. Jonsson, M. Borg, D. Broman, K. Sandahl, S. Eldh, and P. Runeson. Automated Bug Assignment: Ensemble-based Machine Learning in Large Scale Industrial Contexts, Empirical Software Engineering, 21(4), pp. 1533-1578, 2016. (link, preprint)
[J4] S. Assar, M. Borg, and D. Pfahl. Using Text Clustering to Predict Defect Resolution Time: A Conceptual Replication and an Evaluation of Prediction Accuracy, Empirical Software Engineering, 21(4), pp. 1437-1475, 2016. (link, preprint)
[J3] M. Borg, P. Runeson, and A. Ardö. Recovering from a Decade: A Systematic Mapping of Information Retrieval Approaches to Software Traceability, Empirical Software Engineering, 19(6), pp. 1565-1616, 2014. (link, preprint, data)
[J2] E. Bjarnason, P. Runeson, M. Borg, M. Unterkalmsteiner, E. Engström, B. Regnell, G. Sabaliauskaite, A. Loconsole, T. Gorschek, and R. Feldt. Challenges and Practices in Aligning Requirements with Verification and Validation: A Case Study of Six Companies, Empirical Software Engineering, 19(6), pp. 1809-1855, 2014. (link, preprint)
[J1] M. Borg, J. Kembro, J. Notander, C. Petersson, and L. Ohlsson. Conflict Management in Student Groups – a Teacher’s Perspective in Higher Education, Högre Utbildning, 1(2), pp. 111-124, 2011. (open access)
Conference papers
[C38] J. Henriksson, C. Berger, S. Ursing, and M. Borg. Evaluation of Out-of-Distribution Detection Performance on Autonomous Driving Datasets, In Proc. of the IEEE International Conference on Artificial Intelligence Testing (AITest), 2023.
[C37] H. Heyn, K. Habibullah, E. Knauss, J. Horkoff, M. Borg, A. Knauss, and P. Li. Automotive Perception Software Development: An Empirical Investigation into Data, Annotation, and Ecosystem Challenges, In Proc. of the 2nd International Conference on AI Engineering – Software Engineering for AI (CAIN2023).
[C36] K. Habibullah, H. Heyn, G. Gay, J. Horkoff, E. Knauss, M. Borg, A. Knauss, H. Sivencrona, and P. Li. Requirements Engineering for Automotive Perception Systems: An Interview Study, In Proc. of the 29th International Working Conference on Requirements Engineering: Foundation for Quality (REFSQ2023), 2023.
[C35] A. Tornhill and M. Borg. Code Red: The Business Impact of Code Quality – A Quantitative Study of 39 Proprietary Production Codebases, In Proc. of the 5th International Conference on Techincal Debt (TechDebt2022), pp. 11-22, 2022 (link, preprint) (acceptance rate 40.7%)
[C34] M. Borg, J. Bengtsson, H. Österling, A. Hagelborn, I. Gagner, and P. Tomaszewski. Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice, In Proc. of the 1st International Conference on AI Engineering – Software Engineering for AI (CAIN), pp. 22-32, 2022 (link, preprint) (acceptance rate 31.8%)
[C33] Q. Song, M. Borg, E. Engström, H. Ardö, and S. Rico. Exploring ML Testing in Practice – Lessons Learned from an Interactive Rapid Review with Axis Communications, In Proc. of the 1st International Conference on AI Engineering – Software Engineering for AI (CAIN), pp. 10-21, 2022 (link, preprint) (acceptance rate 31.8%)
[C32] H. Ebadi, M. Helali Moghadam, M. Borg, G. Gay, A. Fontes, and K. Socha. Efficient and Effective Generation of Test Cases for Pedestrian Detection – Search-based Software Testing of Baidu Apollo in SVL, In Proc. of the IEEE International Conference on Artificial Intelligence Testing (AITest), pp. 103-110, 2021. (link)
[C31] S. Nilsson Tengstrand, P. Tomaszewski, M. Borg, R. Jabangwe. Challenges of Adopting SAFe in the Banking Industry – A Study Two Years after its Introduction, In Proc. of the International Conference on Agile Software Development (XP), 2021 (open access) (acceptance rate 28.9%)
[C30] M. Borg, R. Ben Abdessalem, S. Nejati, F. Jegeden, and D.Shin. , In Proc. of the 14th International Conference on Software Testing, Verification and Validation, 2021. (preprint, slides)
[C29] O. Werneman, M. Borg, and D. Hansson. Supporting Root Cause Analysis of Inaccurate Bug Prediction Based on Machine Learning – Lessons Learned When Interweaving Training Data and Source Code, In Proc. of the Design and Verification Conference & Exhibition (DVCon) 2021.
[C28] M. Borg. The AIQ Meta-Testbed: Pragmatically Bridging Academic AI Testing and Industrial Q Needs, In Proc. of the International Conference on Software Quality, SWQD 2021: Software Quality: Future Perspectives on Software Engineering Quality, 2021. (link, preprint)
[C27] M. Borg. Making Lab Sessions Mandatory – On Student Work Distribution in a Gamified Project Course on Market-Driven Software Engineering, In Proc. of the 32nd International Conference on Software Engineering Education and Training (CSEE&T), 2020. (link, preprint, code) (Acceptance rate 37%)
[C26] T. Olsson, M. Hell, M. Höst, U. Franke, and M. Borg. Sharing of Vulnerability Information Among Companies – A Survey of Swedish Companies, In Proc. of the 45th Euromicro Conference on Software Engineering and Advanced Applications, 2019. (link, preprint)
[C25] J. Henriksson, C. Berger, M. Borg, L. Tornberg, S. Sathyamoorthy, and C. Englund. Performance Analysis of Out-of-Distribution Detection on Various Trained Neural Networks, In Proc. of the 45th Euromicro Conference on Software Engineering and Advanced Applications, 2019. (link) (distinguished paper award)
[C24] K. Wnuk, M. Borg, and T. Gorschek. Towards New Ways of Evaluating Methods of Supporting Requirements Management and Traceability using Signal-to-Noise Ratio. In Proc. of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering, 2019. (link, preprint)
[C23] J. Henriksson, C. Berger, M. Borg, L. Tornberg, C. Englund, S. Sathyamoorthy, and S. Ursing. Towards Structured Evaluation of Deep Neural Network Supervisors, In Proc. of the 1st IEEE International Conference on Artificial Intelligence Testing (AITest), pp. 27-34, 2019. (link, preprint)
[C22] M. Borg, A. Brytting, and D. Hansson. Enabling Visual Design Verification Analytics – From Prototype Visualizations to an Analytics Tool using the Unity Game Engine. In Proc. of the Design and Verification Conference Europe (DVCon EU), Munich, Germany, 2018. (preprint, slides)
[C21] S. Vercammen, S. Demeyer, M. Borg, and S. Eldh. Speeding up Mutation Testing via the Cloud: Lessons Learned for Further Optimisations, In Proc. of the 12th International Symposium on Empirical Software Engineering and Measurement, p. 26, 2018. (link, preprint) (Acceptance rate 18.3%)
[C20] P. Chatzipetrou, E. Alégroth, E. Papatheocharous, M. Borg, T. Gorschek, and K. Wnuk. Component Selection in Software Engineering – Which Attributes Are the Most Important in the Decision Process?, In Proc. of the 44th Euromicro Conference on Software Engineering and Advanced Applications, 2018. (distinguished paper award) (link, preprint)
[C19] M. Borg, T. Olsson, U. Franke, and S. Assar. Digitalization of Swedish Government Agencies – A Perspective Through the Lens of a Software Development Census, In Proc. of the 40th International Conference on Software Engineering Companion (SEIS Track), 2018. (link, preprint, report) (Acceptance rate 35.5%)
[C18] M. Moghadam, M. Saadatmand, M. Borg, M. Bohlin, and B. Lisper. Adaptive Runtime Response Time Control in PLC-based Real-Time Systems using Reinforcement Learning, In Proc. of the 13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, 2018. (link, preprint) (Acceptance rate 27.8%)
[C17] M. Borg, A. Brytting, and D. Hansson. An Analytical View of Test Results Using CityScapes. In Proc. of the Design and Verification Conference US (DVCon US), San Jose, CA, US, 2018. (related blog post) (preprint)
[C16] M. Borg, T. Ohlsson, and J. Svensson. Piggybacking on an Autonomous Hauler: Business Models Enabling a System-of-Systems Approach to Mapping an Underground Mine, In Proc. of the 25th IEEE Requirements Engineering Conference, pp. 372-381, 2017. (link, preprint) (Acceptance rate 36.7%)
[C15] M. Borg, I. Lennerstad, R.Ros, and E. Bjarnason. On Using Active Learning and Self-Training when Mining Performance Discussions on Stack Overflow, In Proc. of the 21th Evaluation and Assessment in Software Engineering Conference, pp. 308-313, 2017. (link, preprint) (Acceptance rate 36%)
[C14] M. Borg, E. Alégroth, and P. Runeson. Software Engineers’ Information Seeking Behavior in Change Impact Analysis – An Interview Study, In Proc. of the 25th International Conference on Program Comprehension, pp. 12-22, 2017. (link, preprint) (Acceptance rate 30.6%)
[C13] K. Wnuk, M. Borg, and S. Sulaman. An Industrial Case Study on Measuring the Quality of the Requirements Scoping Process, In Proc. of the 17th International Conference on Product-Focused Software Process Improvement (PROFES), pp. 487-494, 2016. (link, preprint)
[C12] E. Bjarnason, M. Borg, and B. Lindvall. Supervising for Independence – A Case Study on Master Science Projects in Higher Education, In Proc. of LU:s femte högskolepedagogiska utvecklingskonferens, 2015.
[C11] E. Bjarnason, M. Unterkalmsteiner, E. Engström, and M. Borg. An Industrial Case Study on Test Cases as Requirements, In Proc. of the 16th International Conference on Agile Software Development, pp. 27-39, 2015. (best paper nominee) (link, preprint)
[C10] N. Erman, V. Tufvesson, M. Borg, P. Runeson, and A. Ardö. Navigating Information Overload Caused by Automated Testing – A Clustering Approach in Multi-Branch Development, In Proc. of the 8th International Conference on Software Testing, Verification and Validation, pp. 1-9, 2015. (link, preprint)
[C9] M. Borg, P. Runeson, J. Johansson, and M. Mäntylä. A Replicated Study on Duplicate Detection: Using Apache Lucene to Search Among Android Defects, In Proc. of the 8th International Symposium on Empirical Software Engineering and Measurement, pp. 8:1-8:4, 2014. (link, preprint, data)
[C8] E. Engström, M. Mantylä, P. Runeson, and M. Borg. Supporting Regression Test Scoping with Visual Analytics, In Proc. of the 7th International Conference on Software Testing, Verification and Validation, pp. 283-292, 2014.
[C7] S. Sulaman Muhammad, A. Orucevic-Alagic, M. Borg, K. Wnuk, M. Höst, and J. de la Vara. Development of Safety-Critical Software Systems Using Open Source Software – A Systematic Map, In Proc. of the Euromicro Conference on Software Engineering and Advanced Applications, pp. 17-24, 2014.
[C6] M. Borg, D. Pfahl, and P. Runeson. Analyzing Networks of Issue Reports, In Proc. of the 17th European Conference on Software Maintenance and Reengineering, pp. 79-88, 2013. (Acceptance rate 36%) (link, preprint, data)
[C5] M. Borg and P. Runeson. IR in Software Traceability: From a Bird’s Eye View, In Proc. of the International Symposium on Empirical Software Engineering and Measurement, pp. 243-246, 2013. (link, preprint)
[C4] M. Borg. Findability through Traceability: A Realistic Application of Candidate Trace Links? In Proc. of the 7th International Conference on Evaluating Novel Approaches to Software Engineering, pp. 173-181, 2012. (Acceptance rate 20%)
[C3] M. Borg, P. Runeson, and L. Brodén. Evaluation of Traceability Recovery in Context: A Taxonomy for Information Retrieval Tools, In Proc. of the 16th International Conference on Evaluation & Assessment in Software Engineering, pp. 111-120, 2012. (Acceptance rate 31%)
[C2] M. Borg, K. Wnuk, and D. Pfahl. Industrial Comparability of Student Artifacts in Traceability Recovery Research – An Exploratory Survey, In Proc. of the 16th European Conference on Software Maintenance and Reengineering, pp. 181-190, 2012. (Acceptance rate 27.8%)
[C1] M. Borg. Time Extraction from Real-time Generated Football Reports, In Proc. of the 16th Nordic Conference of Computational Linguistics, pp. 37-43, 2007. (link, preprint)
Workshop papers
[W22] M. Borg, A. Tornhill, and E. Mones. U Owns the Code That Changes and How Marginal Owners Resolve Issues Slower in Low-Quality Source Code, In Proc. of the 27th International Conference on Evaluation and Assessment in Software Engineering, EASIER Track, (link, preprint)
[W21] P. Tomaszewski, S. Yu, M. Borg, and J. Rönnols. Machine Learning-Assisted Analysis of Small Angle X-ray Scattering, In Proc. of the 2021 Swedish Workshop on Data Science (SweDS), pp. 1-6, 2021. (link, preprint) (Best Paper Award)
[W20] M. Borg, J. Bronson, L. Christensson, F. Olsson, O. Lennartsson, E. Sonnsjö, H. Ebadi, and M. Karsberg. Exploring the Assessment List for Trustworthy AI in the Context of Advanced Driver-Assistance Systems, In Proc. of the 2nd Workshop on Ethics in Software Engineering Research and Practice (SEthics), 2021. (preprint)
[W19] M. Borg, R. Jabangwe, S. Åberg, A. Ekblom, L. Hedlund, and A. Lidfeldt.Test Automation with Grad-CAM Heatmaps – A Future Pipe Segment in MLOps for Vision AI?, In Proc. of the 1st International Workshop on DevOps Testing for Cyber-Physical Systems, 2021. (link, preprint, slides)
[W18] A. Lidfeldt, D. Isaksson, L. Hedlund, S. Åberg, M. Borg, E. Larsson. Enabling Image Recognition on Constrained Devices Using Neural Network Pruning and a CycleGAN, In Proc. of the 10th International Conference on the Internet of Things Companion, 2020. (link, preprint, code)
[W17] M. Borg, J. Wernberg, T. Olsson, U. Franke, and M. Andersson. Illuminating a Blind Spot in Digitalization – Software Development in Sweden’s Private and Public Sector, In Proc. of the 1st International Workshop on Governance in Software Engineering, 2020. (preprint)
[W16] A. Vogelsang and M. Borg. Requirements Engineering for Machine Learning: Perspectives from Data Scientists, In Proc. of the 6th International Workshop on Artificial Intelligence for Requirements Engineering (AIRE), 2019. (link, preprint)
[W15] M. Borg, O. Svensson, K. Berg, and D. Hansson. SZZ Unleashed: An Open Implementation of the SZZ Algorithm – Featuring Example Usage in a Study of Just-in-Time Bug Prediction for the Jenkins Project, In Proc. of the Workshop on Machine Learning Techniques for Software Quality Evolution (MaLTeSQuE), pp. 7-12, 2019. (link, preprint, code, slides)
[W14] M. Helali Moghadam, M. Saadatmand, M. Borg, M. Bohlin, and B. Lisper. Machine Learning to Guide Performance Testing: An Autonomous Test Framework. In Proc. of the International Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems, 2019. (link, preprint)
[W13] J. Cito, J. Wettinger, L. Lwakatare, M. Borg, and F. Li. Feedback from Operations to Software Development – A DevOps Perspective on Runtime Metrics and Logs, In Bruel et al. (Eds.), Software Engineering Aspects of Continuous Development and New Paradigms of Software Production and Deployment (DEVOPS 2018), pp. 184-195, 2019 (link, preprint)
[W12] S. Vercammen, M. Ghafari, S. Demeyer, and M. Borg. Goal-Oriented Mutation Testing with Focal Methods, In Proc. of the 9th ACM SIGSOFT International Workshop on Automating TEST Case Design, Selection, and Evaluation, 2018. (link, preprint)
[W11] M. Moghadam, M. Saadatmand, M. Borg, M. Bohlin, and B. Lisper. Learning-based Response Time Analysis in Real-Time Embedded Systems: A Simulation-based Approach, In Proc. of the 1st International Workshop on Software Qualities and their Dependencies, 2018. (link, preprint)
[W10] J. Henriksson, M. Borg, and C. Englund. Automotive Safety and Machine Learning: Initial Results from a Study on How to Adapt the ISO 26262 Safety Standard, In Proc. of the 1st Software Engineering for AI in Autonomous Systems, 2018. (link, preprint)
[W9] M. Moghadam, M. Saadatmand, M. Borg, M. Bohlin, and B. Lisper. Learning-Based Self-Adaptive Assurance of Timing Properties in a Real-Time Embedded System, In Proc. of the 2nd International Workshop on Testing Extra-Functional Properties and Quality Characteristics of Software Systems, 2018. (link, preprint)
[W8] M. Borg, J.-L. de la Vara, and K. Wnuk. Practitioners’ Perspectives on Change Impact Analysis for Safety-Critical Software – A Preliminary Analysis, In Proc. of the 5th International Workshop on Next Generation of System Assurance Approaches for Safety-Critical Systems, pp. 346-358, 2016. (link, preprint)
[W7] A. Cicchetti, M. Borg, S. Sentilles, K. Wnuk, J. Carlsson, and E. Papatheocharous. Towards Software Assets Origin Selection Supported by a Knowledge Repository, In Proc. of the 1st International Workshop on decision Making in Software ARCHitecture (MARCH2016), pp. 22-29, 2016. (link, preprint)
[W6] J. Larsson, M. Borg, and T. Olsson. Testing Quality Requirements of a System-of-Systems in the Public Sector – Challenges and Potential Remedies, In Proc. of the 3rd International Workshop on Requirements Engineering and Testing, 2016. (link, preprint)
[W5] J. Larsson, and M. Borg. Revisiting the Challenges in Aligning RE and V&V: Experiences from the Public Sector, In Proc. of the 1st International Workshop on Requirements Engineering and Testing, pp. 4-11. 2014.
[W4] M. Borg, O. Gotel, and K. Wnuk. Enabling Traceability Reuse for Impact Analyses: A Feasibility Study in a Safety Context, In Proc. of the 7th International Workshop on Traceability in Emerging Forms of Software Engineering, pp. 72-79, 2013.
[W3] D. Callele, K. Wnuk, and M. Borg. Confounding Factors when Conducting Industrial Replications in Requirements Engineering, In Proc. of the 1st International Workshop on Conducting Empirical Studies in Industry, pp. 55-58, 2013.
[W2] K. Wnuk, M. Borg, and S. Assar. Towards Scalable Information Modeling of Requirements Architectures, In Proc. of the 1st International Workshop on Modeling for Data-Intensive Computing, pp. 141-150, 2012.
[W1] M. Borg and D. Pfahl. Do Better IR Tools Improve the Accuracy of Engineers’ Traceability Recovery?, In Proc. of the International Workshop on Machine Learning Technologies in Software Engineering, pp. 27-34, 2011. (preprint)
Other publications
[31] M. Borg, E. Aasa, K. Etemadi, and M. Monperrus. Human, What Must I Tell You?, IEEE Software, 40(3), pp. 9-14, 2023. (blog, link)
[30] M. Borg. Requirements on Technical Debt: Dare to Specify Them!, IEEE Software, 40(2), pp. 8-12, 2023. (blog, link)
[29] M. Borg. Pipeline Infrastructure Required to Meet the Requirements on AI, IEEE Software, 40(1), pp. 18-22, 2023. (blog, link)
[28] B. Scharinger, M. Borg, A. Vogelsang, and T. Olsson. Can RE Help Better Prepare Industrial AI for Commercial Scale?, IEEE Software, 39(6), pp. 8-12, 2022. (blog, link)
[27] S. Gregory and M. Borg. Looking Back, Moving Forward: A Handover, IEEE Software, 39(5), pp. 17-20, 2022. (link)
[26] M. Borg. Agility in Software 2.0 – Notebook Interfaces and MLOps with Buttresses and Rebars, LASD22 Keynote address, In Proc. of the 6th International Conference on Lean and Agile Software Development, 2022. (link, preprint)
[25] M. Borg. Using Search-Based Software Testing to Guide the Strive for Robust Machine Learning Components: Lessons Learned Across Systems and Simulators in the Mobility Domain, ITEQS22 Keynote address, In Proc. of the International Conference on Software Testing, Verification and Validation Workshops, 2022. (link)
[24] M. Borg, L. Jonsson, E. Engström, B. Bartalos, and A. Szabo. Adopting Automated Bug Assignment in Practice – A Registered Report of an Industrial Case Study, Accepted at the 15th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, 2021. (link)
[23] M. Helali Moghadam, M. Borg, and S. Jalaleddin Mousavirad. Deeper at the SBST 2021 Tool Competition: ADAS Testing Using Multi-Objective Search, In Proc. of the 14th International Workshop on Search-Based Software Testing, 2021. (link)
[22] M. Helali Moghadam, M. Saadatmand, M. Borg, M. Bohlin, and B. Lisper. Poster: Performance Testing Driven by Reinforcement Learning, In Proc. of the IEEE 13th International Conference on Software Testing, Validation and Verification, 2020. (link)
[21] A. Lidfeldt, M. Borg, and J. Bronson. AI Market Survey: Current State of AI in the Øresund Region Private Sector, Technical Report 104, Dept. of Computer Science, Lund University, 2020. (open access)
[20] M. Helali Moghadam, M. Saadatmand, M. Borg, M. Bohlin, B. Lisper. Performance Testing Driven by Reinforcement Learning, Poster publication, In Proc. of the 13th IEEE Conference on Software Testing, Validation and Verification, 2020.
[19] M. Borg. Do Preparatory Programming Lab Sessions Contribute to Even Work Distribution in Student Teams? Poster publication, In Proc. of the 42nd International Conference on Software Engineering, 2020.
[18] G. Modéus, P. Sandgren, M. Borg, F. Andersson, G. Wiel-Berggren, and M. Rosendahl Mjukvara är Sveriges Nya Infrastruktur: Här är Nästa Steg, Technical Report, Swedsoft and Teknikföretagen, 2019. (open access)
[17] M. Borg, C. Englund, and B. Duran. Traceability and Deep Learning – Safety-critical Systems with Traces Ending in Deep Neural Networks, In Proc. of the Grand Challenges of Traceability: The Next Ten Years, pp. 48-49, 2017. (open access)
[16] E. Bjarnason and M. Borg. Aligning Requirements and Testing: Working Together toward the Same Goal, IEEE Software, 34(1), pp. 20-23, 2017. (link, preprint, podcast)
[15] M. Unterkalmsteiner, G. Gay, M. Felderer, E. Bjarnason, M. Borg, and M. Morandini. Summary of the 3rd International Workshop on Requirements Engineering and Testing (RET 2016): Co-located with REFSQ 2016, Technical Report, 2016. (link)
[14] M. Borg, P. Gullin, and L. Olofsson. Do Take it Personal: It’s Not What You Say, It’s Who (and Where) You Are!, Tiny Transactions on Computer Science, Vol. 4, 2016. (open access)
[13] U. Franke and M. Borg. Möjliggörande Elektronik & Mjukvara: Tema Robusta System av System, Omvärldsbevakning av FoU på Fordonselektronikområdet, 2015. (open access)
[12] M. Borg and R. Boreham. Comparing Cousins: A Harmonized Analysis of Racket Sport Set Scores Based on Racketlon World Tour Results, 1st World Conference on the Science of Net and Wall Games, Szombathely, Hungary, 2015.
[11] E. Bjarnason, M. Borg, M. Morandini, M. Unterkalmsteiner, M. Felderer, and M. Staats. Summary of the 2nd International Workshop on Requirements Engineering and Testing (RET 2015): Co-located with ICSE 2015, Technical Report, 2015. (link)
[10] M. Borg. From Bugs to Decision Support – Leveraging the Historical Issue Reports in Software Evolution, PhD Thesis, Lund University, 2015. (blog, open access) *Please request a physical copy*
[9] M. Borg, and L. Jonsson. The More the Merrier: Leveraging Bug Inflow to Guide Software Maintenance, Tiny Transactions on Computer Science, Vol. 3, 2015. (open access)
[8] M. Felderer, E. Bjarnason, M. Borg, M. Unterkalmsteiner, M. Morandini, and M. Staats. Workshop Summary of the 1st International Workshop on Requirements and Testing, Technical Report, 2014. (open access)
[7] M. Borg. Embrace Your Issues: Compassing the Software Engineering Landscape Using Bug Reports, In Proc. of the 29th International Conference on Automated Software Engineering (Doctoral symposium), pp. 891-894, 2014. (link)
[6] M. Borg. Tackle ’em Bugs! Managing the Issue Overflow in Large-scale Software Engineering, In Book of Abstracts of the Summer School on Scientific Visualization and Presentation, pp. 19, 2014. (open access)
[5] J. de la Vara, M. Borg, K. Wnuk, and L. Moonen. Survey on Safety Evidence Change Impact Analysis in Practice: Detailed Description and Analysis, Technical Report 18, Simula Research Laboratory, 2014. (open access)
[4] M. Borg. Advancing Trace Recovery Evaluation: Applied Information Retrieval in a Software Engineering Context, Licentiate Thesis, Lund University, 2012. (open access) *Please request a physical copy*
[3] M. Borg. IR-based Traceability Recovery as a Plugin – An Industrial Case Study, In Proc. of the 4th BCS-IRSG Symposium on Future Directions in Information Access, pp. 14-17, 2011. (open access)
[2] M. Borg. In Vivo Evaluation of Large-scale IR-based Traceability Recovery, In Proc. of the 15th European Conference on Software Maintenance and Reengineering (Doctoral symposium), pp. 365-368, 2011. (link)
[1] M. Borg and L. Serafin. Safe Programming Languages for ABB Automation System 800xA, MSc Thesis, Lund University, 2007. (open access)