I am a temporary lecturer with the Software Engineering Research Group (SERG) at the Department of Computer Science, Lund University, Sweden. I am funded by the Industrial Excellence Centre for Embedded Applications Software Engineering (EASE), working within Theme D - Aligning Requirements and Verification (Project D.2 Large-scale Test to Requirements Linking).
My main research contributions concern increasing the level of automation in the inflow of issue reports by finding actionable patterns in historical data, especially to support change impact analysis and issue assignment. I defended my the PhD thesis on the topic in May 2015: From Bugs to Decision Support - Leveraging Historical Issue Reports in Software Evolution, and I have authored a book chapter on Recommendations Systems for Issue Management.
Previously I focused on information retrieval techniques to semi-automatically create traces between software artifacts. Visit my TraceRepo, a repository of publications covering related research until 2011. In September 2012 I presented my licentiate thesis on the topic: Advancing Trace Recovery Evaluation – Applied Information Retrieval in a Software Engineering Context.
I joined SERG in January 2010. Prior to that I worked three years at ABB in Malmö, working first as a thesis student and then as a development engineer. I was part of a team responsible for editor and compiler development in the 800xA automation system. My experiences include:
- IDE development for DSLs (IEC 61131-3)
- C/C++ and C# development
- Regression testing and test automation
- Safety-critical development (SIL 2)
- Safety certification (IEC 61508 and IEC 61511)
- Embedded systems
- Legacy code
I am currently on a study-leave from ABB, working full-time with my PhD studies.
My research interests are related to information overload involved in large-scale software development. I have published more than 15 papers on the topic. More specifically, my interests include:
- alignment of requirements and test
- mining software repositories
- trace capture/recovery
- software and traceability visualization
- information retrieval and findability
- recommendation systems
- machine learning
- issue management
My favorite tools of the trade are RapidMiner, R, yEd, Gephi, Lucene, and Weka.
I try to maintain Wikipedia pages related to my research, especially in Swedish. Start browsing from spårbarhetsåterhämtning if you are interested. I am a dedicated wiki incrementalist. Currently I try to improve the Swedish pages on recommendation systems.
I am always looking for students interested in master thesis projects related to my interests, take a look at the project proposals for inspiration.
- In print:
- Assar, Borg, and Pfahl. Using Text Clustering to Predict Defect Resolution Time: A Conceptual Replication and an Evaluation of Prediction Accuracy, Awaiting issue number in Empirical Software Engineering, Springer Online First.
- Jonsson, Borg, Broman, Sandahl, Eldh, and Runeson. Automated Bug Assignment: Ensemble-based Machine Learning, Awaiting issue number in Empirical Software Engineering. Springer Online First, Preprint
- Under revision:
- A survey of impact analysis in safety-critical domains. 100+ answers from different domains.
- In submission:
- Guidelines for tuning software engineering tools using experiments.
- An extended version of an interview study on the agile practice "using test cases as requirements".
- Ongoing, not published:
- Reporting a case study on tool support for impact analysis, based on a combination of IR-based trace recovery techniques and network analysis. First in situ study of impact analysis tool in proprietary context.
- Qualitative analysis of engineers' experienced challenges when conducting change impact analysis.
- Exploring safety certifiers' perspectives on traceability as mandated by safety standards.