Software Testing Laboratory

Focus:

Model-based testing of embedded software, empirical studies of software testing, and test automation.


The software testing laboratory (STL) at MDH focuses on industry-relevant research in software testing. In our research, we develop, refine, and evaluate methods, theories and tools for testing of complex software-intensive systems.

With an emphasis on method and tool development, as well as industrial and practical real life case studies, our research focus includes (but is not limited to) test design, model-based testing, search-based software testing, decision-support for software testing, and test automation.

The objectives of STL are to improve the current state-of-the-art in software testing, to share our results with the broader research community, to actively seek academic and industrial collaboration, and to transfer results and knowledge for industrial adoption.  

[Show all publications]

Towards Execution Time Prediction for Test Cases from Test Specification (Aug 2017)
Sahar Tahvili, Mehrdad Saadatmand, Markus Bohlin, Wasif Afzal, Sharvathul Hasan Ameerjan
43rd Euromicro Conference on Software Engineering and Advanced Applications (SEAA'17)

SLAs for Industrial IoT: Mind the Gap (Aug 2017)
Alessandro Papadopoulos, Sara Abbaspour Asadollah, Mohammad Ashjaei, Saad Mubeen, Hongyu Pei-Breivold, Moris Behnam
The 4th International Symposium on Inter-cloud and IoT (ICI 2017) (ICI'17)

A Black-Box Approach to Latency and Throughput Analysis (Jul 2017)
Daniel Brahneborg, Wasif Afzal, Adnan Causevic
The 2017 IEEE International Conference on Software Quality, Reliability and Security (QRS 2017)

A Pragmatic Perspective on Regression Testing Challenges (Jul 2017)
Daniel Brahneborg, Wasif Afzal, Adnan Causevic
The 2017 IEEE International Conference on Software Quality, Reliability and Security (QRS 2017)

Can Pairwise Testing Perform Comparably to Manually Handcrafted Testing Carried Out by Industrial Engineers? (Jul 2017)
Peter Charbachi, Linus Eklund , Eduard Paul Enoiu
International Workshop on Combinatorial Testing and its Applications (CTA'17)

Process Metrics are not Bad Predictors of Fault Proneness (Jul 2017)
Biljana Stanic, Wasif Afzal
The 2017 IEEE International Workshop on Software Engineering and Knowledge Management (SEKM'17)


Daniel Sundmark, Professor

Room: U1-063
Phone:


Wasif Afzal, Associate Professor

Room: U1-138
Phone: +46 21107393