Posted on Sat 01 February 2020 in misc

Mutant Density: A Measure of Fault-Sensitive Complexity Ali Parsai and Serge Demeyer. Proceedings of ICSE 2020 Workshops: SoHEAL. IEEE/ACM, 2020. bibtex pdf publisher

Comparing Mutation Coverage Against Branch Coverage in an Industrial Setting Ali Parsai and Serge Demeyer. Foundation for Mastering Change, International Journal on Software Tools for Technology Transfer. Springer, 2020. bibtex pdf publisher

Automating TEST Case Design, Selection, and Evaluation Report on 10 Editions of A-TEST Workshop Tanja Vos, Wishnu Prasetya, Sigrid Eldh, Sinem Getir, Ali Parsai, and Pekka Aho. ACM SIGSOFT Software Engineering Notes. ACM, 2020. bibtex pdf publisher

Do Null-Type Mutation Operators Help Prevent Null-Type Faults? Ali Parsai and Serge Demeyer. Proceedings of SOFSEM 2019: Theory and Practice of Computer Science. Springer, 2019. bibtex pdf publisher

C++11/14 Mutation Operators Based on Common Fault Patterns Ali Parsai, Serge Demeyer, and Seph De Busser. Proceedings of the 30th IFIP International Conference on Testing Software and Systems. Springer, 2018. bibtex pdf publisher

Dynamic Mutant Subsumption Analysis using LittleDarwin Ali Parsai and Serge Demeyer. Proceedings of the 8th ACM SIGSOFT International Workshop on Automated Software Testing. ACM, 2017. bibtex pdf publisher

LittleDarwin: a Feature-Rich and Extensible Mutation Testing Framework for Large and Complex Java Systems Ali Parsai, Alessandro Murgia, and Serge Demeyer. Proceedings of the 7th IPM International Conference on Fundamentals of Software Engineering. Springer 2017. bibtex pdf publisher

A Model to Estimate First-Order Mutation Coverage from Higher-Order Mutation Coverage Ali Parsai, Alessandro Murgia, and Serge Demeyer. Proceedings of the 2016 International Conference on Software Quality, Reliability, and Security. IEEE, 2016. bibtex pdf publisher

Evaluating Random Mutant Selection at Class-Level in Projects with Non-Adequate Test Suites Ali Parsai, Alessandro Murgia, and Serge Demeyer. Proceedings of the 20th International Conference on Evaluation and Assessment in Software Engineering. ACM, 2016. bibtex pdf publisher

Mutation Testing as a Safety Net for Test Suite Refactoring Ali Parsai, Alessandro Murgia, Quinten D. Soetens, and Serge Demeyer. Scientific Workshop Proceedings of XP 2015. ACM, 2015. bibtex pdf publisher

Considering Polymorphism in Change-Based Test Suite Reduction Ali Parsai, Quinten D. Soetens, Alessandro Murgia, and Serge Demeyer. Agile Methods. Large-Scale Development, Refactoring, Testing, and Estimation. Springer, 2014. bibtex pdf publisher


Posted on Sat 25 January 2020 in misc

Mutation Testing, Opportunities and Pitfalls Test Automation Research for Industry, 11 April 2019, Ericsson, Stockholm, Sweden


Mutant Density: A Measure of Fault-Sensitive Complexity SoHEAL 2020, 3 July 2020, Virtual Presentation YouTube

PhD Thesis

Posted on Fri 10 January 2020 in misc


The cost of software faults has increased from 59 billion USD in 2002 to 1.7 trillion USD in 2017. To alleviate this cost, the consensus among software engineers is to test as early and as often as possible. This, however, is not adopted by many software development teams. Most often, there are limited resources available for testing compared to the development of a product. Therefore, new techniques and methods are needed to improve testing quality in practice. Currently, most software companies rely on simple coverage metrics to assess the quality of their tests. Yet, the academic literature proposes the use of mutation testing to assess and improve the quality of software tests. Despite the promising results of mutation testing, it is not yet widely adopted in industry. We attribute this to three main problems: the performance overhead, lack of domain knowledge in tool providers, and lack of tool support. In this thesis, we address these three problems. Our results show that it is feasible to adapt the process of mutation testing based on industrial needs.


Full Thesis (PDF)

Bibliographic Info (BIB)

University of Antwerp Library Page

Graduate Work

Posted on Sun 05 January 2020 in misc

The article resulting from Research Internship 1 titled "Considering Polymorphism in Change-Based Test Suite Reduction" was accepted in RefTest2014. You can find the abstract below. The full preprint version can be found here. The final publication is available at

With the increasing popularity of continuous integration, algorithms for selecting the minimal test-suite to cover a given set of changes are in order. This paper reports on how polymorphism can handle false negatives in a previous algorithm which uses method-level changes in the base-code to deduce which tests need to be rerun. We compare the approach with and without  olymorphism on two distinct cases —PMD and CruiseControl— and discovered an interesting trade-off: incorporating polymorphism results in more relevant tests to be included in the test suite (hence improves accuracy), however comes at the cost of a larger test suite (hence increases the time to run the minimal test-suite).

The report for the Research Internship 2 titled "Literature Survey on Mutation Testing" can be found here. You can find the abstract below. 

Mutation testing is one of the leading methods of testing the test-suites. In this article we review the literature about mutation testing in order to provide a guide for a developer who wants to design a mutation testing framework. We explore the diverse nature of mutation operators as a main ingridient to any mutation testing framework, and also discuss the features of the tools developed in the past decade.

The abstract for the Master's Thesis is provided below.

In order to assess the ability of a test suite to catch bugs, a quality metric is needed which can simulate realistic situations. Mutation analysis provides this metric with a reliable and repeatable approach. However, because of the computationally intensive nature of mutation  analysis and the difficulties in applying such a technique to complex systems, it has not been widely adopted in industry. This study aims to determine the feasibility of using this technique on an industrial case, and to find out if the information gathered by this method is worth the performance costs. 

You can download the tool developed for the thesis (LittleDarwin) here. The final thesis report is available here.

Research Interests

Posted on Wed 01 January 2020 in misc

  • Mutation Testing
  • Software Quality Assessment
  • Software Testing
  • Digital Twins