New journal article on model-based testing

Today, our new journal article appeared in the Science of Computer Programming journal of Elsevier.

It deals with the problem of automatically generating test-cases from mutated models:

Bernhard K. Aichernig, Elisabeth Jöbstl, and Stefan Tiran. Model-based mutation testing via symbolic refinement checking. Science of Computer Programming. 97 (2015): 383-404, Elsevier, 2015.

Here is a link to a free copy of it that works for 50 days.

Highlights:

• We deal with model- and mutation-based test case generation.
• The main focus lies on optimizations of the underlying conformance check.
• We explain the construction of test cases based on the conformance check.
• We allow for non-determinism in the test models.
• We demonstrate the effectiveness of our optimizations on industrial case studies.

Enjoy!

Towards Symbolic Model-Based Mutation Testing: Combining Reachability and Refinement Checking

We present our newest paper on model-based mutation testing accepted at MBT 2012.

Model-based mutation testing uses altered test models to derive test cases that are able to reveal whether a modelled fault has been implemented. This requires conformance checking between the original and the mutated model. This paper presents an approach for symbolic conformance checking of action systems, which are well-suited to specify reactive systems.

We also consider non-determinism in our models. Hence, we do not check for equivalence, but for refinement. We encode the transition relation as well as the conformance relation as a constraint satisfaction problem and use a constraint solver in our reachability and refinement checking algorithms.

Explicit conformance checking techniques often face state space explosion. First experimental evaluations show that our approach has potential to outperform explicit conformance checkers.

This research is part of the TRUFAL project.

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