Abstract
Recent source code transformation techniques are adopted for coverage-driven testing to ensure software quality. However, due to the limitations present in constraint solvers of concolic testing, they lag to meet desired satisfaction level for testing safety avionics softwares. Particularly, they have the limitation of generating required number of qualitative test cases. So, we propose an agile-based automated test case augmentation technique that flips concolic based test cases that are obtained through source code transformation techniques to achieve high “Modified Condition/Decision Coverage" (MC/DC) score. This work has four technical contributions. The first contribution is code instrumentation of the input program to make it tool supportive. The second contribution is to propose a technique that can generate new effective test cases through agile process by augmenting concolic test cases. The third contribution is to propose a minimizer that can remove redundant and infeasible test cases. The fourth contribution is to propose a framework for MC/DC computation. To validate the proposed technique, it is experimented on two recent source code transformation techniques such as JPCT and JEXNCT and achieved 16.69% and 19.47% increase on MC/DC score respectively than existing technique using some benchmark input Java programs.
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Barisal, S.K., Dutta, A., Godboley, S., Sahoo, B., Mohapatra, D.P. (2022). Agility Based Coverage Improvement. In: Przybyłek, A., Jarzębowicz, A., Luković, I., Ng, Y.Y. (eds) Lean and Agile Software Development. LASD 2022. Lecture Notes in Business Information Processing, vol 438. Springer, Cham. https://doi.org/10.1007/978-3-030-94238-0_10
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