An Analysis of the Code Coverage-based Greedy Algorithms for Test Suite Reduction

Software testing is widely used by development organizations to improve the quality and reliability of a System under Test (SUT). However, testing requires high amount of development resources due to many factors. One important factor is the high cost of executing all generated test cases. Test Suite Reduction (TSR) heuristics focus on finding a minimized set of test cases without compromising on fault detection capability. In addition, TSR can be highly useful in a testing scenario which needs to be performed using actual hardware. Ultimately, TSR helps the development organizations to reduce the amount of estimated development resources. Researchers have proposed a number of TSR heuristics based on different variations of greedy algorithm. In this paper, we present a comparison of proposed code coverage-based greedy algorithms for TSR based on a devised set of analysis parameters. We conclude that most of the greedy algorithm based TSR heuristics use fine-granular coverage criteria and focus on greedily solving the single-objective based TSR optimization problem.