Test Suite Skimming on Agent Based Model using Maximum Clique on a Modified Bee Colony Algorithm

The need for test case skimming is inevitable in almost all arenas of software testing owing to the business constraints on the drop dead date of the date of delivery to pass the QA cycle. Trade-offs are often needed to between time and the test coverage to ensure the maximum test cases are covered within the stipulated time, especially on systems that are just entering the production environment after getting promoted from the staging phase. The most important test cases are often not deemed to qualify under the sanity test suite and any bugs that creeped in them would go undetected until it is found out by the actual user at firsthand. Hence there arises a need to refine the test cases to accommodate the maximum test coverage it makes within the stipulated period of time. An attempt is made in this paper to layout a testing framework to address the process of the test case skimming by following the maximum clique identification on an improved bee colony algorithm, where the optimum input to the test-bed is determined by selecting the test-cases that constitute the input. This input heavily depends on determining the location of the result hive and sub-partitioning, thus test-cases with higher quality are picked up by the improved bee colony algorithm and provides better test efficiency. The Average Percentage of Conditions Covered (APCC) metrics have been used to show the effectiveness of proposed algorithm.