Automatic test data generation targeting hybrid coverage criteria

Abstract

Software used in safety critical domains such as aviation and automotive has to be rigorously tested. Since exhaustive testing is not feasible, Modified Condition/Decision Coverage (MC/DC) has been introduced as an effective structural coverage alternative. However, studies have shown that complementing the test cases satisfying MC/DC to also satisfy Boundary Value Analysis (BVA) increases the bug finding rate. Hence, the industry adopted its testing processes to accommodate both. Satisfying these coverage requirements manually is very expensive and as a result many efforts were put to automate this task. Genetic algorithms (GA) have shown their effectiveness so far in this area. We propose an approach employing GA techniques and targeting hybrid coverage criteria to increase BVA in addition to MC/DC.