Research On Combined Test Case Generation Method Based On Harmony Search Technology

Software systems are typically composed of many subcomponents. Each subcomponent is responsible for providing one or more functionalities to the overall system. Often, in each implementation tailored and configured for a specific set of applications or environments, having a different implementation for each subcomponent is desirable. In this way, interoperability and portability can potentially be maximized. Because each subcomponent has a family of potentially thousands or millions of program configurations and instantiations, quality assurances activities are heavily burdened (i.e., particularly in terms of increasing testing costs and time-to-market pressure). Testing all of the configurations and instantiations is not feasible (i.e., due to combinatorial explosion of configurable test data). A recent work on t-way interaction testing has demonstrated that a combinatorial approach based on variable-strength t-way combinations of inputs (i.e., where t denotes the strength of interaction) can be effective. As a result, many new variable-strength t-way strategies have been developed and are now part of the literature.In order to search the global optimal solution and reduce the test suite scale more efficently, this paper studied the existing suite generation method. Based on the Harmony Search Algorithm (HSA), the current paper proposes to implement a new variable-strength t-way test generation strategy called Harmony Search Based Strategy (HSBS). And puts forward two algorithms:HSBS interaction generation algorithm and the HSBS test suite generation algorithm. The HSBS support variable-strength interaction test suite generation and can handle constraints. Unlike other t-way interaction testing strategys that based on Meta-Heuristic Search algorithm, HSBS can support high strength interaction (t>6) and realize the seamless support constraint. Finally, the paper analyzed the various parameters that impact on the HSBS strategy.Through some experiments compared with existing interaction testing, the result shows that HSBS strategy is more efficient.