Optimal Reordering Trace Files for Improving Software Testing Suitcase

Abstract

An invariant can be described as an essential relationship between program variables. The invariants are very useful in software checking and verification. The tools that are used to detect invariants are invariant detectors. There are two types of invariant detectors: dynamic invariant detectors and static invariant detectors. Daikon software is an available computer program that implements a special case of a dynamic invariant detection algorithm. Daikon proposes a dynamic invariant detection algorithm based on several runs of the tested program; then, it gathers the values of its variables, and finally, it detects relationships between the variables based on a simple statistical analysis. This method has some drawbacks. One of its biggest drawbacks is its overwhelming time order. It is observed that the runtime for the Daikon invariant detection tool is dependent on the ordering of traces in the trace file. A mechanism is proposed in order to reduce differences in adjacent trace files. It is done by applying some special techniques of mutation/crossover in genetic algorithm (GA). An experiment is run to assess the benefits of this approach. Experimental findings reveal that the runtime of the proposed dynamic invariant detection algorithm is superior to the main approach with respect to these improvements.