A reasoning-based approach to dynamic domain reduction in test data generation

Abstract

In this article, a new criterion, domain coverage, for white box testing is introduced. In search of the biggest subdomains for input variables exercising a given path, the variable domains are broken down into overlapping subregions in such a way that the resultant subregions either exercise or deviate from the path. To this aim, an incremental method is applied to detect the subregions, covering the longest subpaths from the start of the given path. The detected subdomain is further subdivided, and this process is repeated as far as the path is fully covered. If no subdomain is detected, the method is backtracked. The backtrack begins with the subdomain covering the longest subpath at the beginning of the given path, but this time the subdomain is divided into relatively smaller subregions, compared with the last time. A directed acyclic graph representation of each input variable domain is used to ignore re-examination of those subdomains which deviate from the path. Conducted experiments reveal that our proposed domain-oriented algorithm outperforms the existing path-oriented test data generation algorithms.