Improving software quality for regular expression matching tools using automated combinatorial testing

Regular expression matching tools (grep) match regular expressions to lines of text. However, because of the complexity that regular expressions can reach, it is challenging to apply state of the art automated testing frameworks to grep tools. Combinatorial testing has shown to be an effective testing methodology, especially for systems with large input spaces. In this dissertation, we investigate the approach of a fully automated combinatorial testing system for regular expression matching tools CoRE (Combinatorial testing for Regular Expressions). CoRE automatically generates test cases using combinatorial testing and measures correctness using differential testing. CoRE outperformed AFL and AFLFast in terms of code coverage testing icGrep, GNU grep and PCRE grep.