Automated Discovery of Valid Test Strings from the Web Using Dynamic Regular Expressions Collation and Natural Language Processing

Classic approaches to test input generation -- such as dynamic symbolic execution and search-based testing -- are commonly driven by a test adequacy criterion such as branch coverage. However, there is no guarantee that these techniques will generate meaningful and realistic inputs, particularly in the case of string test data. Also, these techniques have trouble handling path conditions involving string operations that are inherently complex in nature. This paper presents a novel approach of finding valid values by collating suitable regular expressions dynamically that validate the format of the string values, such as an email address. The regular expressions are found using web searches that are driven by the identifiers appearing in the program, for example a string parameter called email Address. The identifier names are processed through natural language processing techniques to tailor the web queries. Once a regular expression has been found, a secondary web search is performed for strings matching the regular expression. An empirical study is performed on case studies involving String input validation code from 10 open source projects. Compared to other approaches, the precision of generating valid strings is significantly improved by employing regular expressions and natural language processing techniques.