Leveraged Quality Assessment using Information Retrieval Techniques

Abstract

The goal of this research is to apply language processing techniques to extend human judgment into situations where obtaining direct human judgment is impractical due to the volume of information that must be considered. On aspect of this is leveraged quality assessments, which can be used to evaluate third-party coded subsystems, to track quality across the versions of a program, to assess the compression effort (and subsequent cost) required to make a change, and to identify parts of a program in need of preventative maintenance. A description of the QALP tool, its output from just under two million lines of code, and an experiment aimed at evaluating the tool's use in leveraged quality assessment are presented. Statistically significant results from this experiment validate the use of the QALP tool in human leverage quality assessment