The cost-effective construction of software is increasingly important to businesses and consumers. Given software's ever-increasing size and complexity, modern software construction employs significant tool support. Recent tools complement traditional static analysis tools by exploiting the natural language found within a program's text through the use of Information Retrieval (IR). Best known for its use by search engines on the Internet, IR encompasses a growing collection of techniques that apply to large repositories of natural language. New tools using IR have tackled problems previously requiring considerable human effort. However, to reap the full benefit of IR techniques, the language across all software artifacts (e.g., requirement and design documents, test plans, as well as source code) must be normalized. Normalization align the vocabulary found in source code with that of other software artifacts. In addition to improving existing tools, normalization will also encourage the development of new techniques and methodologies useful in future tools. Empirical study of successful tool improvements will aid technology transfer of the tools expected to improve programmer productivity. Beyond its technical goals, this research promotes discovery in Loyola's undergraduate curriculum through the direct involvement of undergraduate students in scientific research and by integrating research results into classroom learning.
