Developing natural language-based program analyses and tools to expedite software maintenance

ABSTRACT

With as much as 60-90% of software life cycle resources spent on program maintenance, there is a critical need for automated software tools to help explore and understand today's large and complex software. One important source of information software maintenance tools can draw from is lexical information in comments and identifiers. Identifier names often communicate a programmer's intent when writing code, and help developers map real-world concepts to code during comprehension. My dissertation will develop specialized information retrieval techniques and natural language analyses for software so that software maintenance tools can take full advantage of the wealth of information in program identifiers, and integrate these techniques into software tools to expedite the maintenance activities of program exploration, concern location, and fault localization.

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Index Terms

• Software and its engineering

  • Software creation and management

    • Software post-development issues

      • Software reverse engineering