CI-P: Collaborative Research: Advanced Text Analysis Infrastructure for Software Engineering

University Of Delaware, Newark DE

Investigators

Abstract

This planning project brings together the community to begin addressing the challenges of using text analysis (i.e., the analysis of the information extracted from the natural language used in software artifacts and program code) in software engineering. A set of workshops will be organized with researchers in the software engineering community interested in the use of text analysis, in order to elicit requirements for the design of the necessary infrastructure for the research community. The common infrastructure of foundational text analyses for the software domain will include software libraries, data, and educational materials. Because the textual information embedded in software artifacts, program code and documentation encodes the software?s domain incepts and developers? knowledge about them, it is critical in supporting developers to effectively maintain today?s software and it is essential to the other stake- holders in the software engineering process, including managers, clients, and users. A study of recent literature shows that over 25 distinct software engineering tasks, ranging from requirements analysis to program comprehension, utilize textual analysis based tools. This project?s outcomes will have a broad impact, enabling researchers to: combine different types of text analysis techniques; transfer results of successful research to industry and facilitate entry for software engineering researchers in applying text analysis techniques; integrate new components for exploration of novel approaches to specific analyses; gain continual user evaluation of text analysis-based software engineering tools; and enable other researchers and practitioners to easily leverage text analysis to solve new software engineering problems. The long-term goal is to create such an infrastructure, which will allow text analysis to integrate seamlessly with current technology and environments used by software engineers. The increase in software size and complexity, as well as larger development teams, have made it significantly more challenging for humans to maintain software without tools to support them.