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An Information Foraging Theory Perspective on Tools for Debugging, Refactoring, and Reuse Tasks

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https://ir.library.oregonstate.edu/concern/articles/xp68kh54c

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Abstract
  • Theories of human behavior are an important but largely untapped resource for software engineering research. They facilitate understanding of human developers’ needs and activities, and thus can serve as a valuable resource to researchers designing software engineering tools. Furthermore, theories abstract beyond specific methods and tools to fundamental principles that can be applied to new situations. Toward filling this gap, we investigate the applicability and utility of Information Foraging Theory (IFT) for understanding information-intensive software engineering tasks, drawing upon literature in three areas: debugging, refactoring, and reuse. In particular, we focus on software engineering tools that aim to support information-intensive activities, that is, activities in which developers spend time seeking information. Regarding applicability, we consider whether and how the mathematical equations within IFT can be used to explain why certain existing tools have proven empirically successful at helping software engineers. Regarding utility, we applied an IFT perspective to identify recurring design patterns in these successful tools, and consider what opportunities for future research are revealed by our IFT perspective.
  • Keywords: Programming Environments, Software maintenance, Integrated environments, Information foraging, Interactive environments, Programmer workbench, Human Factors, Design
  • Keywords: Programming Environments, Software maintenance, Integrated environments, Information foraging, Interactive environments, Programmer workbench, Human Factors, Design
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  • Fleming, S. D., Scaffidi, C., Piorkowski, D., Burnett, M., Bellamy, R., Lawrance, J., & Kwan, I. (2013). An information foraging theory perspective on tools for debugging, refactoring, and reuse tasks. ACM Transactions on Software Engineering and Methodology (TOSEM), 22(2), 1-41. doi:10.1145/2430545.2430551
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  • 22
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  • 2
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  • This work was supported in part by the Air Force Office of Scientific Research FA9550-09-1-0213, by the EUSES Consortium via ITR-0325273, and by an IBM Open Research Collaboration Award.
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