CSC News
Ge and Murphy-Hill Receive Best Paper Award
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The winning paper is titled “How Developers Use Multi-Recommendation System in Local Code Search,” and the abstract follows:
Developers often start programming tasks by searching for relevant code in their local codebase. Previous research suggests that 88% of manually-composed queries retrieve no relevant results. Many searches fail because existing search tools depend solely on string matching with manually-composed query, which cannot find semantically-related code. To solve this problem, researchers proposed query recommendation techniques to help developers compose queries without the extensive knowledge of the codebase under search. However, few of these techniques are empirically evaluated by the usage data from real-world developers. To fill this gap, we studied several query recommendation techniques by extending Sando and conducting a longitudinal field study. Our study shows that over 30% of all queries were adopted from recommendation; and recommended queries retrieved results 7% more often than manual queries.
The paper was co-authored by David Shepherd of ABB Inc., and Kostadin Damevski of Virginia State University. To read the award-winning paper, click here.
The IEEE Symposium on Visual Languages and Human-Centric Computing is the premier international forum for research on this topic. Established in 1984, the mission of the conference is to support the design, theory, application, and evaluation of computing technologies and languages for programming, modeling, and communicating, which are easier to learn, use, and understand by people. The conference was co-located with DIAGRAMS 2014.
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