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Mendel: Source Code Recommendation based on a Genetic Metaphor
Angela Lozano, Andy Kellens, and Kim Mens
(Université Catholique de Louvain, Belgium; Vrije Universiteit Brussel, Belgium)
When evolving software systems, developers spend a considerable amount of time understanding existing source code. To successfully implement new or alter existing behavior, developers need to answer questions such as: “Which types and methods can I use to solve this task?” or “Should my implementation follow particular naming or structural conventions?”. In this paper we present Mendel, a source code recommendation tool that aids developers in answering such questions. Based on the entity the developer currently browses, the tool employs a genetics-inspired metaphor to analyze source-code entities related to the current working context and provides its user with a number of recommended properties (naming conventions, used types, invoked messages, etc.) that the source code entity currently being worked on should exhibit. An initial validation of Mendel seems to confirm the potential of our approach