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- W2085999713 abstract "To ease framework understanding, tools have been developed that analyze existing framework instantiations to extract API usage patterns and present them to the user. However, detailed quantitative evaluations of such recommender systems are lacking. In this paper we present an automated evaluation process which extracts queries and expected results from existing code bases. This enables the validation of recommendation systems with large test beds in an objective manner by means of precision and recall measures. We demonstrate the applicability of our approach by evaluating an improvement of an existing API recommender tool that takes into account the framework-method context for recommendations." @default.
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- W2085999713 date "2008-11-09" @default.
- W2085999713 modified "2023-09-30" @default.
- W2085999713 title "On evaluating recommender systems for API usages" @default.
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- W2085999713 doi "https://doi.org/10.1145/1454247.1454254" @default.
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