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Correlation-based software search by leveraging software term database
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DOI：10.1007/s11704-017-6573-z.png)
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Abstract
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Internet-scale open source software (OSS) production in various communities generates abundant reusable resources for software developers. However, finding the desired and mature software with keyword queries from a considerable number of candidates, especially for the fresher, is a significant challenge because current search services often fail to understand the semantics of user queries. In this paper, we construct a software term database (STDB) by analyzing tagging data in Stack Overflow and propose a correlation-based software search (CBSS) approach that performs correlation retrieval based on the term relevance obtained from STDB. In addition, we design a novel ranking method to optimize the initial retrieval result. We explore four research questions in four experiments, respectively, to evaluate the effectiveness of the STDB and investigate the performance of the CBSS. The experiment results show that the proposed CBSS can effectively respond to keyword-based software searches and significantly outperforms other existing search services at finding mature software.
Keywords:
software retrieval
software term database
open source software
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