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Home > Archive>Volume 32, Issue 4, 2021 >1023-1038. DOI:10.13328/j.cnki.jos.006228
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Fusing Code and Documents to Mine Software Functional Features
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TP311

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National Natural Science Foundation of China (61972006); National Natural Science Fund for Distinguished Young Scholars (61525201)

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    Abstract:

    In the process of software reuse, users need concise and clear natural language description of software functions to understand the candidate software project quickly. However, current open source software often lacks high-quality documentation, which makes this process even more complex and difficult. This study proposes a novel functional feature mining approach combining code and documentation. It describes functional features in the form of verb phrases, automatically extracts functional features by iterately mining source code and software documents such as Stack Overflow, associates corresponding API usage example for each functional feature, and builds hierarchical functional feature view for uses finally. The experiments are set on several open source software and its related heterogeneous data, the results show that the functional features generated by the proposed approach cover 95.38% of the functions in official documentation, and the proposed approach achieves 93.78% and 92.57% accuracy for mining sentences and functional features respectively. Compared to two existing tools TaskNav and APITasks, the proposed approach improves the accuracy by 28.78% and 11.56% separately.

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沈琦,钱莹,邹艳珍,伍仕骏,谢冰.融合代码与文档的软件功能特征挖掘方法.软件学报,2021,32(4):1023-1038

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History
  • Received:September 13,2020
  • Revised:October 26,2020
  • Online: January 22,2021
  • Published: April 06,2021
Links:Institute of Software, CASChina Computer FederationCASNSFC
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