Challenges in analyzing software documentation in Portuguese

Many tools that automatically analyze, summarize, or transform software artifacts rely on natural language processing tooling for the interpretation of natural language text produced by software developers, such as documentation, code comments, commit messages, or bug reports. Processing natural lan...

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Bibliographic Details
Main Authors: TREUDE, Christoph, PROLO, Carlos A., FIGUEIRA FILHO, Fernando
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2015
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Online Access:https://ink.library.smu.edu.sg/sis_research/8943
https://ink.library.smu.edu.sg/context/sis_research/article/9946/viewcontent/sbes15.pdf
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Institution: Singapore Management University
Language: English
Description
Summary:Many tools that automatically analyze, summarize, or transform software artifacts rely on natural language processing tooling for the interpretation of natural language text produced by software developers, such as documentation, code comments, commit messages, or bug reports. Processing natural language text produced by software developers is challenging because of unique characteristics not found in other texts, such as the presence of code terms and the systematic use of incomplete sentences. In addition, texts produced by Portuguese-speaking developers mix languages since many keywords and programming concepts are referred to by their English name. In this paper, we provide empirical insights into the challenges of analyzing software artifacts written in Portuguese. We analyzed 100 question titles from the Portuguese version of Stack Overflow with two Portuguese language tools and identified multiple problems which resulted in very few sentences being tagged completely correctly. Based on these results, we propose heuristics to improve the analysis of natural language text produced by software developers in Portuguese.