Deficient documentation detection a methodology to locate deficient project documentation using topic analysis
| Autor: | James Miller, Abram Hindle, Joshua Charles Campbell, Zhen Xu, Chenlei Zhang |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
business.industry
Computer science Python (programming language) Technical documentation Latent Dirichlet allocation World Wide Web symbols.namesake Common Source Data Base Documentation symbols Stack overflow Project management Software engineering business Topic analysis computer computer.programming_language |
| Zdroj: | MSR |
| DOI: | 10.1109/msr.2013.6624005 |
| Popis: | A project's documentation is the primary source of information for developers using that project. With hundreds of thousands of programming-related questions posted on programming Q&A websites, such as Stack Overflow, we question whether the developer-written documentation provides enough guidance for programmers. In this study, we wanted to know if there are any topics which are inadequately covered by the project documentation. We combined questions from Stack Overflow and documentation from the PHP and Python projects. Then, we applied topic analysis to this data using latent Dirichlet allocation (LDA), and found topics in Stack Overflow that did not overlap the project documentation. We successfully located topics that had deficient project documentation. We also found topics in need of tutorial documentation that were outside of the scope of the PHP or Python projects, such as MySQL and HTML. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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