Recognizing software bug-specific named entity in software bug repository
作者： Cheng Zhou , Bin Li , Xiaobing Sun , Hongjing Guo
关键词:
摘要: Software bug issues are unavoidable in software development and maintenance. In order to manage bugs effectively, tracking systems developed help record, track the of each project. The rich information repository provides possibility establishment entity-centric knowledge bases understand fix bugs. However, existing named entity recognition (NER) deal with text that is structured, formal, well written, a good grammatical structure few spelling errors, which cannot be directly used for bug-specific recognition. For data, they free-form texts, include mixed language studded code, abbreviations software-specific vocabularies. this paper, we summarize characteristics entities, propose classification method build baseline corpus on two open source projects (Mozilla Eclipse). On basis, an approach called BNER Conditional Random Fields (CRF) model word embedding technique. An empirical study conducted evaluate accuracy our technique, results show designed suitable recognition, effective cross-projects NER.
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