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Detection of duplicate defect reports using natural language processing

In English

Författare

Summary, in English

Defect reports are generated from various testing and development activities in software engineering. Some-times two reports are submitted that describe the same problem, leading to duplicate reports. These reports are mostly written in structured natural language, and as such, it is hard to compare two reports for similarity with formal methods. In order to identify duplicates, we investigate using Natural Language Processing (NLP) techniques to support the identification. A prototype tool is developed and evaluated in a case study analyzing defect reports at Sony Ericsson Mobile Communications. The evaluation shows that about 2/3 of the duplicates can possibly be found using the NLP techniques. Different variants of the techniques provide only minor result differences, indicating a robust technology. User testing shows that the overall attitude towards the technique is positive and that it has a growth potential. © 2007 IEEE.

Publiceringsår

2007

Språk

Engelska

Sidor

499-508

Publikation/Tidskrift/Serie

Proceedings - International Conference on Software Engineering

Dokumenttyp

Konferensbidrag

Förlag

IEEE - Institute of Electrical and Electronics Engineers Inc.

Ämne

  • Computer Science

Nyckelord

  • Sony Ericsson (CO)
  • User testing

Conference name

29th International Conference on Software Engineering, ICSE 2007

Conference date

2007-05-20 - 2007-05-26

Conference place

Minneapolis, MN, United States

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 0270-5257
  • CODEN: PCSEDE