Detection of Duplicate Defect Reports Using Natural Language Processing

Defect reports are generated from various testing and development activities in software engineering. Sometimes 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...

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Veröffentlicht in:29th International Conference on Software Engineering (ICSE'07) S. 499 - 510
Hauptverfasser: Runeson, P., Alexandersson, M., Nyholm, O.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.01.2007
Schlagworte:
Failure analysis
Mobile communication
Natural language processing
Natural languages
Prototypes
Relays
Robustness
Software engineering
Software testing
Vocabulary
ISBN:9780769528281, 0769528287
ISSN:0270-5257
Online-Zugang:Volltext
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Abstract Defect reports are generated from various testing and development activities in software engineering. Sometimes 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.
AbstractList Defect reports are generated from various testing and development activities in software engineering. Sometimes 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.
Author Nyholm, O.
Alexandersson, M.
Runeson, P.
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  surname: Nyholm
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Snippet Defect reports are generated from various testing and development activities in software engineering. Sometimes two reports are submitted that describe the...
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SubjectTerms Failure analysis
Mobile communication
Natural language processing
Natural languages
Prototypes
Relays
Robustness
Software engineering
Software testing
Vocabulary
Title Detection of Duplicate Defect Reports Using Natural Language Processing
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