Detection of duplicate defect reports using natural language processing
Runeson, Per LU
; Alexandersson, Magnus
and Nyholm, Oskar
(2007)
29th International Conference on Software Engineering, ICSE 2007
p.499-508
- Abstract
- 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... (More)
- 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. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/643449
- author
- Runeson, Per
LU
; Alexandersson, Magnus
and Nyholm, Oskar
- organization
- publishing date
- 2007
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Sony Ericsson (CO), User testing
- host publication
- Proceedings - International Conference on Software Engineering
- pages
- 499 - 508
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 29th International Conference on Software Engineering, ICSE 2007
- conference location
- Minneapolis, MN, United States
- conference dates
- 2007-05-20 - 2007-05-26
- external identifiers
-
- wos:000247063000049
- other:CODEN: PCSEDE
- scopus:34548795892
- ISSN
- 0270-5257
- DOI
- 10.1109/ICSE.2007.32
- language
- English
- LU publication?
- yes
- id
- 790a2092-354d-4d08-ae3e-ba8c62ae9b38 (old id 643449)
- date added to LUP
- 2016-04-01 16:36:27
- date last changed
- 2022-04-22 23:12:41
@inproceedings{790a2092-354d-4d08-ae3e-ba8c62ae9b38,
abstract = {{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.}},
author = {{Runeson, Per and Alexandersson, Magnus and Nyholm, Oskar}},
booktitle = {{Proceedings - International Conference on Software Engineering}},
issn = {{0270-5257}},
keywords = {{Sony Ericsson (CO); User testing}},
language = {{eng}},
pages = {{499--508}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
title = {{Detection of duplicate defect reports using natural language processing}},
url = {{http://dx.doi.org/10.1109/ICSE.2007.32}},
doi = {{10.1109/ICSE.2007.32}},
year = {{2007}},
}