A classification scheme for studies on fault-prone components
Runeson, Per LU
; Ohlsson, Magnus C.
and Wohlin, Claes
(2001)
2188.
p.341-355
- Abstract
- Various approaches are presented in the literature to identify fault-prone components. The approaches represent a wide range of characteristics and capabilities, but they are not comparable, since different aspects are compared and different data sets are used. In order to enable a consistent and fair comparison, we propose a classification scheme, with two parts, 1) a characterisation scheme which captures information on input, output and model characteristics, and 2) an evaluation scheme which is designed for comparing different models' capabilities. The schemes and the rationale for the elements of the schemes are presented in the paper. Important capabilities to evaluate when comparing different models are rate of misclassification,... (More)
- Various approaches are presented in the literature to identify fault-prone components. The approaches represent a wide range of characteristics and capabilities, but they are not comparable, since different aspects are compared and different data sets are used. In order to enable a consistent and fair comparison, we propose a classification scheme, with two parts, 1) a characterisation scheme which captures information on input, output and model characteristics, and 2) an evaluation scheme which is designed for comparing different models' capabilities. The schemes and the rationale for the elements of the schemes are presented in the paper. Important capabilities to evaluate when comparing different models are rate of misclassification, classification efficiency and total classification cost. Further, the schemes are applied in an example study to illustrate the use of the schemes. It is expected that applying these schemes would help researchers to compare different approaches and thereby enable building of a more consistent knowledge base in software engineering. In addition it is expected to help practitioners to choose a suitable prediction approach for a specific environment by filling out the characterisation scheme and making an evaluation in their own environment. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/526419
- author
- Runeson, Per
LU
; Ohlsson, Magnus C.
and Wohlin, Claes
- organization
- publishing date
- 2001
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Lecture Notes in Computer Science
- volume
- 2188
- pages
- 341 - 355
- publisher
- Springer
- external identifiers
-
- scopus:84977534564
- DOI
- 10.1007/3-540-44813-6_29
- language
- English
- LU publication?
- yes
- id
- 742751fa-582c-46cd-98b0-374d9c176b98 (old id 526419)
- date added to LUP
- 2016-04-04 12:03:55
- date last changed
- 2022-01-29 22:52:36
@inproceedings{742751fa-582c-46cd-98b0-374d9c176b98,
abstract = {{Various approaches are presented in the literature to identify fault-prone components. The approaches represent a wide range of characteristics and capabilities, but they are not comparable, since different aspects are compared and different data sets are used. In order to enable a consistent and fair comparison, we propose a classification scheme, with two parts, 1) a characterisation scheme which captures information on input, output and model characteristics, and 2) an evaluation scheme which is designed for comparing different models' capabilities. The schemes and the rationale for the elements of the schemes are presented in the paper. Important capabilities to evaluate when comparing different models are rate of misclassification, classification efficiency and total classification cost. Further, the schemes are applied in an example study to illustrate the use of the schemes. It is expected that applying these schemes would help researchers to compare different approaches and thereby enable building of a more consistent knowledge base in software engineering. In addition it is expected to help practitioners to choose a suitable prediction approach for a specific environment by filling out the characterisation scheme and making an evaluation in their own environment.}},
author = {{Runeson, Per and Ohlsson, Magnus C. and Wohlin, Claes}},
booktitle = {{Lecture Notes in Computer Science}},
language = {{eng}},
pages = {{341--355}},
publisher = {{Springer}},
title = {{A classification scheme for studies on fault-prone components}},
url = {{http://dx.doi.org/10.1007/3-540-44813-6_29}},
doi = {{10.1007/3-540-44813-6_29}},
volume = {{2188}},
year = {{2001}},
}