IEICE TRANSACTIONS on Information
LSA-X: Exploiting Productivity Factors in Linear Size Adaptation for Analogy-Based Software Effort Estimation
Summary :
Analogy-based software effort estimation has gained a considerable amount of attention in current research and practice. Its excellent estimation accuracy relies on its solution adaptation stage, where an effort estimate is produced from similar past projects. This study proposes a solution adaptation technique named LSA-X that introduces an approach to exploit the potential of productivity factors, i.e., project variables with a high correlation with software productivity, in the solution adaptation stage. The LSA-X technique tailors the exploitation of the productivity factors with a procedure based on the Linear Size Adaptation (LSA) technique. The results, based on 19 datasets show that in circumstances where a dataset exhibits a high correlation coefficient between productivity and a related factor (r≥0.30), the proposed LSA-X technique statistically outperformed (95% confidence) the other 8 commonly used techniques compared in this study. In other circumstances, our results suggest using any linear adaptation technique based on software size to compensate for the limitations of the LSA-X technique.
- Publication
- IEICE TRANSACTIONS on Information Vol.E99-D No.1 pp.151-162
- Publication Date
- 2016/01/01
- Publicized
- 2015/10/15
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2015EDP7237
- Type of Manuscript
- PAPER
- Category
- Software Engineering
Authors
Passakorn PHANNACHITTA
Nara Institute of Science and Technology
Akito MONDEN
Okayama University
Jacky KEUNG
City University of Hong Kong
Kenichi MATSUMOTO
Nara Institute of Science and Technology
Keyword
Latest Issue
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Passakorn PHANNACHITTA, Akito MONDEN, Jacky KEUNG, Kenichi MATSUMOTO, "LSA-X: Exploiting Productivity Factors in Linear Size Adaptation for Analogy-Based Software Effort Estimation" in IEICE TRANSACTIONS on Information,
vol. E99-D, no. 1, pp. 151-162, January 2016, doi: 10.1587/transinf.2015EDP7237.
Abstract: Analogy-based software effort estimation has gained a considerable amount of attention in current research and practice. Its excellent estimation accuracy relies on its solution adaptation stage, where an effort estimate is produced from similar past projects. This study proposes a solution adaptation technique named LSA-X that introduces an approach to exploit the potential of productivity factors, i.e., project variables with a high correlation with software productivity, in the solution adaptation stage. The LSA-X technique tailors the exploitation of the productivity factors with a procedure based on the Linear Size Adaptation (LSA) technique. The results, based on 19 datasets show that in circumstances where a dataset exhibits a high correlation coefficient between productivity and a related factor (r≥0.30), the proposed LSA-X technique statistically outperformed (95% confidence) the other 8 commonly used techniques compared in this study. In other circumstances, our results suggest using any linear adaptation technique based on software size to compensate for the limitations of the LSA-X technique.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2015EDP7237/_p
Copy
@ARTICLE{e99-d_1_151,
author={Passakorn PHANNACHITTA, Akito MONDEN, Jacky KEUNG, Kenichi MATSUMOTO, },
journal={IEICE TRANSACTIONS on Information},
title={LSA-X: Exploiting Productivity Factors in Linear Size Adaptation for Analogy-Based Software Effort Estimation},
year={2016},
volume={E99-D},
number={1},
pages={151-162},
abstract={Analogy-based software effort estimation has gained a considerable amount of attention in current research and practice. Its excellent estimation accuracy relies on its solution adaptation stage, where an effort estimate is produced from similar past projects. This study proposes a solution adaptation technique named LSA-X that introduces an approach to exploit the potential of productivity factors, i.e., project variables with a high correlation with software productivity, in the solution adaptation stage. The LSA-X technique tailors the exploitation of the productivity factors with a procedure based on the Linear Size Adaptation (LSA) technique. The results, based on 19 datasets show that in circumstances where a dataset exhibits a high correlation coefficient between productivity and a related factor (r≥0.30), the proposed LSA-X technique statistically outperformed (95% confidence) the other 8 commonly used techniques compared in this study. In other circumstances, our results suggest using any linear adaptation technique based on software size to compensate for the limitations of the LSA-X technique.},
keywords={},
doi={10.1587/transinf.2015EDP7237},
ISSN={1745-1361},
month={January},}
Copy
TY - JOUR
TI - LSA-X: Exploiting Productivity Factors in Linear Size Adaptation for Analogy-Based Software Effort Estimation
T2 - IEICE TRANSACTIONS on Information
SP - 151
EP - 162
AU - Passakorn PHANNACHITTA
AU - Akito MONDEN
AU - Jacky KEUNG
AU - Kenichi MATSUMOTO
PY - 2016
DO - 10.1587/transinf.2015EDP7237
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E99-D
IS - 1
JA - IEICE TRANSACTIONS on Information
Y1 - January 2016
AB - Analogy-based software effort estimation has gained a considerable amount of attention in current research and practice. Its excellent estimation accuracy relies on its solution adaptation stage, where an effort estimate is produced from similar past projects. This study proposes a solution adaptation technique named LSA-X that introduces an approach to exploit the potential of productivity factors, i.e., project variables with a high correlation with software productivity, in the solution adaptation stage. The LSA-X technique tailors the exploitation of the productivity factors with a procedure based on the Linear Size Adaptation (LSA) technique. The results, based on 19 datasets show that in circumstances where a dataset exhibits a high correlation coefficient between productivity and a related factor (r≥0.30), the proposed LSA-X technique statistically outperformed (95% confidence) the other 8 commonly used techniques compared in this study. In other circumstances, our results suggest using any linear adaptation technique based on software size to compensate for the limitations of the LSA-X technique.
ER -
English
