This paper presents analogy-based software quality estimation with project feature weights. The objective of this research is to predict the quality of project accurately and use the results in future predictions. The focus includes identifying parameters on which the quality of software depends. Estimation of rate of improvement of software quality chiefly depends on the development time. Assigning weights to these parameters to improve upon the results is also in the area of interest. In this paper two different similarity measures namely, Euclidian and Manhattan were the measures used for retrieving the matching cases from the knowledgebase to increases estimation accuracy & reliability. Expert judgment, weights and rating levels were used to assign weights and quality rating levels. The results show that assigning weights to software metrics increases the prediction performance considerably. In order to obtain the results, we have used indigenous tools.
| Published in | American Journal of Software Engineering and Applications (Volume 2, Issue 2) |
| DOI | 10.11648/j.ajsea.20130202.14 |
| Page(s) | 49-53 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Analogy, CBR, Effort estimation, Software quality prediction, Similarity function
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APA Style
Ekbal Rashid, Srikanta Patnaik, Vandana Bhattacharya. (2013). Analogy-Based Software Quality Prediction with Project Feature Weights. American Journal of Software Engineering and Applications, 2(2), 49-53. https://doi.org/10.11648/j.ajsea.20130202.14
ACS Style
Ekbal Rashid; Srikanta Patnaik; Vandana Bhattacharya. Analogy-Based Software Quality Prediction with Project Feature Weights. Am. J. Softw. Eng. Appl. 2013, 2(2), 49-53. doi: 10.11648/j.ajsea.20130202.14
AMA Style
Ekbal Rashid, Srikanta Patnaik, Vandana Bhattacharya. Analogy-Based Software Quality Prediction with Project Feature Weights. Am J Softw Eng Appl. 2013;2(2):49-53. doi: 10.11648/j.ajsea.20130202.14
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Download@article{10.11648/j.ajsea.20130202.14,
author = {Ekbal Rashid and Srikanta Patnaik and Vandana Bhattacharya},
title = {Analogy-Based Software Quality Prediction with Project Feature Weights},
journal = {American Journal of Software Engineering and Applications},
volume = {2},
number = {2},
pages = {49-53},
doi = {10.11648/j.ajsea.20130202.14},
url = {https://doi.org/10.11648/j.ajsea.20130202.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajsea.20130202.14},
abstract = {This paper presents analogy-based software quality estimation with project feature weights. The objective of this research is to predict the quality of project accurately and use the results in future predictions. The focus includes identifying parameters on which the quality of software depends. Estimation of rate of improvement of software quality chiefly depends on the development time. Assigning weights to these parameters to improve upon the results is also in the area of interest. In this paper two different similarity measures namely, Euclidian and Manhattan were the measures used for retrieving the matching cases from the knowledgebase to increases estimation accuracy & reliability. Expert judgment, weights and rating levels were used to assign weights and quality rating levels. The results show that assigning weights to software metrics increases the prediction performance considerably. In order to obtain the results, we have used indigenous tools.},
year = {2013}
}
TY - JOUR T1 - Analogy-Based Software Quality Prediction with Project Feature Weights AU - Ekbal Rashid AU - Srikanta Patnaik AU - Vandana Bhattacharya Y1 - 2013/04/02 PY - 2013 N1 - https://doi.org/10.11648/j.ajsea.20130202.14 DO - 10.11648/j.ajsea.20130202.14 T2 - American Journal of Software Engineering and Applications JF - American Journal of Software Engineering and Applications JO - American Journal of Software Engineering and Applications SP - 49 EP - 53 PB - Science Publishing Group SN - 2327-249X UR - https://doi.org/10.11648/j.ajsea.20130202.14 AB - This paper presents analogy-based software quality estimation with project feature weights. The objective of this research is to predict the quality of project accurately and use the results in future predictions. The focus includes identifying parameters on which the quality of software depends. Estimation of rate of improvement of software quality chiefly depends on the development time. Assigning weights to these parameters to improve upon the results is also in the area of interest. In this paper two different similarity measures namely, Euclidian and Manhattan were the measures used for retrieving the matching cases from the knowledgebase to increases estimation accuracy & reliability. Expert judgment, weights and rating levels were used to assign weights and quality rating levels. The results show that assigning weights to software metrics increases the prediction performance considerably. In order to obtain the results, we have used indigenous tools. VL - 2 IS - 2 ER -
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