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Analogy-Based Software Quality Prediction with Project Feature Weights

Published: 2 April 2013
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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.

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), 2013. Published by Science Publishing Group

Keywords

Analogy, CBR, Effort estimation, Software quality prediction, Similarity function

References
[1] A. Idri, L.Kjiri, and A Abran. (2000), "COCOMO Cost Model Using Fuzzy Logic", In Proceedings of the 7th International Conference on Fuzzytheory and Technology, pp.219-223. Atlantic City, NJ, USA.
[2] A. Idri and A Abran. (2000b), "Towards A Fuzzy Logic Based Measures for Software Project Similarity", In Proceedings of the 6th Maghrebian Conference on Computer Sciences, pp. 9-18, Fes Morroco.
[3] A. Idri and A. Abran. (2001), "A Fuzzy Logic Based Measures For Software Project similarity: Validation and Possible Improvements", In Proceedings of the 7th International Symposium on Software Metrics, pp. 85-96, England, UK, IEEE.
[4] A. Idri , A. Abran and T.M. Khoshgoftaar .(2001c), " Fuzzy Analogy: Anew Approach for Software Cost Estimation", In Proceedings of the 11th International workshop on software Measurements, pp.93-101, Montreal, Canada.
[5] G.Kadoda, M Cartwright, L Chen, and M.shepperd.(2000), "Experiences Using Case- Based Reasoning to Predict Software Project Effort", In Proceeding of EASE, p.23-28, Keele,UK.
[6] I. Myrtveit and E. Stensrud. (1999), "A Controlled Experiment to Assess the Benefits of Estimating with Analogy and Regression Models", IEEE transactions on software Engineering, vol 25,no. 4, pp. 510-525.
[7] K. Ganeasn, T.M. Khoshgoftaar, and E. Allen. (2002), "Case-based Software Quality Prediction", International journal of Software Engineering and Knowledge Engineering, 10 (2), pp. 139-152.
[8] M. Auer, A. trendowicz, B. Graser, E. Haunschmid and S. Biffl, "Optimal Project Feature Weights in analogy-based Cost Estimation: Improvement and Limitations", IEEE, TSE, Vol.32, No.2, Feb 2006, pp 83-92.
[9] S. Kumar and V.Bhattacharjee,(2005),"Fuzz logic based Model for Software cost Estimation ",In Proceedings of the international Conference on information Technology, Nov’05, PCTE, Ludhiana India.
[10] S. Kumar and V.Bhattacharjee,(2007),"Analogy and Expert Judgment: A Hybrid Approach to Software Cost Estimation", In Proceedings of the National Conference on information Technology: Present practice and Challenge, Sep’07, New-Delhi, India.
[11] V. Bhattacherjee and S. Kumar,(2004),"Software cost estimation and its relevance in the Indian software Industry", In Proceedings of the International Conference on Emerging Technologies IT Industry, Nov’05, PCTE, Ludhiana India..
[12] V. Bhattacherjee and S .Kumar,(2006),"An Expert- Case Based Frame work for Software Cost Estimation", In Proceedings of the National Conference on Soft Computing Techniques for Engineering Application (SCT-2006), NIT Rourkela.
[13] E. Rashid, V. Bhattacherjee, S. Patnaik, "The Application of Case-Based Reasoning to Estimation of Software Development Effort". International Journal of Computer Science and Informatics (IJCSI) ISSN 2231 –5292, Vol 1 Issue 3 pp 29-34 Feb 2012.
[14] V. Bhattacherjee, S. Kumar and E. Rashid ,A Case Study on Estimation of Software Development Effort" In Proceedings on International Conference on Advanced Computing Technologies(ICACT-2008), Gokaraju Rangaraju Institute of Engg & Technology, Hyderabad, India,p.no.161-164.
[15] Ekbal Rashid, Srikanta Patnaik, Vandana Bhattacherjee "A Survey in the Area of Machine Learning and Its Application for Software Quality Estimation" has been published in ACM SigSoft ISSN 0163-5948, volume 37, number 5, September 2012, http://doi.acm.org/10.1145/2347696.2347709 New York, NY, USA.
[16] Shi Zhong,Taghi M.Khoshgoftaar and Naeem Selvia "Unsupervised Learning for Expert-Based Software Quality Estimation".Proceeding of the Eighth IEEE International Symposium on High Assurance Systems Engineering (HASE’04).
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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

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    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

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    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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  • @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}
    }
    

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  • TY  - JOUR
    T1  - Analogy-Based Software Quality Prediction with Project Feature Weights
    AU  - Ekbal Rashid
    AU  - Srikanta Patnaik
    AU  - Vandana Bhattacharya
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    T2  - American Journal of Software Engineering and Applications
    JF  - American Journal of Software Engineering and Applications
    JO  - American Journal of Software Engineering and Applications
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    PB  - Science Publishing Group
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    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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Author Information
  • Department of CS & E CIT, Tatisilwai,Ranchi, India

  • Department of CS & E SOA University, Bhubaneswar, Orissa,India

  • Department of CS & E BIT Mesra, Ranchi, India

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