research-article

Neuro-Fuzzy Model to Estimate & Optimize Quality and Performance of Component Based Software Engineering

Authors:

Pradeep Kumar BhatiaAuthors Info & Claims

ACM SIGSOFT Software Engineering Notes, Volume 40, Issue 2

Pages 1 - 6

https://doi.org/10.1145/2735399.2735410

Published: 03 April 2015 Publication History

Abstract

Component Based Software Engineering (CBSE) constructs a quality software system by reusing existing components. For the construction of high-quality software system, reusability plays an important role. Software component should be designed and implemented in such a way that many different programs can reuse them. Reuse of software can increase the productivity and quality of software by reducing effort, time and cost which was elapsed in designing and developing reusable software component. In this paper, a Neuro-fuzzy model has been proposed that uses software component design patterns for analysis and Chidamber and Kemerer (CK) metric for evaluation, optimization and categorization of reusability for component based software. The work is divided into 2 phases. In the first phase, analysis and optimization of reusability are empirically evaluated with high precision value using CK metric and unsupervised Self Organizing Map (SOM) Neural Network. In the second phase, reusability is categorized as very low, low, medium, high and very high using a supervised Back propagation Neural Network (BPNN) and fuzzy inference rules applied on CK metric values. The proposed model may help a software designer to evaluate and optimize the reusability of components while designing software to make quality software system.

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Cited By

Roshani RMotameni HMohamadi H(2023)A decentralized method for initial populations of genetic algorithmsThe Journal of Supercomputing10.1007/s11227-023-05066-w79:9(10232-10251)Online publication date: 4-Feb-2023
https://doi.org/10.1007/s11227-023-05066-w
Banga ABhatia P(2021)Optimized Component based Selection using LSTM Model by Integrating Hybrid MVO-PSO Soft Computing TechniqueAdvances in Science, Technology and Engineering Systems Journal10.25046/aj0604086:4(62-71)Online publication date: Jul-2021
https://doi.org/10.25046/aj060408
Banga ABhatia P(2021)Software Component Selection in CBSE Considering Cost, Reliability, and Delivery Delay Using PSO-integrated MVO and ALOEmerging Research in Computing, Information, Communication and Applications10.1007/978-981-16-1342-5_36(455-479)Online publication date: 1-Dec-2021
https://doi.org/10.1007/978-981-16-1342-5_36
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Index Terms

Neuro-Fuzzy Model to Estimate & Optimize Quality and Performance of Component Based Software Engineering
1. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Probabilistic reasoning
      2. Vagueness and fuzzy logic
  2. Modeling and simulation
    1. Model development and analysis
2. Software and its engineering
  1. Software creation and management
    1. Designing software
      1. Software implementation planning
        Software design techniques
    2. Software development process management

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Published In

cover image ACM SIGSOFT Software Engineering Notes

ACM SIGSOFT Software Engineering Notes Volume 40, Issue 2

March 2015

125 pages

ISSN:0163-5948

DOI:10.1145/2735399

Editor:
Michael Wing

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Copyright © 2015 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 April 2015

Published in SIGSOFT Volume 40, Issue 2

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Cited By

Roshani RMotameni HMohamadi H(2023)A decentralized method for initial populations of genetic algorithmsThe Journal of Supercomputing10.1007/s11227-023-05066-w79:9(10232-10251)Online publication date: 4-Feb-2023
https://doi.org/10.1007/s11227-023-05066-w
Banga ABhatia P(2021)Optimized Component based Selection using LSTM Model by Integrating Hybrid MVO-PSO Soft Computing TechniqueAdvances in Science, Technology and Engineering Systems Journal10.25046/aj0604086:4(62-71)Online publication date: Jul-2021
https://doi.org/10.25046/aj060408
Banga ABhatia P(2021)Software Component Selection in CBSE Considering Cost, Reliability, and Delivery Delay Using PSO-integrated MVO and ALOEmerging Research in Computing, Information, Communication and Applications10.1007/978-981-16-1342-5_36(455-479)Online publication date: 1-Dec-2021
https://doi.org/10.1007/978-981-16-1342-5_36
Manju Bhatia P(2021)Dynamic Reusability Measurement Using Machine Learning Algorithms in Object-Oriented EnvironmentIntelligent Computing and Communication Systems10.1007/978-981-16-1295-4_40(393-399)Online publication date: 22-Jun-2021
https://doi.org/10.1007/978-981-16-1295-4_40
Eduardo Carbonera CFarias KBischoff V(2020)Software development effort estimation: a systematic mapping studyIET Software10.1049/iet-sen.2018.5334Online publication date: 3-Mar-2020
https://doi.org/10.1049/iet-sen.2018.5334
Saini GDubey SBharti S(2019)Novel algorithm for software planning & developmentProceedings of the Third International Conference on Advanced Informatics for Computing Research10.1145/3339311.3339315(1-7)Online publication date: 15-Jun-2019
https://dl.acm.org/doi/10.1145/3339311.3339315
Anisha Saini GKumar V(2018)An Adaptive Algorithm for User-Oriented Software EngineeringSmart Innovations in Communication and Computational Sciences10.1007/978-981-10-8971-8_3(29-37)Online publication date: 12-Jul-2018
https://doi.org/10.1007/978-981-10-8971-8_3
Gulia PPalak P(2017)Component Based Software Development Life Cycle Models: A Comparative ReviewOriental journal of computer science and technology10.13005/ojcst/10.02.3010:2(467-473)Online publication date: 3-Jun-2017
https://doi.org/10.13005/ojcst/10.02.30
Dubey SJasra B(2017)Reliability assessment of component based software systems using fuzzy and ANFIS techniquesInternational Journal of System Assurance Engineering and Management10.1007/s13198-017-0602-z8:S2(1319-1326)Online publication date: 21-Mar-2017
https://doi.org/10.1007/s13198-017-0602-z
Saini GDubey SBharti S(2017)Fuzzy-Based Algorithm for Resource AllocationProceedings of the 5th International Conference on Frontiers in Intelligent Computing: Theory and Applications10.1007/978-981-10-3153-3_7(69-77)Online publication date: 17-Mar-2017
https://doi.org/10.1007/978-981-10-3153-3_7

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