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Component Selection Efforts Estimation– A Fuzzy Logic Based Approach
Kirti Seth, Arun Sharma, Ashish Seth
Pages - 210 - 215     |    Revised - 05-08-2009     |    Published - 01-09-2009
Volume - 3   Issue - 3    |    Publication Date - June 2009  Table of Contents
Component, Component Based software Engineering, Selection Efforts, Reusability, Fuzzy Rule Base.
Effort Estimation with good accuracy helps in managing overall budgeting and planning. The accuracy of these estimates is very less and most difficult to obtain, because no or very little detail about the project is known at the beginning. Due to architectural difference in CBS (Component Based Systems), this estimation becomes more crucial. CBS mainly involves two types of efforts: selection and integration. Present paper presents a fuzzy rule based model for estimating the efforts in selecting these Components for developing an application using CBSE approach.
CITED BY (15)  
1 Fatima, M., Ahmad, S. F., & Hasan, M. (2015). Fuzzy Based Software Cost Estimation Methods: A Comparative Study. International Journal for Innovative Research in Science and Technology, 1(7), 287-290.
2 Iraji, M. S. (2015). Fuzzy Agent Oriented Software Effort Estimate with COCOMO.
3 Bhatia, S. M., & Sharma, A. K. (2014). Fuzzy Quality Function Deployment and Software Engineering-A Literature Review. Software Engineering and Technology, 6(6), 159-168.
4 Rai, D., & Tyagi, K. (2013, July). Estimating the regression test case selection probability using fuzzy rules. In Recent Trends in Information Technology (ICRTIT), 2013 International Conference on (pp. 603-611). IEEE.
5 Pauline, M., Aruna, P., & Shadaksharappa, B. (2013). Layered model to Estimate Effort, Performance and cost of the Software projects. International Journal of Computer Applications, 63(13), 17-23.
6 Elgamel, M. S., Korani, E. A., & El Helow, K. R. Developing a Software Certification for Quality Assurance.
7 Pauline, M., Aruna, P., & Shadaksharappa, B. (2012). Fuzzy-Based Approach Using Enhanced Function Point to Evaluate the Performance of Software Project. IUP Journal of Computer Sciences, 6(2), 20.
8 Nazir, S., Khan, M. A., Anwar, S., Khan, H., & Nazir, M. (2012, May). A novel fuzzy logic based software component selection modeling. In Information Science and Applications (ICISA), 2012 International Conference on (pp. 1-6). IEEE.
9 KUMAR, M. S. R., & SivaSubramanian, S. An Approach towards Developing an Efficient Software Cost Estimation System Using Fuzzy and Analogy Methods.
10 Pauline, M., Aruna, P., & Shadaksharappa, B. an enhanced model to estimate effort, performance and cost of the software projects.
11 PVGD, P. R. (2010). Particle swarm optimization in the fine-tuning of fuzzy software cost estimation models. International Journal of Software Engineering (IJSE), 1(2), 12-23.
12 Asghar, S., & Umar, M. (2010). Requirement engineering challenges in development of software applications and selection of customer-off-the-shelf (COTS) components. International Journal of Software Engineering, 1(1), 32-50.
13 P. Reddy , K.R. Sudha , P. R. Sree and Ramesh, “Fuzzy Based Approach for Predicting Software Development Effort”, International Journal of Software Engineering (IJSE), 1(1), pp. 1 - 11, 2010.
14 S. Asghar and M. Umar, “Requirement Engineering Challenges in Development of Software Applications and Selection of Customer-off-the-Shelf (COTS) Components”, International Journal of Software Engineering (IJSE), 1(2), pp. 32 – 50, 2010.
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Mr. Kirti Seth
UPTU - India
Professor Arun Sharma
- India
Mr. Ashish Seth
- India

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