Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Software Reliability Growth Model using Testing coverage, Function point and Test point analysis

Author : Amol K. Kadam 1 Dr. Shashank D. Joshi 2 Sachin B. Wakurdekar 3

Date of Publication :21st March 2018

Abstract: Testing is an important activity to ensure software quality but long time testing may not insure bug free software and high reliability. Optimum amount of code also need to be covered to make sure that software is of good quality and high reliability. In these proposed Software Reliability Growth Model analyze all codes files of the project. In this model every code file of the project is analyze and provide the suggestion to the user for improving performance of the system. Also this model calculate the cost of the project that cannot be calculate at existing software reliability growth model. This model focused on testing time, testing coverage, functional point analysis and test point analysis to increases the reliability of software, calculate software cost and optimize the software maintenance cost.

Reference :

    1. Yamada, Shigeru, Mitsuru Ohba, and Shunji Osaki. "Sshaped reliability growth modeling for software error detection." IEEE Transactions on reliability 32.5 (1983): 475-484.
    2. Malaiya, Y. K., Li, M. N., Bieman, J. M., & Karcich, R. (2002). Software reliability growth with test coverage. IEEE Transactions on Reliability, 51(4), 420-426.
    3. Pham, H., & Zhang, X. (2003). NHPP software reliability and cost models with testing coverage. European Journal of Operational Research, 145(2), 443- 454.
    4. Ledoux, J. (2003). Software reliability modeling. Handbook of Reliability Engineering, 213-234. 
    5. Zheng, J. (2009). Predicting software reliability with neural network ensembles. Expert systems with applications, 36(2), 2116-2122.
    6. Martens, A., Koziolek, H., Becker, S., & Reussner, R. (2010, January). Automatically improve software architecture models for performance, reliability, and cost using evolutionary algorithms. In Proceedings of the first

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