Software Metric and Back Propagation Techniques Applied in Fuzzy Logic

Authors

  • Zindhu S.
  • Aswini G.
  • Anusha Prem I.

Keywords:

Fuzzy Logic, Neural Network, Backpropgation, Software Metrics

Abstract

Software quality is one of the most important factors in the software development. It can be depends on many attributes. One of the best techniques in Fuzzy Logic is metrics and maintainability. This paper presents the application of fuzzy logic in software metrics. Software metric is the measurement of the software development process and product. It can be used as variables in the project management. The most common types of these models are predicting the development effort for a software system based on size, complexity, characteristics and metrics. There are many problems that have not been overcome using the traditional techniques of both formal and linear regression model. Once the problem faced by managers, who are using project metrics models is the elicitation of numerical inputs. These problems can be seen as collective failure of software measurement. The proposed techniques can help to overcome some of the difficulties by representing the imprecision in both input and output. This techniques especially fuzzy logic is investigated and some usable recommendation is made. Different levels of available information and desired precision can be used differently, mainly depends on current phase, although a single model can be used for consistency.

 

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How to Cite

S., Z., G., A., & Prem I., A. (2017). Software Metric and Back Propagation Techniques Applied in Fuzzy Logic. Asian Journal of Applied Sciences, 5(1). Retrieved from https://ajouronline.com/index.php/AJAS/article/view/4648

Issue

Vol. 5 No. 1 (2017): February 2017

Section

Articles

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