An Efficient Predictive Paradigm for Software Reliability

Authors

  • Srivyshnavi Pagadala Assistant Professor (Senior), Department of Computer Science and Engineering, School of Engineering and Technology, Sri Padmavati Mahila Visva Vidyalayam, Tirupati, Andhra Pradesh, India
  • Sony Bathala Assistant Professor, Department of Computer Science and Engineering, School of Engineering and Technology, Sri Padmavati Mahila Visva Vidyalayam, Tirupati, Andhra Pradesh, India
  • B. Uma Assistant Professor, Department of Computer Science and Engineering, School of Engineering and Technology, Sri Padmavati Mahila Visva Vidyalayam, Tirupati, Andhra Pradesh, India

DOI:

https://doi.org/10.51983/ajcst-2019.8.S3.2051

Keywords:

Defect Prediction, Rayleigh Function, STLC

Abstract

Software Estimation gives solution for complex problems in the software industry which gives estimates for cost and schedule. Software Estimation provides a comprehensive set of tips and heuristics that Software Developers, Technical Leads, and Project Managers can apply to create more accurate estimates. It presents key estimation strategies and addresses particular estimation challenges. In the planning of a software development project, a major challenge faced by project managers is to predict the defects and effort. The Software defect plays critical role in software product development. The estimation of defects can be determined in the product development using many advanced statistical modelling techniques based on the empirical data obtained by the testing phases. The proposed estimation technique in this paper is a model which was developed using Rayleigh function for estimating effect of defects in Software Project Management. The present study offers to decide how many defects creep in to production and determine the effort spent in months. The estimation model was used on Software Testing Life Cycle (STLC) to complete product. The accuracy of the model explains the variation in spent efforts in months associated with number of defects. The model helps the senior management in estimating the defects, schedule, cost and effort.

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Published

28-05-2019

How to Cite

Pagadala, S., Bathala, S., & Uma, B. (2019). An Efficient Predictive Paradigm for Software Reliability. Asian Journal of Computer Science and Technology, 8(S3), 114–116. https://doi.org/10.51983/ajcst-2019.8.S3.2051