Design for Software Risk Management Using Soft Computing and Simulated Biological Approach

1. Introduction

The process of software defects based engineering and associated prediction is one of the key tasks while developing the effectual software products. Software Defect Prediction (Lyytinen et al. 2016; Gao et al., 2011; Turhan et al., 2007) in software engineering used to predict the deformity in the software module. Numbers of defect are present during the development or after the delivery of software module. To obtain high quality software the prediction process is followed to predict to the defects. The overall performance and defect free software create huge loyalty and faith of the client. Few big organizations are using this prediction process as they release their software and software versions frequently and they have less time so instead of manually predicting the defects they use software analysis process.

The work on the nature inspired approaches are not quite new and widely variety of algorithms are available even for other engineering domains. Using such approaches the higher degree of accuracy can be achieved with the greater values in the outcomes. In this research work, the presentation of the nature inspired approaches towards the specific scenarios of software quality are depicted and found that the greater accuracy can be achieved using such approaches.

Following Table 1 shows there is a relative strength and weaknesses of four risk management approaches. The following Table 1 is presenting the risk management approaches and the criteria towards the performance issues like what are the listing criteria, making a list of risk against actions, any strategic modeling and analysis of the strategies made.