Software Quality Measures as Degree of Excellence

Introduction

The objective of this chapter is to improve the degree of excellence by removing the number of exceptions from the software. The modern age is more concerned with the quality of software. The rate of improvement of quality of software largely depends on the development time. This development time is chiefly calculated in clock hours. However, development time does not reflect the effort put in by the developer. A better parameter can be the rate of improvement of quality level or the rate of improvement of degree of excellence with respect to time. Now this parameter needs the prediction of error level and degree of excellence at a particular stage of development of the software. This chapter explores an attempt to develop a system to predict rate of improvement of the software quality at a particular point of time with respect to the number of lines of code present in the software (Rashid, Patnaik, & Bhattacherjee, 2014). A machine or algorithm serves its purpose if it fulfills the task of generating quality products in short time. The dream of any engineer is to build machines fitted for this purpose. Researchers have engaged themselves with such tasks and this leads to the development of newer gadgets, devices and machines. Moreover, after the advent of computational machines, the task has also been to develop software that can handle different situations. So, a newer field of research has developed for software development. This field of research grew rapidly over the last decade and many sub-branches have emerged. There is the task of developing new software for newer tasks. Then there is the important area of development of computational languages. Among several others, there is also the need of working with the methodology of software development. This field in particular deals with the notion that what we need should not only be workable software, but should also be efficient. Efficiency amounts to a balance between using the least possible space and employing minimum run-time. So, algorithms and complexity theories emerged rapidly. Then there also emerged the urge to develop tools for programming and thus reducing the workload and stress of both the adept and ordinary programmer. This research work is focused on the two areas. That is, on one hand developing an algorithm that can be used by scientists as well as ordinary programmers to judge and produce software of the best quality, while on the other hand reduce the workload of the man and transfer his burden on the machine (Rashid, Patnaik, & Bhattacherjee, 2012). The main thrust in modern software engineering research is centered on trying to build tools that can enhance software quality. Software quality estimation models in software engineering are used to predict important attributes such as software development effort, software reliability, and productivity of programmers (Bhattacherjee & Kumar, 2005). Software quality prediction is a complex mix of characteristics that varies from application to application and users who request for it. A software quality prediction model can be used to identify the defective modules (Rashid, Patnaik, & Bhattacherjee, 2012). Although cost estimation and quality estimation may have relative independence, the two are dialectically dependent on one another. Cost reduction can be considered to some extent as a parameter of quality. At the same time, quality improvement is sure to affect the cost factor. The cost of software is related to the development time. However, the development time does not truly reflect the effort put in by the developer. A better method is to calculate the rate of improvement of software quality and the effort put in by a developer and to use it as a new parameter to provide a better understanding of the cost of a software. This chapter focuses upon the need and the methods to estimate the rate of improvement of software quality and the effort put in by the developer in the course of software development.