Novel Approach to Software Metrics

Software metrics are becoming important day by day. Many metrics have been defined and have been related to class coupling cohesion etc. First of all it is difficult to choose the correct metrics for particular software and secondly most of the metrics only cater to requirements phase. It is to be understood that the importance of software metrics cannot be undermined in the design and implementation phase also. The work discusses the various techniques, their merits and demerits and intends to propose a new system for measuring the goodness of implementation phase. The concept of Object Oriented Software Metrics has also been explored. The proposed metrics uses the concept of Genetic Algorithms, which are based on the theory of natural selection. Thus, the work intends to introduce natural selection techniques for measuring the quality of software. It is said that what can be measured can be studied. The concept is valid for all types of engineering including software engineering. Measurements in software are done using Software metrics. Software metric is a measure of some property of a piece of software or its specifications. Since quantitative measurements are essential in all sciences, there is a continuous effort by computer science practitioners and theoreticians to bring similar approaches to software development. The use of software metrics is primarily to determine the quality of software. However, they are also used not only to predict the quality of product or process, but also to improve the quality. There are many types of metrics ranging from object, component and aspect metrics. The following work throws some light on the various metrics also. The goal of the present work is Obtaining objective, reproducible and quantifiable measurements, which may have numerous valuable applications in schedule and budget planning, cost Estimation, quality assurance testing, software debugging, software performance optimization, and optimal personnel task assignments. The work proposes the use of genetic Algorithms in Metrics. The work proposes the use of Genetic Algorithms in Software metrics. Genetic Algorithms are based on the theory of natural selection and the survival of the fittest. The concept is to prioritize the various elements in a software and then apply GA to select the fittest whose value is representational as per as software is concerned. The idea can be a turning point as per as software measurements are concerned.