Design and Analysis of Some Software Metrics Using Soft Computing Approaches

Abstract

Introduction Software metrics are the integral part of software engineering to quantify activities during the different phases of software development life cycle. The quantification processes consist of the measurements of entities which need to be analyzed during the software development processes. In software engineering, these entities are called software metrics, which are measured in all the phases of software development life cycle. There are defined processes and product metrics which contain various attributes to be measured. Direct measurement is not possible for some software metrics; hence these metrics are derived using a combination of different metrics attributes. For example, size metric is a direct measure and complexity is indirect measure, which depends on a combination of different factors. Software metrics measurement has been a great research interest area for last four decades. The different conventional statistical methods have been proposed for analysis and measurements of the software attributes. Regression analysis is frequently used method for software attributes analysis. Although conventional methodologies are most widely used in the industries worldwide but recently the research communities are moving towards interdisciplinary streams and have started exploring the unconventional techniques such as fuzzy logic, artificial neural network, neuro-fuzzy etc. There are some metrics attributes, which needs forecasting i.e., the occurrence in future for better process improvement in advance. Some of these metrics are software quality, reliability, maintainability, reusability, defect density and many more. There is no direct measurement possible with the fixed mathematical concept for most of these attributes. So, the term prediction comes into consideration in software engineering. The prediction is nothing but the forecasting and quantification of these attributes which are based on the available information during the software development process at any point of time.