Case Study Of GIPSY and MARF

TL;DR

This paper presents an experimental study analyzing software metrics for MARF and GIPSY systems to identify problematic classes and predict maintenance effort using various tools and metrics.

Contribution

It provides a comparative analysis of metrics applied to open source systems MARF and GIPSY using multiple tools and visualization techniques.

Findings

Identification of problematic classes using Kiviat graphs and Cyclomatic Complexity

Prioritized metrics for maintenance prediction based on tool analysis

Insights into metric effectiveness for open source systems

Abstract

Metrics are used mainly to predict software engineering efforts such as maintenance effort, error Prone ness, and error rate. This document emphasis on experimental study based on two open source systems namely MARF and GIPSY. With the help of various research papers we were able to analyze and give priorities to various metrics that are implemented with JDeodrant. LOGISCOPE and McCabe tools are used to identify problematic classes with help of Kiviat graph and average Cyclomatic Complexity that further are implemented with highest priority metric with JDeodrant. To obtain accurate results we collected data using different tools. The analysis of the two systems is done as a conclusion of study using different tools.