  This literature focuses on doing a comparative analysis between Modular Audio
Recognition Framework (MARF) and the General Intentional Programming System
(GIPSY) with the help of different software metrics. At first, we understand
the general principles, architecture and working of MARF and GIPSY by looking
at their frameworks and running them in the Eclipse environment. Then, we study
some of the important metrics including a few state of the art metrics and rank
them in terms of their usefulness and their influence on the different quality
attributes of a software. The quality attributes are viewed and computed with
the help of the Logiscope and McCabe IQ tools. These tools perform a
comprehensive analysis on the case studies and generate a quality report at the
factor level, criteria level and metrics level. In next step, we identify the
worst code at each of these levels, extract the worst code and provide
recommendations to improve the quality. We implement and test some of the
metrics which are ranked as the most useful metrics with a set of test cases in
JDeodorant. Finally, we perform an analysis on both MARF and GIPSY by doing a
fuzzy code scan using MARFCAT to find the list of weak and vulnerable classes.
