Abstract
To make software better in view of its maintainability, its software development process must be controlled and continuously observed. Researchers and software managers have stressed on the early measurement of maintainability starting from design phase itself so that timely steps could be taken for producing maintainable software. This paper evaluates and compares several methodologies for improving the numerical stability of a fuzzy-logic-based maintainability metrics system. Fuzzy parameters are adjusted using heuristic methods. A number of alternates were considered, in which training data sets were generated using different methods and these sets were used to evaluate objective functions in GA and accordingly fuzzy parameters were tuned. After conditioning, real projects’ maintainability data is used to show that fuzzy model performance is increased, however marginally, after conditioning
Highlights
Software is described by several characteristics in its quality domain such as test-ability, maintainability, flexibility etc
When contributing attributes are of diverse nature and are hard to be converted into a single crisp value it is very difficult to identify a mathematical model or formula
Several fuzzy based integrated measures have come up in the literature [3] [4]. Maintainability is one such hy-brid attribute, whose crisp value depends on many lower order attributes such as source code size, comment ratio, software complexity, source code readability, documentation quality etc
Summary
Software is described by several characteristics in its quality domain such as test-ability, maintainability, flexibility etc. As there are several diverse attributes collected from different artifacts of software, which are distinct in measurement and performance scale, efforts are made to integrate these, in order to get a single crisp value of maintainability For this type of integration fuzzy modeling was used by several authors [3]. Model under Consideration For assessment four-input-boundaries practicality measurements is processed with assistance of a fuzzy model proposed by Aggarwal et al [3] In these writers have considered normal average cyclomatic complexity (ACC), readability of source code (RSC), Documents quality (DOQ) and understandability of software (UOS) as significant ascribes for the estimation of viability. Our investigation inferred that framework can be made steadier to sudden changes by tuning boundaries of a framework dependent on condition number rule This criterion has special rele-vance where previous modeling experience and/or data is unavailable. The results in previous paper were quite encouraging and prompted us to experiment with new alternatives of different training data sets and try to find out the best method for tuning MFs of fuzzy sys-tem with minimum condition number
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