An automated Framework for Measuring the Code Readability to Maintain the Quality of Software
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Abstract
IT industry uses software metrics to evaluate the complexity of software systems to find software cost estimation, software development control, software assurance, software testing, and software maintenance. Taking the help of Human annotators much data has been collected to derive the relationship between a simple set of local code features and human concept of readability. In this paper, we explore the concept of code readability and investigate its relation to software quality. A Framework has been developed to evaluate proposed metrics and apply to the use of Bug counts which reduces the complexity of not capturing or missing even the small parts of the meaning of the attributes they are being used to measure. The constructed automated readability measure can be more effective than a human on average at predicting the judgment of readability. So, this paper strongly satisfies with three measures of software quality: Changes in the code, defect log messages, and automated defect reports.
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Keywords: Quality, Code Readability, Snippets, Annotators, Classifier.
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