SIMPLIFIED READABILITY METRICS

Abstract

This paper describes a new approach to measuring the complexity of software systems with considering their readability. Readability Metrics were first proposed by Chung and Yung 181 in 1990. Software industry uses software metrics to measure the complexity of software systems for software cost estimation, software development control, software assurance, software testing, and software maintenance [3], [71, [9], 151, [18]. Most of the software metrics measure the software complexity by one or more of the software attributes. We usually class@ the software attributes that software metrics use for measuring complexity into three categories: size, control flow, and data flow [5], f71. All the three categories concern with the physical activities of software development. Readability Metrics have been outstanding among the existing software complexity metrics for taking nonphysical software attributes, like readability, into considerations [8]. The applications of Readability Metrics are good in indicating the additional efforts required for less readable software systems, and help in keeping the software systems maintainable. However, the numerous metrics and the complicated formulas in the family usually make it tedious to apply Readability Metrics to large scale software systems. In this paper, we propose a simplified approach to Readability Metrics. We reduce the number of required measures and keep the considerations on software readability. We introduce our Readability model in a more formal way. The Readability Metrics preprocesses algorithm is developed with compilers front-end techniques. The experiment results show that this simplified approach has good predictive power in measuring software complexity with software readability, in addition to its ease of applying. The applications of Readability Metrics indicate the readability of software systems and help in keeping the source code readable and maintainable.