An Empirical Study of Source Level Complexity

Software metrics are developed and used by the various software organizations for evaluating and assuring software source code quality, operation, and maintenance. Software metrics measure various types of software complexity like source size, control flow and data flow metrics. Software metrics can be used in different phases of the software development lifecycle. This paper proposes a novel source level complexity evaluation method by using different metrics included in programs written in different programming languages. Experiments show that source codes written in compiled languages have greater complexity than those written in interpreted languages.