An Empirical Study of Source Level Complexity

Author

Liu Xiao

Author_Institution

Fac. of Sci., Chulalongkorn Univ., Bangkok, Thailand

fYear

2013

fDate

21-23 June 2013

Firstpage

1991

Lastpage

1994

Abstract

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.

Keywords

program compilers; program interpreters; programming languages; software metrics; compiled languages; interpreted languages; programming languages; software complexity; software development lifecycle; software metrics; software organizations; software source code maintenance; software source code operation; software source code quality; source level complexity evaluation method; Complexity theory; Flow graphs; Java; Measurement; Software; Standards; compiled language; interpreted language; software metrics; source code complexity;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational and Information Sciences (ICCIS), 2013 Fifth International Conference on

Conference_Location

Shiyang

Type

conf

DOI

10.1109/ICCIS.2013.520

Filename

6643439