2007•Unpublished venueRequires access

Correlations between Internal Software Metrics and Software Dependability in a Large Population of Small C/C++ Programs

Miguel A. Revilla

Open publisher page 58 citations

Abstract

Software metrics are often supposed to give valuable information for the development of software. In this paper we focus on several common internal metrics: Lines of Code, number of comments, Halstead Volume and McCabe's Cyclomatic Complexity. We try to find relations between these internal software metrics and metrics of software dependability: Probability of Failure on Demand and number of defects. The research is done using 59 specifications from a programming competition---The Online Judge--on the internet. Each specification provides us between 111 and 11,495programs for our analysis; the total number of programs used is 71,917. We excluded those programs that consist of a look-up table. The results for the Online Judge programs are: (1) there is a very strong correlation between Lines of Code and Hal- stead Volume; (2) there is an even stronger correlation between Lines of Code and McCabe's Cyclomatic Complexity; (3) none of the internal software metrics makes it possible to discern correct programs from incorrect ones; (4) given a specification, there is no correlation between any of the internal software metrics and the software dependability metrics.

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What this paper is about

Software metrics are often supposed to give valuable information for the development of software. In this paper we focus on several common internal metrics: Lines of Code, number of comments, Halstead Volume and McCabe's Cyclomatic Complexity. We try to find relations between these internal software metrics and metrics of software dependability: Probability of Failure on Demand and number of defects. The research is done using 59 specifications from a programming competition---The Online Judge--on the internet. Each specification provides us between 111 and 11,495programs for our analysis; the total number of programs used is 71,917. We excluded those programs that consist of a look-up table. The results for the Online Judge programs are: (1) there is a very strong correlation between Lines of Code and Hal- stead Volume; (2) there is an even stronger correlation between Lines of Code and McCabe's Cyclomatic Complexity; (3) none of the internal software metrics makes it possible to discern correct programs from incorrect ones; (4) given a specification, there is no correlation between any of the internal software metrics and the software dependability metrics.

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Available abstract

Software metrics are often supposed to give valuable information for the development of software. In this paper we focus on several common internal metrics: Lines of Code, number of comments, Halstead Volume and McCabe's Cyclomatic Complexity. We try to find relations between these internal software metrics and metrics of software dependability: Probability of Failure on Demand and number of defects. The research is done using 59 specifications from a programming competition---The Online Judge--on the internet. Each specification provides us between 111 and 11,495programs for our analysis; the total number of programs used is 71,917. We excluded those programs that consist of a look-up table. The results for the Online Judge programs are: (1) there is a very strong correlation between Lines of Code and Hal- stead Volume; (2) there is an even stronger correlation between Lines of Code and McCabe's Cyclomatic Complexity; (3) none of the internal software metrics makes it possible to discern correct programs from incorrect ones; (4) given a specification, there is no correlation between any of the internal software metrics and the software dependability metrics.

Key concepts: Cyclomatic complexity, Dependability, Computer science, Software metric, Source lines of code, Software engineering, Software development, Software

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