Paper Info
Title
A statistical comparison of Java and Python software metric properties.
Abstract
This paper presents a statistical analysis of 20 opens ource object-oriented systems with the purpose of detecting differences in metrics distribution between Java and Python projects. We selected ten Java projects from the Java Qualitas Corpus and ten projects written in Python. For each system, we considered 10 class-level software metrics. We performed a best fit procedure on the empirical distributions through the log-normal distribution and the double Pareto distribution to identify differences between the two languages. Even though the statistical distributions for projects written in Java and Python may appear the same for lower values of the metric, performing the procedure with the double Pareto distribution for the Number of Local Methods metric reveals that major differences can be noticed along the queue of the distributions. On the contrary, the same analysis performed with the Number of Statements metric reveals that only the initial portion of the double Pareto distribution shows differences between the two languages. In addition, the dispersion parameter associated to the log-normal distribution fit for the total Number Of Methods can be used for distinguishing Java projects from Python projects.
Year
DOI
Venue
2016
10.1145/2897695.2897697
WETSoM@ICSE
Keywords
Field
DocType
software metrics,java,python
Programming language,Scala,Pareto distribution,Computer science,Cyclomatic complexity,Theoretical computer science,Probability distribution,Software,Software metric,Java,Python (programming language)
Conference
ISSN
ISBN
Citations 
2327-0950
978-1-5090-2241-0
3
PageRank 
References 
Authors
0.42
14
5
Name
Order
Citations
PageRank
Giuseppe Destefanis123720.74
Marco Ortu226716.83
Simone Porru3314.88
Stephen Swift442731.32
Michele Marchesi5807120.28