2017 5th Intl Conf on Applied Computing and Information Technology/4th Intl Conf on Computational Science/Intelligence and Applied Informatics/2nd Intl Conf on Big Data, Cloud Computing, Data Science (ACIT-CSII-BCD) /

While static code analysis tools would be helpful in reviewing source code, they have not been actively utilized in practice. One of main reasons why they are not used by practitioners has been said that such tools output many warnings (violations to predefined rules) but most of them are false posi...

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Weitere Titel:
2017 5th Intl Conf on Applied Computing and Information Technology/4th Intl Conf on Computational Science/Intelligence and Applied Informatics/2nd Intl Conf on Big Data, Cloud Computing, Data Science
Körperschaft:
Institute of Electrical and Electronics Engineers (IEEE)
Format:
Elektronisch E-Book
Sprache:
Englisch
Veröffentlicht:
Piscataway, New Jersey : Institute of Electrical and Electronics Engineers (IEEE), 2017.
Zusammenfassung:
While static code analysis tools would be helpful in reviewing source code, they have not been actively utilized in practice. One of main reasons why they are not used by practitioners has been said that such tools output many warnings (violations to predefined rules) but most of them are false positive. Thus, there have been studies evaluating violations in the past. This paper focuses on one of such studies, which evaluates violations using their change patterns over releases. Then, the paper examines an impact of authorship on those violation evaluations because a preference of a certain programmer may have an affect on a creation or modification of violation. This paper collects violations made by a popular static code analysis tool, PMD, from seven open source software projects. The set of collected data is divided into two subsets according to the authorship of source file: the set of violations appearing in source files which have been developed and maintained by a single programmer (single-authored files) vs. the set of ones appearing in source files which have been done by two or more programmers (multi-authored files). The results of data analyses show the following findings: (1) the difference in the authoring type has significant impacts on the trends of violations and their evaluations; (2) while important violations tend to vary from project to project and from person to person, about 30% of violations would be commonly worthless across projects for many programmers.
Umfang:
1 online resource : illustrations
ISBN:
9781538633021
1538633027
Schlagworte:
Big data > Congresses.
Computer engineering > Congresses.
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