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An analysis of SNA metrics on the Java Qualitas Corpus

Published: 24 February 2011 Publication History

Abstract

We computed the software graphs of 96 systems of the Java Qualitas Corpus, parsing the source code and identifying the dependencies among classes.
We analyzed 12 software metrics on these 96 graphs, nine borrowed from Social Network Analysis (SNA), and three more traditional software metrics, such as Loc, Fan-in and Fan-out. We analyzed their correlations at system level, and studied the correlation statistics at data-set level.
Our results show that these correlations are independent from the specific software system and are general properties of Java software systems.
We show how the metrics can be partitioned in groups for almost the whole Java Qualitas Corpus, and that such grouping can provide insights on the topology of software networks.
For two systems, Eclipse and Netbeans, we computed also the number of bugs, identifying the bugs affecting each class, and finding that some SNA metrics are highly correlated with bugs, while others are strongly anticorrelated.
This suggests that practitioners and software engineers might take advantage of such metrics to keep control of software quality.

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Netbeans. http://www.netbeans.org/.
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Cited By

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  • (2018)Software structure evolution and relation to subgraph defectivenessIET Software10.1049/iet-sen.2018.5060Online publication date: 11-Dec-2018
  • (2014)Comparative Analysis of Software Network and CK Metrics: Implications for Pre- and Post-release FaultsJournal of Software10.4304/jsw.9.3.541-5529:3Online publication date: 1-Mar-2014
  • (2012)Micro Pattern Fault-PronenessProceedings of the 2012 38th Euromicro Conference on Software Engineering and Advanced Applications10.1109/SEAA.2012.63(302-306)Online publication date: 5-Sep-2012

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cover image ACM Other conferences
ISEC '11: Proceedings of the 4th India Software Engineering Conference
February 2011
229 pages
ISBN:9781450305594
DOI:10.1145/1953355
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • Computer Society of India: Computer Society of India

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 February 2011

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Author Tags

  1. SNA
  2. complex networks
  3. software metrics

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  • Research-article

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ISEC '11
Sponsor:
  • Computer Society of India
ISEC '11: Indian Software Engineering Conference
February 24 - 27, 2011
Kerala, Thiruvananthapuram, India

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Overall Acceptance Rate 76 of 315 submissions, 24%

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Cited By

View all
  • (2018)Software structure evolution and relation to subgraph defectivenessIET Software10.1049/iet-sen.2018.5060Online publication date: 11-Dec-2018
  • (2014)Comparative Analysis of Software Network and CK Metrics: Implications for Pre- and Post-release FaultsJournal of Software10.4304/jsw.9.3.541-5529:3Online publication date: 1-Mar-2014
  • (2012)Micro Pattern Fault-PronenessProceedings of the 2012 38th Euromicro Conference on Software Engineering and Advanced Applications10.1109/SEAA.2012.63(302-306)Online publication date: 5-Sep-2012

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