loading
Documents

Research.Publish.Connect.

Paper

Author: Xiaoxing Yang

Affiliation: School of Data and Computer Science, Sun Yat-Sen University, Guangzhou and China

ISBN: 978-989-758-379-7

ISSN: 2184-2833

Keyword(s): Software Defect Prediction, Sorting Modules in Order of Defect Count, Software Metrics, Correlation Analysis, Metric Analysis.

Abstract: Sorting software modules in order of defect count can help testers to focus on software modules with more defects. Many approaches have been proposed to accomplish this. In order to compare approaches more fairly, researchers have provided publicly available data sets. In this paper, we provide a new metric selection approach and evaluate the usefulness of software metrics of eleven publicly available data sets, in order to investigate the quality of these data sets and find out the software metrics that are most efficient for sorting modules in order of defect count. Unexpectedly, experimental results show that only one metric can work well over most of these data sets, which implies that more effective metrics should be introduced. We also obtain other findings from these data sets, which can help to introduce new metrics for sorting software modules in order of defect count to some extent.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.204.55.168

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Yang, X. (2019). Evaluating Software Metrics for Sorting Software Modules in Order of Defect Count.In Proceedings of the 14th International Conference on Software Technologies - Volume 1: ICSOFT, ISBN 978-989-758-379-7, ISSN 2184-2833, pages 94-105. DOI: 10.5220/0007924800940105

@conference{icsoft19,
author={Xiaoxing Yang.},
title={Evaluating Software Metrics for Sorting Software Modules in Order of Defect Count},
booktitle={Proceedings of the 14th International Conference on Software Technologies - Volume 1: ICSOFT,},
year={2019},
pages={94-105},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007924800940105},
isbn={978-989-758-379-7},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Software Technologies - Volume 1: ICSOFT,
TI - Evaluating Software Metrics for Sorting Software Modules in Order of Defect Count
SN - 978-989-758-379-7
AU - Yang, X.
PY - 2019
SP - 94
EP - 105
DO - 10.5220/0007924800940105

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic