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An Empirical Evaluation of the Relationship between Technical Debt and Software Security

Title: An Empirical Evaluation of the Relationship between Technical Debt and Software Security
Authors: Siavvas, M
Tsoukalas, D
Janković, M
Kehagias, D
Chatzigeorgiou, A
Tzovaras, D
Aničić, N
Gelenbe, E
Item Type: Dataset
Abstract: This dataset contains the static analysis results of 50 open source software applications retrieved from Github. The results were produced by using SonarQube, PMD, CKJM Extended and Findbugs tools. Further details can be found in the relevant publication: Siavvas, M., Tsoukalas, D., Janković, M., Kehagias, D., Chatzigeorgiou, A., Tzovaras, D., Aničić, N., Gelenbe, E. An Empirical Evaluation of the Relationship between Technical Debt and Software Security. In: Konjović, Z., Zdravković, M., Trajanović, M. (Eds.) ICIST 2019 Proceedings Vol.1, pp.199-203, 2019
This dataset contains the static analysis results of 50 open source software applications retrieved from Github. The results were produced by using SonarQube, PMD, CKJM Extended and Findbugs tools. Further details can be found in the relevant publication: Siavvas, M., Tsoukalas, D., Janković, M., Kehagias, D., Chatzigeorgiou, A., Tzovaras, D., Aničić, N., Gelenbe, E. An Empirical Evaluation of the Relationship between Technical Debt and Software Security. In: Konjović, Z., Zdravković, M., Trajanović, M. (Eds.) ICIST 2019 Proceedings Vol.1, pp.199-203, 2019
Content Version: 1.0
Issue Date: 22-Aug-2019
Citation: 10.5281/zenodo.3379632
URI: http://hdl.handle.net/10044/1/74190
DOI: 10.5281/zenodo.3374712
Copyright Statement: https://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor/Funder: Commission of the European Communities
Funder's Grant Number: 780572
Keywords: software security
technical debt
vulnerability prediction
empirical study
static analysis
Notes: Grants: European Commission: SDK4ED - Software Development toolKit for Energy optimization and technical Debt elimination (780572)
Appears in Collections:Faculty of Engineering - Research Data