COMPARATIVE ANALYSIS OF TOOLS FOR STATIC CODE ANALYSIS FOR THE PURPOSE OF IDENTIFICATION AND ESTIMATION OF TECHNICAL DEBT IN .NET PROJECTS
DOI:
https://doi.org/10.24867/18OI01StankovicKeywords:
Technical debt, Static code analysis toolsAbstract
This research examines the existing tools for static code analysis with the aim of identifying and estimating the amount of technical debt in .NET projects. The tools that were tested were: SonarCloud, Squore, NDepend and Sonargraph. The aim of the research is to compare the obtained amount of technical debt in the source code in order to get a picture of the precision (reliability) of the estimation of technical debt that these tools provide.
References
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[2] N. T. R. R. S. F. N. R. B. P. C. D. C. A. P. G. L. C. I. D. F. C. S. R. S. V. Mandic, „Technical and Nontechnical Prioritization Schema for Technical Debt: Voice of TD-Experienced Practitioners,“ IEEE SOFTWARE, 2021..
[3] R. L. N. I. O. P. Kruchten, „Technical Debt: From Metaphor to Theory and Practice,“ IEEE SOFTWARE, 2012..
[4] R. B. S. M. A. Z. M. Beller, „Analyzing the State of Static Analysis: A Large-Scale Evaluation in Open Source Software,“ 2016..
[5] E. M. A. M. R. S. A. T. F. A. Fontana, „An experience report on using code smells detection tools,“ u Fourth International Conference on Software Testing, Verification and Validation Workshops, 2011..
[6] M. W. Suman, „A Comparative Study of Software Quality Models,“ International Journal of Computer Science and Information Technologies, t. 5, 2014.
[7] C. I. C. H. Isaac Griffith, „An Industry Perspective to Comparing the SQALE and Quamoco Software Quality Models,“ 2017.
[8] D. R. C. I. Z. C. A. D. B. W. Isaac Griffith, „The Correspondence between Software Quality Models and Technical Debt Estimation Approaches,“ u 2014 6th IEEE International Workshop on Managing Technical Debt, 2014.
[9] L. F. R. V. C. T. S. M. R. O. S. Nicolli S. R. Alves, „Towards an Ontology of Terms on Technical Debt,“ 2014.
[10] E. B. Rini van Solingen, The Goal/Question/Metric Method: a practical guide for quality improvement of software development, McGraw-Hill Publishing Company, 1999..
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Published
2022-08-08
Issue
Section
Information Systems Engineering
