Algorithm of aggregation of software metrics and its application at testing of software.

Keywords: aggregation, software metrics, parameter, risk, testing, software, software code, cyclomatic complexity.

Abstract

. The algorithm of software metrics aggregation and its application in software testing is revealed in the article. The genesis of the formation of scientific thought on the aggregation of program metrics is determined. The methodology of software testing with the separation of the scheme of the software testing process is revealed. It is emphasized that as a basis for determining the levels of aggregation of software metrics in software testing, you should first determine the process and component blocks on the example of a testing system. It is emphasized that the aggregation of software metrics can be carried out at the level of decision making, at the level of compliance values and at the level of features and samples. It is noted that aggregation at the first and second levels occurs after the comparison tool is involved, while the third and fourth levels perform operations before the comparison device produces the resulting data. Mathematical properties of aggregation methods are described, namely, domain, range, invariance and decomposition. The algorithm of aggregation of program metrics to ratings, using threshold values on the basis of reference indicators is presented. The implementation of the algorithm is described step by step and the parametric values of the aggregation process are determined. It is emphasized that the reduction of individual measurements to ratings is carried out using a two-level process based on two types of thresholds, and individual measurements are combined in the risk profile using metric thresholds. At the same time, risk profiles are aggregated on a 5-point star scale using threshold values. Two-level aggregation, at the first level aggregation is carried out by calculating the relative size of the system falling under each risk category, at the second level combining risk profiles into a rating is carried out by determining the minimum rating for which the total relative size of all risk profile categories does not exceed a set of thresholds 2nd level. Dia software tested. The risk profile for Dia contains 73.3% of the code in low risk, 8.2% in moderate risk, 7.9% in high risk and 10.7% in very high risk. Using the interpolated function gives a rating value of 2.99, the rating for Dia has three stars.

References

Shatnawi, Raed. (2020). Comparison of threshold identification techniques for object-oriented software metrics. IET Software. 14. 10.1049/iet-sen.2020.0025.

Meng T. et al. (2020) A survey on machine learning for data fusion //Information Fusion. – 2020. – Т. 57. – С. 115-129.

Sicilia, M. & Sánchez-Alonso, Salvador & Mora-Cantallops, Marçal & Barriocanal, Elena. (2020). On the Source Code Structure of Quantum Code: Insights from Q# and QDK. 10.1007/978-3-030-58793-2_24.

Norris S. (2019) Systematically working with multimodal data: Research methods in multimodal discourse analysis. – John Wiley & Sons, 2019.

Liu, Zhengli & Li, Bing & Wang, Jian & Yang, Rong. (2020). Requirements engineering for crossover services: Issues, challenges and research directions. IET Software. 15. 10.1049/sfw2.12014.

Franco, Eduardo. (2020). A dynamical evaluation framework for technical debt management in software maintenance process. 10.11606/T.3.2020.tde-17052021-140104.

Broy, Manfred & Kuhrmann, Marco. (2021). Eigenschaften und Strukturen von Softwaresystemen. 10.1007/978-3-662-50263-1_2.

Falco, Mariana & Robiolo, Gabriela. (2021). Building a Catalogue of ISO/IEC 25010 Quality Measures Applied in an Industrial Context. Journal of Physics: Conference Series. 1828. 012077. 10.1088/1742-6596/1828/1/012077.

Serebrenik A, Roubtsov S, van den Brand MGJ. Dn-based architecture assessment of Java open source software systems. In ICPC ’09: Proc. 17th Int. Conf. on Program Comprehension, 2009, IEEE, 2009; 198–207.

Heitlager I, Kuipers T, Visser J. A practical model for measuring maintainability. In Proceedings of the 6th International Conference on Quality of Information and Communications Technology. IEEE Computer Society: Washington, DC, USA, 2007; 30–39

ISO/IEC 80000-2:2019 Quantities and units – Part 2: Mathematics. – https://www.iso.org/standard/64973.html

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Published
2021-10-29
How to Cite
Abharian , Y. (2021). Algorithm of aggregation of software metrics and its application at testing of software . COMPUTER-INTEGRATED TECHNOLOGIES: EDUCATION, SCIENCE, PRODUCTION, (44), 81-86. https://doi.org/10.36910/6775-2524-0560-2021-44-13
Section
Computer science and computer engineering