Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen: http://dx.doi.org/10.25673/101921
Titel: Software Metrics Visualization
Autor(en): Liubchenko, Vira
Körperschaft: Hochschule Anhalt
Erscheinungsdatum: 2023
Umfang: 1 Online-Ressource (8 Seiten)
Sprache: Englisch
Zusammenfassung: Software engineering is an empirical field of study. To support managerial and technical decision-making, the engineer needs numerical measures closely connected with different software metrics. Visual representation of numerical data improves the effectiveness of human data processing and shows insights that humans may miss. This paper aims to provide a systematic review of the approaches for software metrics visualization and define the possible recommendation for their use. The study is based on the literature review of the papers from two text collections – IEEE Xplore and ACM Digital Library – and the scientometric database Scopus. After merging and filtering, the final set of publications contains 16 papers. Our study showed that there were the metrics used significantly more often; among them are lines-of-code, cyclomatic complexity, coupling, and cohesion. We were not able to identify such leaders for visualization means. Instead, there was a tendency to combine different metrics on one chart or dashboard to provide the whole process picture. Based on the results of empirical studies reported in the literature, we offered an analysis of simple charts’ properties and recommendations on their use for support decision-making in the software engineering process.
URI: https://opendata.uni-halle.de//handle/1981185920/103872
http://dx.doi.org/10.25673/101921
Open-Access: Open-Access-Publikation
Nutzungslizenz: (CC BY-SA 4.0) Creative Commons Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International(CC BY-SA 4.0) Creative Commons Namensnennung - Weitergabe unter gleichen Bedingungen 4.0 International
Enthalten in den Sammlungen:International Conference on Applied Innovations in IT (ICAIIT)

Dateien zu dieser Ressource:
Datei Beschreibung GrößeFormat 
2_4 ICAIIT_2023_paper_4502.pdf987.78 kBAdobe PDFMiniaturbild
Öffnen/Anzeigen