Пожалуйста, используйте этот идентификатор, чтобы цитировать или ссылаться на этот ресурс:
http://dspace.opu.ua/jspui/handle/123456789/15454
Название: | Software metrics visualization |
Авторы: | Liubchenko, Vira Любченко, Віра Вікторівна |
Ключевые слова: | metrics software visualization data diagrams analysis decision making effectiveness |
Дата публикации: | 2023 |
Издательство: | Anhalt University of Applied Sciences |
Библиографическое описание: | Liubchenko, V. (2023). Software metrics visualization. Proceedings of International Conference on Applied Innovation in IT, Volume 11, Issue 1, P. 81-87. |
Краткий осмотр (реферат): | 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 (Унифицированный идентификатор ресурса): | http://dspace.opu.ua/jspui/handle/123456789/15454 |
ISSN: | 21998876 |
Располагается в коллекциях: | 2023 |
Файлы этого ресурса:
Файл | Описание | Размер | Формат | |
---|---|---|---|---|
2_4 ICAIIT_2023_paper_4502.pdf | 710.83 kB | Adobe PDF | Просмотреть/Открыть |
Все ресурсы в архиве электронных ресурсов защищены авторским правом, все права сохранены.