Evaluation of Software Product Quality Metrics

September 03, 2020 Β· Declared Dead Β· πŸ› International Conference on Evaluation of Novel Approaches to Software Engineering

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Arthur-Jozsef Molnar, Alexandra NeamΕ£u, Simona Motogna arXiv ID 2009.01557 Category cs.SE: Software Engineering Citations 9 Venue International Conference on Evaluation of Novel Approaches to Software Engineering Last Checked 4 months ago
Abstract
Computing devices and associated software govern everyday life, and form the backbone of safety critical systems in banking, healthcare, automotive and other fields. Increasing system complexity, quickly evolving technologies and paradigm shifts have kept software quality research at the forefront. Standards such as ISO's 25010 express it in terms of sub-characteristics such as maintainability, reliability and security. A significant body of literature attempts to link these subcharacteristics with software metric values, with the end goal of creating a metric-based model of software product quality. However, research also identifies the most important existing barriers. Among them we mention the diversity of software application types, development platforms and languages. Additionally, unified definitions to make software metrics truly language-agnostic do not exist, and would be difficult to implement given programming language levels of variety. This is compounded by the fact that many existing studies do not detail their methodology and tooling, which precludes researchers from creating surveys to enable data analysis on a larger scale. In our paper, we propose a comprehensive study of metric values in the context of three complex, open-source applications. We align our methodology and tooling with that of existing research, and present it in detail in order to facilitate comparative evaluation. We study metric values during the entire 18-year development history of our target applications, in order to capture the longitudinal view that we found lacking in existing literature. We identify metric dependencies and check their consistency across applications and their versions. At each step, we carry out comparative evaluation with existing research and present our results.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Software Engineering

Died the same way β€” πŸ‘» Ghosted