Object-Oriented Software Metrics

By J. Polgar. Encyclopedia of Information Science and Technology, 2005

500 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

View Paper: https://www.semanticscholar.org/paper/c374304740a61db84a7363547c0b843412103f89

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. M. Heričko
2. Ruchika Malhotra
3. Danijel Radjenovic
4. Richard Torkar
5. Ales Zivkovic
6. Radu Marinescu
7. Yann-Gaël Guéhéneuc

In Information Systems

1. M. Heričko
2. Ruchika Malhotra
3. Danijel Radjenovic
4. Richard Torkar
5. Ales Zivkovic
6. Radu Marinescu
7. Yann-Gaël Guéhéneuc
8. Massimiliano Di Penta

Citations in the corpus

• Software fault prediction metrics: A systematic literature review (2013, background): “This, however, can be a difficult task to accomplish when there is a large choice of metrics with no clear distinction regarding their usability.”
• A systematic review of machine learning techniques for software fault prediction (2015, methodology): “ Studies using Object-Oriented Metrics: These studies use metrics that measure various attributes of Object-Oriented (OO) software like cohesion, coupling and inheritance for an OO class [13-15].”
• Detection strategies: metrics-based rules for detecting design flaws (2004, background): “In most of the cases setting the threshold values is highly empirical process and it is guided by similar past experiences and by hints from metrics’ authors [19].”