Using the Conceptual Cohesion of Classes for Fault Prediction in Object-Oriented Systems
By Andrian Marcus, Denys Poshyvanyk, Rudolf Ferenc. IEEE Transactions on Software Engineering, 2008
324 citations recorded by the source corpus.
Subfields: Information Systems, Software
View Paper: https://www.semanticscholar.org/paper/fa0e973286d4601c9ee3c349619902404d51287d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
- Ruchika Malhotra
- Richard Torkar
- M. Heričko
- Danijel Radjenovic
- Ales Zivkovic
- Cagatay Catal
- Romain Robbes
- Marco D'Ambros
In Software
- Ruchika Malhotra
- Richard Torkar
- M. Heričko
- Danijel Radjenovic
- Ales Zivkovic
- Cagatay Catal
- Romain Robbes
- Marco D'Ambros
Citations in the corpus
- Increasing diversity: Natural language measures for software fault prediction (2009, background): “introduce the non-structural measure Conceptual Cohesion of Classes for fault prediction (Marcus et al., 2008).”
- A systematic review of machine learning techniques for software fault prediction (2015, background): “Hence, total number of 122 studies [1, 2, 20-139] were identified for further processing and analysis.”
- Software fault prediction metrics: A systematic literature review (2013, methodology): “The predictive performance of cohesion metrics LCC and TCC [5] was estimated as modest by all ten studies [71,65,69,66,67,52,109, 53,56,55].”
- Software fault prediction: A literature review and current trends (2011, background): “Marcus, Poshyvanyk, and Ferenc (2008) proposed a new cohesion metric named Conceptual Cohesion of Classes (C3) in this study.”
- Evaluating defect prediction approaches: a benchmark and an extensive comparison (2011, methodology): “Marcus et al. (2008) used a cohesion measurement based on the vocabulary used in documents, as measured by Latent Semantic Indexing (LSI) for defect prediction on several C++ systems, including Mozilla.”
- An extensive comparison of bug prediction approaches (2010, methodology): “Marcus et al. used a cohesion measurement based on LSI for defect prediction on several C++ systems, including Mozilla [ 20 ].”
- On the relative value of cross-company and within-company data for defect prediction (2009, background): “As to the issue of conceptual connections within the code, we refer the reader to the concept location and cohesion work of Marcus et al. (2008).”