Evaluating Software Complexity Measures
By Elaine J. Weyuker. IEEE Trans. Software Eng., 2010
958 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems, Software
View Paper: https://www.semanticscholar.org/paper/f34949d8aa42b3b55e77ed00937c0920f97c0f22
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
- Ahmed E. Hassan
- Jeannette M. Wing
- Chris F. Kemerer
- Pratyusa K. Manadhata
- Shyam R. Chidamber
- Raymond P. L. Buse
- Westley Weimer
- Charles Sutton
In Information Systems
- Westley Weimer
- Ahmed E. Hassan
- Jeannette M. Wing
- Chris F. Kemerer
- Pratyusa K. Manadhata
- Shyam R. Chidamber
- Raymond P. L. Buse
- Romain Robbes
In Software
- Westley Weimer
- Ahmed E. Hassan
- Jeannette M. Wing
- Chris F. Kemerer
- Pratyusa K. Manadhata
- Shyam R. Chidamber
- Raymond P. L. Buse
- Shane McIntosh
Citations in the corpus
- An Attack Surface Metric (2011, background): “Validating a software attribute’s measure is hard [17], [18], [19]; security is an attribute that is hard to measure and hence even harder to validate.”
- Predicting faults using the complexity of code changes (2009, methodology): “Whereas our model quantifies the complexity of the code change process as calculated from the source code modification statistics, previous studies [1, 4, 6, 12, 36] quantify the complexity of the source code.”
- Learning a Metric for Code Readability (2010, background): “A consensus exists that readability is an essential determining characteristic of code quality [1], [4], [8], [9], [10], [15], [30], [31], [32], [33], [34], [ 40 ], but not about”
- A Metrics Suite for Object Oriented Design (2015, positive): “These include: lacking a theoretical basis [41], lacking in desirable measurement properties [47], being insufficiently generalized or too implementation technology dependent [45], and being too labor-intensive to collect [22].”