The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Automatically detecting and describing high level actions within methods
Abstract
One approach to easing program comprehension is to reduce the amount of code that a developer has to read. Describing the high level abstract algorithmic actions associated with code fragments using succinct natural language phrases potentially enables a newcomer to focus on fewer and more abstract concepts when trying to understand a given method. Unfortunately, such descriptions are typically missing because it is tedious to create them manually.
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Cites
Towards automatically generating summary comments for Java methods
Sridhara, G., Hill, E., Muppaneni, D., Pollock, L., & Vijay-Shanker, K. (2010) · Proceedings of the IEEE/ACM international conference on Automated software engineering · doi:10.1145/1858996.1859006 · Cited by 514
Self-citation
Cited by
On the naturalness of software
Hindle, A., Barr, E. T., Su, Z., Gabel, M., & Devanbu, P. (2012) · 2012 34th International Conference on Software Engineering (ICSE) · doi:10.1109/icse.2012.6227135 · Cited by 425
Measuring Program Comprehension: A Large-Scale Field Study with Professionals
Xia, X., Bao, L., Lo, D., Xing, Z., Hassan, A. E., & Li, S. (2018) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2017.2734091 · Cited by 326
On the naturalness of software
Hindle, A., Barr, E. T., Gabel, M., Su, Z., & Devanbu, P. (2016) · Communications of the ACM · doi:10.1145/2902362 · Cited by 307
Tu, Z., Su, Z., & Devanbu, P. (2014) · Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering · doi:10.1145/2635868.2635875 · Cited by 238
Improving automated source code summarization via an eye-tracking study of programmers
Rodeghero, P., McMillan, C., McBurney, P. W., Bosch, N., & D'Mello, S. (2014) · Proceedings of the 36th International Conference on Software Engineering · doi:10.1145/2568225.2568247 · Cited by 198
Semantic similarity metrics for evaluating source code summarization
Haque, S., Eberhart, Z., Bansal, A., & McMillan, C. (2022) · Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension · doi:10.1145/3524610.3527909 · Cited by 116
Unveiling ChatGPT’s usage in open source projects: A mining-based study
Tufano, R., Mastropaolo, A., Pepe, F., Dabic, O., Di Penta, M., & Bavota, G. (2024) · Proceedings of the 21st International Conference on Mining Software Repositories · doi:10.1145/3643991.3644918 · Cited by 38
Metadata
- Authors
- Sridhara, G., Pollock, L., & Vijay-Shanker, K.
- Venue
- Proceedings of the 33rd International Conference on Software Engineering
- Publisher
- ACM
- Published
- 2011-05-21
- Pages
- 101-110
- ISSN
- 0270-5257 (ISSN-L)
- OpenAlex
- W2166879716
- Cited by
- 182
- References
- 1
- FWCI
- 9.37
- Type
- conference paper
- Language
- en
- Open access
- closed
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
