The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Program comprehension during software maintenance and evolution
Abstract
Code cognition models examine how programmers understand program code. The authors survey the current knowledge in this area by comparing six program comprehension models: the Letovsky (1986) model; the Shneiderman and Mayer (1979) model; the Brooks (1983) model; Soloway, Adelson and Ehrlich's (1988) top-down model; Pennington's (1987) bottom-up model; and the integrated metamodel of von Mayrhauser and Vans (1994). While these general models can foster a complete understanding of a piece of code, they may not always apply to specialized tasks that more efficiently employ strategies geared toward partial understanding. We identify open questions, particularly considering the maintenance and evolution of large-scale code. These questions relate to the scalability of existing experimental results with small programs, the validity and credibility of results based on experimental procedures, and the challenges of data availability.>
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Cites
Stimulus structures and mental representations in expert comprehension of computer programs
Pennington, N. (1987) · Cognitive Psychology · doi:10.1016/0010-0285(87)90007-7 · Cited by 526
Expertise in debugging computer programs: A process analysis
Vessey, I. (1985) · International Journal of Man-Machine Studies · doi:10.1016/s0020-7373(85)80054-7 · Cited by 359
Cited by
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
Questions programmers ask during software evolution tasks
Sillito, J., Murphy, G. C., & De Volder, K. (2006) · Proceedings of the 14th ACM SIGSOFT international symposium on Foundations of software engineering · doi:10.1145/1181775.1181779 · Cited by 270
Comparing Code Explanations Created by Students and Large Language Models
Leinonen, J., Denny, P., MacNeil, S., Sarsa, S., Bernstein, S., Kim, J., Tran, A., & Hellas, A. (2023) · Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V. 1 · doi:10.1145/3587102.3588785 · Cited by 210
Towards understanding programs through wear-based filtering
DeLine, R., Khella, A., Czerwinski, M., & Robertson, G. (2005) · Proceedings of the 2005 ACM symposium on Software visualization · doi:10.1145/1056018.1056044 · Cited by 91
Can Better Identifier Splitting Techniques Help Feature Location?
Dit, B., Guerrouj, L., Poshyvanyk, D., & Antoniol, G. (2011) · 2011 IEEE 19th International Conference on Program Comprehension · doi:10.1109/icpc.2011.47 · Cited by 89
Metadata
- Authors
- Von Mayrhauser, A., & Vans, A. M.
- Venue
- Computer
- Published
- 1995
- Volume
- 28
- Issue
- 8
- Pages
- 44-55
- ISSN
- 0018-9162 (ISSN-L)
- OpenAlex
- W2162363818
- Cited by
- 575
- References
- 2
- FWCI
- 18.30
- Type
- journal article
- Language
- en
- Open access
- closed
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- Von Mayrhauser, A., & Vans, A. M. (1995). Program comprehension during software maintenance and evolution. Computer. https://doi.org/10.1109/2.402076
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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