The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Recovering traceability links between code and documentation
Abstract
Software system documentation is almost always expressed informally in natural language and free text. Examples include requirement specifications, design documents, manual pages, system development journals, error logs, and related maintenance reports. We propose a method based on information retrieval to recover traceability links between source code and free text documents. A premise of our work is that programmers use meaningful names for program items, such as functions, variables, types, classes, and methods. We believe that the application-domain knowledge that programmers process when writing the code is often captured by the mnemonics for identifiers; therefore, the analysis of these mnemonics can help to associate high-level concepts with program concepts and vice-versa. We apply both a probabilistic and a vector space information retrieval model in two case studies to trace C++ source code onto manual pages and Java code to functional requirements. We compare the results of applying the two models, discuss the benefits and limitations, and describe directions for improvements.
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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
An information retrieval approach to concept location in source code
Marcus, A., Sergeyev, A., Rajlich, V., & Maletic, J. I. (2005) · 11th Working Conference on Reverse Engineering · doi:10.1109/wcre.2004.10 · Cited by 455
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
A survey of traceability in requirements engineering and model-driven development
Winkler, S., & von Pilgrim, J. (2010) · Software & Systems Modeling · doi:10.1007/s10270-009-0145-0 · Cited by 313
Software traceability: trends and future directions
Cleland-Huang, J., Gotel, O. C. Z., Huffman Hayes, J., Mäder, P., & Zisman, A. (2014) · Future of Software Engineering Proceedings · doi:10.1145/2593882.2593891 · Cited by 309
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
Metadata
- Authors
- Antoniol, G., Canfora, G., Casazza, G., De Lucia, A., & Merlo, E.
- Venue
- IEEE Transactions on Software Engineering
- Published
- 2002-10
- Volume
- 28
- Issue
- 10
- Pages
- 970-983
- ISSN
- 0098-5589 (ISSN-L)
- 1939-3520
- 2326-3881
- OpenAlex
- W2128581098
- Cited by
- 967
- References
- 2
- FWCI
- 47.87
- Type
- journal article
- Language
- en
- Open access
- closed
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- Antoniol, G., Canfora, G., Casazza, G., De Lucia, A., & Merlo, E. (2002). Recovering traceability links between code and documentation. IEEE Transactions on Software Engineering. https://doi.org/10.1109/tse.2002.1041053
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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.
