The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
An information retrieval approach to concept location in source code
Abstract
Concept location identifies parts of a software system that implement a specific concept that originates from the problem or the solution domain. Concept location is a very common software engineering activity that directly supports software maintenance and evolution tasks such as incremental change and reverse engineering. This work addresses the problem of concept location using an advanced information retrieval method, Latent Semantic Indexing (LSI). LSI is used to map concepts expressed in natural language by the programmer to the relevant parts of the source code. Results of a case study on NCSA Mosaic are presented and compared with previously published results of other static methods for concept location.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Indexing by latent semantic analysis
Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., & Harshman, R. (1990) · Journal of the American Society for Information Science · doi:10.1002/(sici)1097-4571(199009)41:6<391::aid-asi1>3.0.co;2-9 · Cited by 12,751
Introduction to Modern Information Retrieval
Salton, G., & McGill, M. J. (1983) · Virtual Defense Library (Ministerio de Defensa) · Cited by 9,680
An introduction to latent semantic analysis
Landauer, T. K., Foltz, P. W., & Laham, D. (1998) · Discourse Processes · doi:10.1080/01638539809545028 · Cited by 4,880
Automatic text processing: the transformation, analysis, and retrieval of information by computer
(1989) · Choice Reviews Online · doi:10.5860/choice.27-0351 · Cited by 3,188
Recovering traceability links between code and documentation
Antoniol, G., Canfora, G., Casazza, G., De Lucia, A., & Merlo, E. (2002) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2002.1041053 · Cited by 967
Locating features in source code
Eisenbarth, T., Koschke, R., & Simon, D. (2003) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2003.1183929 · Cited by 554
Recovering Documentation-to-Source-Code Traceability Links using Latent Semantic Indexing
Marcus, A., & Maletic, J. I. (2007) · Cited by 548
Self-citationRecovering documentation-to-source-code traceability links using latent semantic indexing
Marcus, A., & Maletic, J. I. (2003) · 25th International Conference on Software Engineering, 2003. Proceedings. · doi:10.1109/icse.2003.1201194 · Cited by 445
Self-citationAn information retrieval approach for automatically constructing software libraries
Maarek, Y. S., Berry, D. M., & Kaiser, G. E. (1991) · IEEE Transactions on Software Engineering · doi:10.1109/32.83915 · Cited by 442
Software reconnaissance: Mapping program features to code
Wilde, N., & Scully, M. C. (1995) · Journal of Software Maintenance: Research and Practice · doi:10.1002/smr.4360070105 · Cited by 373
Cited by
Zhou, J., Zhang, H., & Lo, D. (2012) · 2012 34th International Conference on Software Engineering (ICSE) · doi:10.1109/icse.2012.6227210 · Cited by 507
On the Use of Automated Text Summarization Techniques for Summarizing Source Code
Haiduc, S., Aponte, J., Moreno, L., & Marcus, A. (2010) · 2010 17th Working Conference on Reverse Engineering · doi:10.1109/wcre.2010.13 · Cited by 408
Self-citationEvaluating source code summarization techniques: Replication and expansion
Eddy, B. P., Robinson, J. A., Kraft, N. A., & Carver, J. C. (2013) · 2013 21st International Conference on Program Comprehension (ICPC) · doi:10.1109/icpc.2013.6613829 · Cited by 144
Using Data Fusion and Web Mining to Support Feature Location in Software
Revelle, M., Dit, B., & Poshyvanyk, D. (2010) · 2010 IEEE 18th International Conference on Program Comprehension · doi:10.1109/icpc.2010.10 · Cited by 105
Analyzing and mining a code search engine usage log
Bajracharya, S. K., & Lopes, C. V. (2012) · Empirical Software Engineering · doi:10.1007/s10664-010-9144-6 · Cited by 90
Metadata
- Authors
- Marcus, A., Sergeyev, A., Rajlich, V., & Maletic, J. I.
- Venue
- 11th Working Conference on Reverse Engineering
- Publisher
- IEEE Comput. Soc
- Published
- 2005-02-22
- Pages
- 214-223
- ISSN
- 1095-1350 (ISSN-L)
- OpenAlex
- W2110220994
- Cited by
- 455
- References
- 28
- FWCI
- 19.50
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: An information retrieval approach to concept location in source code. https://app.cochat.ai/papers/10.1109/wcre.2004.10
- The paper
- Marcus, A., Sergeyev, A., Rajlich, V., & Maletic, J. I. (2005). An information retrieval approach to concept location in source code. 11th Working Conference on Reverse Engineering. https://doi.org/10.1109/wcre.2004.10
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.
