The DOI matches its Crossref record.
Software reuse
Abstract
Software reuse is the process of creating software systems from existing software rather than building software systems from scratch. This simple yet powerful vision was introduced in 1968. Software reuse has, however, failed to become a standard software engineering practice. In an attempt to understand why, researchers have renewed their interest in software reuse and in the obstacles to implementing it. This paper surveys the different approaches to software reuse found in the research literature. It uses a taxonomy to describe and compare the different approaches and make generalizations about the field of software reuse. The taxonomy characterizes each reuse approach in terms of its reusable artifacts and the way these artifacts are abstracted, selected, specialized, and integrated . Abstraction plays a central role in software reuse. Concise and expressive abstractions are essential if software artifacts are to be effectively reused. The effectiveness of a reuse technique can be evaluated in terms of cognitive distance —an intuitive gauge of the intellectual effort required to use the technique. Cognitive distance is reduced in two ways: (1) Higher level abstractions in a reuse technique reduce the effort required to go from the initial concept of a software system to representations in the reuse technique, and (2) automation reduces the effort required to go from abstractions in a reuse technique to an executable implementation. This survey will help answer the following questions: What is software reuse? Why reuse software? What are the different approaches to reusing software? How effective are the different approaches? What is required to implement a software reuse technology? Why is software reuse difficult? What are the open areas for research in software reuse?
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
Cited by
A classification and comparison framework for software architecture description languages
Medvidovic, N., & Taylor, R. N. (2000) · IEEE Transactions on Software Engineering · doi:10.1109/32.825767 · Cited by 1,987
Large language models for software engineering: survey and open problems
Fan, A., Gokkaya, B., Harman, M., Lyubarskiy, M., Sengupta, S., Yoo, S., & Zhang, J. M. (2023) · 2023 IEEE/ACM International Conference on Software Engineering: Future of Software Engineering (ICSE-FoSE) · doi:10.1109/icse-fose59343.2023.00008 · Cited by 650
Large Language Models for Software Engineering: Survey and Open Problems
Fan, A., Gokkaya, B., Harman, M., Lyubarskiy, M., Sengupta, S., Yoo, S., & Zhang, J. M. (2023) · arXiv · doi:10.48550/arxiv.2310.03533 · Cited by 523
EON: A Component-Based Approach to Automation of Protocol-Directed Therapy
Musen, M. A., Tu, S. W., Das, A. K., & Shahar, Y. (1996) · Journal of the American Medical Informatics Association · doi:10.1136/jamia.1996.97084511 · Cited by 346
To Reuse or Not To Reuse?: A Framework and System for Evaluating Summarized Knowledge
Liu, M. X., Kittur, A., & Myers, B. A. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3449240 · Cited by 23
Metadata
- Authors
- Krueger, C. W.
- Venue
- ACM Computing Surveys
- Published
- 1992-06
- Volume
- 24
- Issue
- 2
- Pages
- 131-183
- ISSN
- 0360-0300 (ISSN-L)
- 1557-7341
- OpenAlex
- W2294861651
- Cited by
- 1,431
- References
- 0
- FWCI
- 41.14
- Type
- journal article
- 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: Software reuse. https://app.cochat.ai/papers/10.1145/130844.130856
- The paper
- Krueger, C. W. (1992). Software reuse. ACM Computing Surveys. https://doi.org/10.1145/130844.130856
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.