The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Weak Mutation Testing and Completeness of Test Sets
Abstract
Different approaches to the generation of test data are described. Error-based approaches depend on the definition of classes of commonly occurring program errors. They generate tests which are specifically designed to determine if particular classes of errors occur in a program. An error-based method called weak mutation testing is described. In this method, tests are constructed which are guaranteed to force program statements which contain certain classes of errors to act incorrectly during the execution of the program over those tests. The method is systematic, and a tool can be built to help the user apply the method. It is extensible in the sense that it can be extended to cover additional classes of errors. Its relationship to other software testing methods is discussed. Examples are included.
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
Hints on Test Data Selection: Help for the Practicing Programmer
DeMillo, R. A., Lipton, R. J., & Sayward, F. G. (1978) · Computer · doi:10.1109/c-m.1978.218136 · Cited by 2,081
Testing Programs with the Aid of a Compiler
Hamlet, R. G. (1977) · IEEE Transactions on Software Engineering · doi:10.1109/tse.1977.231145 · Cited by 552
Current trends in programming methodology
Yeh, R. T., & Chandy, K. M. (1977) · CERN Document Server (European Organization for Nuclear Research) · Cited by 545
Toward a theory of test data selection
Goodenough, J. B., & Gerhart, S. L. (1975) · ACM SIGPLAN Notices · doi:10.1145/390016.808473 · Cited by 514
Reliability of the Path Analysis Testing Strategy
Howden, W. E. (1976) · IEEE Transactions on Software Engineering · doi:10.1109/tse.1976.233816 · Cited by 400
Self-citationA Domain Strategy for Computer Program Testing
White, L. J., & Cohen, E. I. (1980) · IEEE Transactions on Software Engineering · doi:10.1109/tse.1980.234486 · Cited by 378
An Approach to Program Testing
Huang, J. C. (1975) · ACM Computing Surveys · doi:10.1145/356651.356652 · Cited by 229
Theories of Program Testing and the Application of Revealing Subdomains
Weyuker, E. J., & Ostrand, T. J. (1980) · IEEE Transactions on Software Engineering · doi:10.1109/tse.1980.234485 · Cited by 223
Cited by
An Analysis and Survey of the Development of Mutation Testing
Jia, Y., & Harman, M. (2011) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2010.62 · Cited by 1,745
Software unit test coverage and adequacy
Zhu, H., Hall, P. A. V., & May, J. H. R. (1997) · ACM Computing Surveys · doi:10.1145/267580.267590 · Cited by 1,247
Constraint-based automatic test data generation
DeMilli, R. A., & Offutt, A. J. (1991) · IEEE Transactions on Software Engineering · doi:10.1109/32.92910 · Cited by 804
A fortran language system for mutation‐based software testing
King, K. N., & Offutt, A. J. (1991) · Software: Practice and Experience · doi:10.1002/spe.4380210704 · Cited by 379
Inferring extended finite state machine models from software executions
Walkinshaw, N., Taylor, R., & Derrick, J. (2016) · Empirical Software Engineering · doi:10.1007/s10664-015-9367-7 · Cited by 127
Metadata
- Authors
- Howden, W. E.
- Venue
- IEEE Transactions on Software Engineering
- Published
- 1982-07
- Volume
- SE-8
- Issue
- 4
- Pages
- 371-379
- ISSN
- 0098-5589 (ISSN-L)
- OpenAlex
- W2157755550
- Cited by
- 477
- References
- 8
- FWCI
- 16.15
- 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: Weak Mutation Testing and Completeness of Test Sets. https://app.cochat.ai/papers/10.1109/tse.1982.235571
- The paper
- Howden, W. E. (1982). Weak Mutation Testing and Completeness of Test Sets. IEEE Transactions on Software Engineering. https://doi.org/10.1109/tse.1982.235571
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.
