The DOI matches its Crossref record.
On the Automated Generation of Program Test Data
Abstract
Software validation through testing will continue to be a very important tool for ensuring correctness of large scale software systems. Automation of testing tools can greatly enhance their power and reduce testing cost. In this paper, techniques for automated test data generation are discussed. Given a program graph, a set of paths are identified to satisfy some given testing criteria. When a path or a program segment is specified, symbolic execution is used for generating input constraints which define a set of inputs for executing this path or segment. Problems encountered in symbolic execution are discussed. A new approach for resolving array reference ambiguities and a procedure for generating test inputs satisfying input constraints are proposed. References to arrays are recorded in a table. during symbolic execution and ambiguities are resolved when test data are generated to evaluate the subscript expressions. The implementation of a test data generator for Fortran programs incorporating these techniques is also described.
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
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
Search‐based software test data generation: a survey
McMinn, P. (2004) · Software Testing, Verification and Reliability · doi:10.1002/stvr.294 · Cited by 1,368
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
The software model checker Blast: Applications to software engineering
Beyer, D., Henzinger, T. A., Jhala, R., & Majumdar, R. (2007) · International Journal on Software Tools for Technology Transfer · doi:10.1007/s10009-007-0044-z · Cited by 585
Metadata
- Authors
- Ramamoorthy, C. V., Ho, S.-B. F., & Chen, W. T.
- Venue
- IEEE Transactions on Software Engineering
- Published
- 1976-12
- Volume
- SE-2
- Issue
- 4
- Pages
- 293-300
- ISSN
- 0098-5589 (ISSN-L)
- OpenAlex
- W2033072042
- Cited by
- 319
- References
- 0
- FWCI
- 15.58
- 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: On the Automated Generation of Program Test Data. https://app.cochat.ai/papers/10.1109/tse.1976.233835
- The paper
- Ramamoorthy, C. V., Ho, S.-B. F., & Chen, W. T. (1976). On the Automated Generation of Program Test Data. IEEE Transactions on Software Engineering. https://doi.org/10.1109/tse.1976.233835
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.