The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Randoop: feedback-directed random testing for Java
Abstract
R ANDOOP for Java generates unit tests for Java code using feedback-directed random test generation. Below we describe R ANDOOP 's input, output, and test generation algorithm. We also give an overview of RANDOOP's annotation-based interface for specifying configuration parameters that affect R ANDOOP 's behavior and output.
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
JCrasher: an automatic robustness tester for Java
Csallner, C., & Smaragdakis, Y. (2004) · Software: Practice and Experience · doi:10.1002/spe.602 · Cited by 426
Cited by
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
Fraser, G., & Arcuri, A. (2013) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2012.14 · Cited by 586
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
FairFuzz: a targeted mutation strategy for increasing greybox fuzz testing coverage
Lemieux, C., & Sen, K. (2018) · Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering · doi:10.1145/3238147.3238176 · Cited by 477
An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation
Schäfer, M., Nadi, S., Eghbali, A., & Tip, F. (2024) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2023.3334955 · Cited by 431
“They position their technique as a complement to traditional techniques [8], [17].”
BackgroundMethodInfluential
Metadata
- Authors
- Pacheco, C., & Ernst, M. D.
- Venue
- Companion to the 22nd ACM SIGPLAN conference on Object-oriented programming systems and applications companion
- Publisher
- ACM
- Published
- 2007-10-20
- Pages
- 815-816
- OpenAlex
- W1965194038
- Cited by
- 558
- References
- 1
- FWCI
- 2.83
- 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: Randoop: feedback-directed random testing for Java. https://app.cochat.ai/papers/10.1145/1297846.1297902
- The paper
- Pacheco, C., & Ernst, M. D. (2007). Randoop: feedback-directed random testing for Java. Companion to the 22nd ACM SIGPLAN conference on Object-oriented programming systems and applications companion. https://doi.org/10.1145/1297846.1297902
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.
