The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Automated concolic testing of smartphone apps
Abstract
We present an algorithm and a system for generating input events to exercise smartphone apps. Our approach is based on concolic testing and generates sequences of events automatically and systematically. It alleviates the path-explosion problem by checking a condition on program executions that identifies subsumption between different event sequences. We also describe our implementation of the approach for Android, the most popular smartphone app platform, and the results of an evaluation that demonstrates its effectiveness on five Android apps.
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
de Moura, L., & Bjørner, N. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-78800-3_24 · Cited by 6,595
KLEE: unassisted and automatic generation of high-coverage tests for complex systems programs
Cadar, C., Dunbar, D., & Engler, D. (2008) · doi:10.5555/1855741.1855756 · Cited by 2,620
TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones
Enck, W., Gilbert, P., Chun, B.-G., Cox, L. P., Jung, J., McDaniel, P. D., & Sheth, A. N. (2010) · doi:10.5555/1924943.1924971 · Cited by 2,238
DART: directed automated random testing
Godefroid, P., Klarlund, N., & Sen, K. (2005) · ACM SIGPLAN Notices · doi:10.1145/1064978.1065036 · Cited by 2,067
(2011) · doi:10.1145/1966445.1966473 · Cited by 1,870
Self-citationCUTE: a concolic unit testing engine for C
Sen, K., Marinov, D., & Agha, G. (2005) · Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering · doi:10.1145/1081706.1081750 · Cited by 1,651
DART: directed automated random testing
Godefroid, P., Klarlund, N., & Sen, K. (2005) · Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation · doi:10.1145/1065010.1065036 · Cited by 1,570
Android permissions demystified
Felt, A. P., Chin, E., Hanna, S., Song, D., & Wagner, D. (2011) · Proceedings of the 18th ACM conference on Computer and communications security · doi:10.1145/2046707.2046779 · Cited by 1,291
Automated Whitebox Fuzz Testing.
Godefroid, P., Levin, M. Y., & Molnar, D. A. (2008) · Cited by 1,095
Soot: a Java bytecode optimization framework
Vallée-Rai, R., Co, P., Gagnon, E., Hendren, L., Lam, P., & Sundaresan, V. (2010) · CASCON First Decade High Impact Papers on - CASCON '10 · doi:10.1145/1925805.1925818 · Cited by 933
Cited by
Guided, stochastic model-based GUI testing of Android apps
Su, T., Meng, G., Chen, Y., Wu, K., Yang, W., Yao, Y., Pu, G., Liu, Y., & Su, Z. (2017) · Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering · doi:10.1145/3106237.3106298 · Cited by 371
MobiGUITAR: Automated Model-Based Testing of Mobile Apps
Amalfitano, D., Fasolino, A. R., Tramontana, P., Ta, B. D., & Memon, A. M. (2015) · IEEE Software · doi:10.1109/ms.2014.55 · Cited by 278
Metadata
- Authors
- Anand, S., Naik, M., Harrold, M. J., & Yang, H.
- Venue
- Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering
- Publisher
- ACM
- Published
- 2012-11-11
- Pages
- 1-11
- OpenAlex
- W2161963160
- Cited by
- 401
- References
- 26
- FWCI
- 23.64
- 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: Automated concolic testing of smartphone apps. https://app.cochat.ai/papers/10.1145/2393596.2393666
- The paper
- Anand, S., Naik, M., Harrold, M. J., & Yang, H. (2012). Automated concolic testing of smartphone apps. Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering. https://doi.org/10.1145/2393596.2393666
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.
