The DOI matches its Crossref record.
Soot: a Java bytecode optimization framework
Abstract
This paper presents Soot, a framework for optimizing Java* bytecode. The framework is implemented in Java and supports three intermediate representations for representing Java bytecode: Baf, a streamlined representation of bytecode which is simple to manipulate; Jimple, a typed 3-address intermediate representation suitable for optimization; and Grimp, an aggregated version of Jimple suitable for decompilation. We describe the motivation for each representation, and the salient points in translating from one representation to another. In order to demonstrate the usefulness of the framework, we have implemented intraprocedural and whole program optimizations. To show that whole program bytecode optimization can give performance improvements, we provide experimental results for 12 large benchmarks, including 8 SPECjvm98 benchmarks running on JDK 1.2 for GNU/Linuxtm. These results show up to 8% improvement when the optimized bytecode is run using the interpreter and up to 21% when run using the JIT compiler.
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
Security Analysis of Emerging Smart Home Applications
Fernandes, E., Jung, J., & Prakash, A. (2016) · 2016 IEEE Symposium on Security and Privacy (SP) · doi:10.1109/sp.2016.44 · Cited by 689
A Survey of Performance Optimization for Mobile Applications
Hort, M., Kechagia, M., Sarro, F., & Harman, M. (2022) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2021.3071193 · Cited by 91
PrivacyStreams: Enabling Transparency in Personal Data Processing for Mobile Apps
Li, Y., Chen, F., Li, T. J.-J., Guo, Y., Huang, G., Fredrikson, M., Agarwal, Y., & Hong, J. I. (2017) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies · doi:10.1145/3130941 · Cited by 39
Metadata
- Authors
- Vallée-Rai, R., Co, P., Gagnon, E., Hendren, L., Lam, P., & Sundaresan, V.
- Venue
- CASCON First Decade High Impact Papers on - CASCON '10
- Publisher
- ACM Press
- Published
- 2010
- Pages
- 214-224
- OpenAlex
- W2080696000
- Cited by
- 933
- References
- 0
- FWCI
- 33.52
- 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: Soot: a Java bytecode optimization framework. https://app.cochat.ai/papers/10.1145/1925805.1925818
- The paper
- Vallée-Rai, R., Co, P., Gagnon, E., Hendren, L., Lam, P., & Sundaresan, V. (2010). Soot: a Java bytecode optimization framework. CASCON First Decade High Impact Papers on - CASCON '10. https://doi.org/10.1145/1925805.1925818
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.
