Combining static analysis error traces with dynamic symbolic execution (experience paper)
Frank Busse, Pritam M. Gharat, Cristian Cadar, Alastair F. Donaldson
Abstract
This paper reports on our experience implementing a technique for sifting through static analysis reports using dynamic symbolic execution. Our insight is that if a static analysis tool produces a partial trace through the program under analysis, annotated with conditions that the analyser believes are important for the bug to trigger, then a dynamic symbolic execution tool may be able to exploit the trace by (a) guiding the search heuristically so that paths that follow the trace most closely are prioritised for exploration, and (b) pruning the search using the conditions associated with each step of the trace. This may allow the bug to be quickly confirmed using dynamic symbolic execution, if it turns out to be a true positive, yielding an input that triggers the bug.
To experiment with this approach, we have implemented the idea in a tool chain that allows the popular open-source static analysis tools Clang Static Analyzer (CSA) and Infer to be combined with the popular open-source dynamic symbolic execution engine KLEE. Our findings highlight two interesting negative results. First, while fault injection experiments show the promise of our technique, they also reveal that the traces provided by static analysis tools are not that useful in guiding search. Second, we have systematically applied CSA and Infer to a large corpus of real-world applications that are suitable for analysis with KLEE, and find that the static analysers are rarely able to find non-trivial true positive bugs for this set of applications.
We believe our case study can inform static analysis and dynamic symbolic execution tool developers as to where improvements may be necessary, and serve as a call to arms for researchers interested in combining symbolic execution and static analysis to identify more suitable benchmark suites for evaluation of research ideas.
• Software and its engineering → Software testing and debugging.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext c5e56a39-af02-4b77-9b59-71664e4cffd1Cited by top-tier papers2
- Atropos: Effective Fuzzing of Web Applications for Server-Side VulnerabilitiesEmre Güler, Sergej Schumilo, Moritz Schloegel, Nils Bars et al.USENIX Security 2024 · 45 citations
- Combining Structured Static Code Information and Dynamic Symbolic Traces for Software Vulnerability PredictionHuanting Wang, Zhanyong Tang, Shin Hwei Tan, Jie Wang et al.ICSE 2024 · 15 citations
Builds on1
Related papers
- Making symbolic execution promising by learning aggressive state-pruning strategySooyoung Cha, Hakjoo OhFSE 2020 · 14 citations
- When Compiler Optimizations Meet Symbolic Execution: An Empirical StudyYue Zhang, Melih Sirlanci, Ruoyu Wang, Zhiqiang LinCCS 2024 · 2 citations
- Compatible Branch Coverage Driven Symbolic Execution for Efficient Bug FindingQiuping Yi, Yifan Yu, Guowei YangPLDI 2024 · 10 citations
- A Compilation-Based Under-Constrained Execution EngineMingjun Yin, Zhaorui Li, Ju Chen, Haochen Zeng et al.OSDI 2026
- SYMTUNER: Maximizing the Power of Symbolic Execution by Adaptively Tuning External ParametersSooyoung Cha, Myungho Lee, Seokhyun Lee, Hakjoo OhICSE 2022 · 4 citations
