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Published, Version of Record (VoR)Open Access via Drexel Libraries Read and Publish Program 2024CC BY V4.0, Open
Conference proceeding
When Compiler Optimizations Meet Symbolic Execution: An Empirical Study
CCS '24: Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, pp 4212-4225
09 Dec 2024
Featured in Collection : Research Supported by Drexel Libraries' OA Programs
Abstract
Compiler optimizations intend to transform a program into a semantic-equivalent one with improved performance, but it is unclear how these optimizations may impact the performance of dynamic symbolic execution (DSE) on binary code. To systematically understand the impact of compiler optimizations on two popular DSE techniques (i.e., symbolic exploration and symbolic tracing), this paper presents an empirical study that quantifies 209 GCC compilation flags and 73 Clang compilation flags to reveal both positive and negative optimizations to DSE. Our data set contains 992 unique test cases, which are produced from 3,449 source files in the GCC test suite. After analyzing 2,978,976 binary programs that we compiled with two compilers and various compilation flags, we found that although some optimizations make DSE faster, most optimizations will actually slow down DSE. Our analysis further reveals root causes behind these impacts. The most positive impacts that optimizations have on DSE come from the reduction of the number of instructions and program paths, whereas negative impacts are caused by a series of unexpected behaviors, including increased numbers of instructions or program paths, library function inlining preventing DSE engines from using function summaries, and arithmetic optimizations leading to more sophisticated constraints. Being the first in-depth analysis on why compiler flags influence the performance of DSE, this project sheds light on program transformations that can be applied before performing DSE tasks for better performance.
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Details
- Title
- When Compiler Optimizations Meet Symbolic Execution: An Empirical Study
- Creators
- Yue Zhang (Corresponding Author) - Drexel University, Computer ScienceMelih Sirlanci - The Ohio State UniversityRuoyu Wang - Arizona State UniversityZhiqiang Lin - The Ohio State University
- Publication Details
- CCS '24: Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, pp 4212-4225
- Conference
- CCS '24: ACM SIGSAC Conference on Computer and Communications Security (Salt Lake City, Utah, 14 Oct 2024–18 Oct 2024)
- Publisher
- Association for Computing Machinery
- Number of pages
- 14
- Grant note
- Army Research Office (ARO): W911NF2110081 DefenseAdvanced Research ProjectsAgency (DARPA): N6600120C4020, N6600122C4026, SP47012 3C0074 National Science Foundation (NSF): 2146568, 2232915
We thank the anonymous reviewers for their insightful feedback. This research was supported in part by Army Research Office (ARO) award W911NF2110081, DefenseAdvanced Research ProjectsAgency (DARPA) awards N6600120C4020 and N6600122C4026, Advanced Research ProjectsAgency for Health (ARPA-H) Contract No. SP47012 3C0074, and National Science Foundation (NSF) awards 2146568 and 2232915. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of ARO, DARPA, ARPA-H, or NSF.
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science
- Web of Science ID
- WOS:001436367300286
- Scopus ID
- 2-s2.0-85215531342
- Other Identifier
- 991021970300904721
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Hardware & Architecture
- Computer Science, Theory & Methods
- Telecommunications