Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review
Safe and Sound Program Analysis with Flix. / Madsen, Magnus; Lhoták, Ondrej.
ISSTA 2018 - Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis. ed. / Eric Bodden; Frank Tip. New York, NY, USA : Association for Computing Machinery, 2018. p. 38-48 (ISSTA 2018).Research output: Contribution to book/anthology/report/proceeding › Article in proceedings › Research › peer-review
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TY - GEN
T1 - Safe and Sound Program Analysis with Flix
AU - Madsen, Magnus
AU - Lhoták, Ondrej
PY - 2018/7/12
Y1 - 2018/7/12
N2 - Program development tools such as bug finders, build automation tools, compilers, debuggers, integrated development environments, and refactoring tools increasingly rely on static analysis techniques to reason about program behavior. Implementing such static analysis tools is a complex and difficult task with concerns about safety and soundness. Safety guarantees that the fixed point computation - inherent in most static analyses - converges and ultimately terminates with a deterministic result. Soundness guarantees that the computed result over-approximates the concrete behavior of the program under analysis. But how do we know if we can trust the result of the static analysis itself? Who will guard the guards? In this paper, we propose the use of automatic program verification techniques based on symbolic execution and SMT solvers to verify the correctness of the abstract domains used in static analysis tools. We implement a verification toolchain for Flix, a functional and logic programming language tailored for the implementation of static analyses.We apply this toolchain to several abstract domains. The experimental results show that we are able to prove 99.5% and 96.3% of the required safety and soundness properties, respectively.
AB - Program development tools such as bug finders, build automation tools, compilers, debuggers, integrated development environments, and refactoring tools increasingly rely on static analysis techniques to reason about program behavior. Implementing such static analysis tools is a complex and difficult task with concerns about safety and soundness. Safety guarantees that the fixed point computation - inherent in most static analyses - converges and ultimately terminates with a deterministic result. Soundness guarantees that the computed result over-approximates the concrete behavior of the program under analysis. But how do we know if we can trust the result of the static analysis itself? Who will guard the guards? In this paper, we propose the use of automatic program verification techniques based on symbolic execution and SMT solvers to verify the correctness of the abstract domains used in static analysis tools. We implement a verification toolchain for Flix, a functional and logic programming language tailored for the implementation of static analyses.We apply this toolchain to several abstract domains. The experimental results show that we are able to prove 99.5% and 96.3% of the required safety and soundness properties, respectively.
KW - lattices, monotonicity, safety, soundness, static analysis
KW - Lattices
KW - Monotonicity
KW - Safety
KW - Soundness
KW - Static analysis
U2 - 10.1145/3213846.3213847
DO - 10.1145/3213846.3213847
M3 - Article in proceedings
SN - 978-1-4503-5699-2
SP - 38
EP - 48
BT - ISSTA 2018 - Proceedings of the 27th ACM SIGSOFT International Symposium on Software Testing and Analysis
A2 - Bodden, Eric
A2 - Tip, Frank
PB - Association for Computing Machinery
CY - New York, NY, USA
ER -