Worst-Case Execution Time (WCET) analysis provides an upper bound on a program’s execution time and is fundamental to the design and verification of real-time systems.
Accurate modeling of cache behavior is critical for WCET estimation, as cache-miss latency is typically orders of magnitude larger than cache-hit latency.
Since cache behavior is path dependent, existing methods commonly use abstract interpretation to estimate cache behaviors without enumerating all paths. However, conventional abstract interpretation is context-agnostic—adopting the most conservative case across paths—and thus may produce an overestimated WCET bound.
To bridge the gap between scalability and accuracy, we propose a path-sensitive abstract-interpretation-based cache analysis that maintains a set of cache states drawn from critical execution paths to derive context-aware cache behavior.
This path-sensitive cache analysis integrates seamlessly into standard WCET frameworks, resulting in tight yet provably sound WCET bounds.
Experiments show that our approach improves WCET accuracy by an average of 24.83% without sacrificing scalability.