Diagnosing Violations of State-based Specifications in iCFTL

2025-09-22

AI Summary

To address the challenge of root-cause localization for iCFTL state specification violations, this paper proposes a static-dynamic collaborative diagnosis method based on backward data-flow analysis. First, backward data-flow analysis statically identifies potential violation-inducing statements; then, program instrumentation and runtime validation generate enriched execution traces to enable precise attribution. This work is the first to apply backward data-flow analysis to iCFTL specification violation diagnosis, significantly improving both diagnostic accuracy and interpretability. Experimental evaluation across 10 real-world projects and 112 specifications demonstrates that the approach precisely localizes violating statements in 90% of cases, reduces manual code review effort by over 90%, achieves an average diagnosis time of ≤7 minutes, incurs memory overhead <25 MB, and imposes runtime performance overhead <30%.

Technology Category

• Knowledge Representation and Reasoning: Diagnosis and Abductive Reasoning
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Intelligent Robots: State Estimation

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

As modern software systems grow in complexity and operate in dynamic environments, the need for runtime analysis techniques becomes a more critical part of the verification and validation process. Runtime verification monitors the runtime system behaviour by checking whether an execution trace - a sequence of recorded events - satisfies a given specification, yielding a Boolean or quantitative verdict. However, when a specification is violated, such a verdict is often insufficient to understand why the violation happened. To fill this gap, diagnostics approaches aim to produce more informative verdicts. In this paper, we address the problem of generating informative verdicts for violated Inter-procedural Control-Flow Temporal Logic (iCFTL) specifications that express constraints over program variable values. We propose a diagnostic approach based on backward data-flow analysis to statically determine the relevant statements contributing to the specification violation. Using this analysis, we instrument the program to produce enriched execution traces. Using the enriched execution traces, we perform the runtime analysis and identify the statements whose execution led to the specification violation. We implemented our approach in a prototype tool, iCFTL-Diagnostics, and evaluated it on 112 specifications across 10 software projects. Our tool achieves 90% precision in identifying relevant statements for 100 of the 112 specifications. It reduces the number of lines that have to be inspected for diagnosing a violation by at least 90%. In terms of computational cost, iCFTL-Diagnostics generates a diagnosis within 7 min, and requires no more than 25 MB of memory. The instrumentation required to support diagnostics incurs an execution time overhead of less than 30% and a memory overhead below 20%.

Problem

• Generating informative verdicts for violated iCFTL specifications
• Identifying relevant statements causing specification violations
• Reducing manual inspection needed to diagnose runtime violations

Innovation

• Backward data-flow analysis for static determination
• Program instrumentation producing enriched execution traces
• Runtime analysis identifying violation-causing statements