Testing meets static and runtime verification

Chimento, Jesús Mauricio; Ahrendt, Wolfgang; Schneider, Gerardo

doi:10.1145/3193992.3194000

Cited by 8 publications

(2 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…RV can complement and has been used in combination with other formal static verification methods such as model checking [26], deductive verification [12] and static analysis [15,9,12,4], as well as informal dynamic methods such as testing [13] and debugging [23]. While a complete a priori verification is ideally desirable for verifying program correctness, proving the correctness of many properties is fundamentally undecidable statically.…”

Section: Introductionmentioning

confidence: 99%

Residual Runtime Verification via Reachability Analysis

Soueidi

Falcone

2023

Lecture Notes in Computer Science

View full text Add to dashboard Cite

We leverage static verification to reduce monitoring overhead when runtime verifying a property. We present a sound and efficient analysis to statically find safe execution paths in the control flow at the intra-procedural level of programs. Such paths are guaranteed to preserve the monitored property and thus can be ignored at runtime. Our analysis guides an instrumentation tool to select program points that should be observed at runtime. The monitor is left to perform residual runtime verification for parts of the program that the analysis could not statically prove safe. Our approach does not depend on dataflow analysis, thus separating the task of residual analysis from static analysis; allowing for seamless integration with many RV frameworks and development pipelines. We implement our approach within BISM, which is a recent tool for bytecode-level instrumentation of Java programs. Our experiments on the DaCapo benchmark show a reduction in instrumentation points by a factor of 2.5 on average (reaching 9), and accordingly, a reduction in the number of runtime events by a factor of 1.8 on average (reaching 6).

show abstract

Section: Introductionmentioning

confidence: 99%

Residual Runtime Verification via Reachability Analysis

Soueidi

Falcone

2023

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

“…Static analysis has been widely used for performing multiple types of program properties verification, such as vulnerability/bug detection, test case generation, and compiler optimizations [5,7,12,15,23,36]. At the core of many of those analyses is the program's call graph, which establishes the relationships between callers and callees [16].…”

Section: Introductionmentioning

confidence: 99%

Salsa: static analysis of serialization features

Santos

Jones

Mirakhorli

2020

Proceedings of the 22nd ACM SIGPLAN International Workshop on Formal Techniques for Java-Like Programs

View full text Add to dashboard Cite

Static analysis has the advantage of reasoning over multiple possible paths. Thus, it has been widely used for verification of program properties. Property verification often requires inter-procedural analysis, in which control and data flow are tracked across methods. At the core of interprocedural analyses is the call graph, which establishes relationships between caller and callee methods. However, it is challenging to perform static analysis and compute the call graph of programs with dynamic features. Dynamic features are widely used in software systems; not supporting them makes it difficult to reason over properties related to these features. Although state-of-the-art research had explored certain types of dynamic features, such as reflection and RMI-based programs, serialization-related features are still not very well supported, as demonstrated in a recent empirical study. Therefore, in this paper, we introduce Salsa (Static AnaLyzer for SeriAlization features), which aims to enhance existing points-to analysis with respect to serialization-related features. The goal is to enhance the resulting call graph's soundness, while not greatly affecting its precision. In this paper, we report our early effort in developing Salsa and its early evaluation using the Java Call Graph Test Suite (JCG). CCS Concepts: • Software and its engineering → Compilers; Automated static analysis; • Theory of computation → Program analysis.

show abstract