scholarly journals Loopfrog — loop summarization for static analysis

10.29007/g3fd ◽  
2018 ◽  
Author(s):  
Daniel Kroening ◽  
Natasha Sharygina ◽  
Stefano Tonetta ◽  
Aliaksei Tsitovich ◽  
Christoph M. Wintersteiger

Loopfrog is a scalable static analyzer for ANSI-C programs, that combines the precision of model checking and the performance of abstract interpretation. In contrast to traditional static analyzers, it does not calculate the abstract fix-point of a program by iterative application of an abstract transformer. Instead, it calculates symbolic abstract transformers for program fragments (e.g., loops) using a loop summarization algorithm. Loopfrog computes abstract transformers starting from the inner-most loops, which results in linear (in the number of the looping constructs) run-time of the sum- marization procedure and which is often considerably smaller than the traditional saturation procedure of abstract interpetation. It also provides “leaping” counterexamples to aid in the diagnosis of errors.

10.29007/7lrd ◽  
2018 ◽  
Author(s):  
Ian Cassar ◽  
Adrian Francalanza ◽  
Duncan Attard ◽  
Luca Aceto ◽  
Anna Ingolfsdottir

Ensuring formal correctness for actor-based, concurrent systems is a difficult task, pri- marily because exhaustive, static analysis verification techniques such as model checking quickly run into state-explosion problems. Runtime monitoring techniques such as Run- time Verification and Adaptation circumvent this limitation by verifying the correctness of a program by dynamically analysing its executions. This paper gives an overview of a suite of monitoring tools available for verifying and adapting actor-based Erlang programs.


Author(s):  
Simmo Saan ◽  
Michael Schwarz ◽  
Kalmer Apinis ◽  
Julian Erhard ◽  
Helmut Seidl ◽  
...  

AbstractGoblintis a static analysis framework for C programs specializing in data race analysis. It relies on thread-modular abstract interpretation where thread interferences are accounted for by means of flow-insensitive global invariants.


2021 ◽  
Vol 54 (7) ◽  
pp. 1-37
Author(s):  
Jihyeok Park ◽  
Hongki Lee ◽  
Sukyoung Ryu

Understanding program behaviors is important to verify program properties or to optimize programs. Static analysis is a widely used technique to approximate program behaviors via abstract interpretation. To evaluate the quality of static analysis, researchers have used three metrics: performance, precision, and soundness. The static analysis quality depends on the analysis techniques used, but the best combination of such techniques may be different for different programs. To find the best combination of analysis techniques for specific programs, recent work has proposed parametric static analysis . It considers static analysis as black-box parameterized by analysis parameters , which are techniques that may be configured without analysis details. We formally define the parametric static analysis, and we survey analysis parameters and their parameter selection in the literature. We also discuss open challenges and future directions of the parametric static analysis.


Author(s):  
Subburaj Ramasamy ◽  
Anuj Singh ◽  
Deepak Singal
Keyword(s):  

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