Program analysis using empirical abstraction

Given a program analysis problem that consists of a program and a property of interest, we use an empirical approach to automatically construct a sequence of abstractions that approach an ideal abstraction suitable for solving that problem. This process begins with an infinite concrete domain that m...

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Veröffentlicht in:International journal on software tools for technology transfer Jg. 25; H. 4; S. 431 - 452
Hauptverfasser: Ho, Vivian M., Alvin, Chris, Lawson, Jimmie D., Mukhopadhyay, Supratik, Peterson, Brian
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2023
Springer Nature B.V
Schlagworte:
Clustering
Computer Science
Empirical analysis
Queries
Software Engineering
Software Engineering/Programming and Operating Systems
Theory of Computation
Abstract Interpretation
Program Analysis
Abstract Cluster Domain
Bounded CTL
ISSN:1433-2779, 1433-2787
Online-Zugang:Volltext
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Zusammenfassung:Given a program analysis problem that consists of a program and a property of interest, we use an empirical approach to automatically construct a sequence of abstractions that approach an ideal abstraction suitable for solving that problem. This process begins with an infinite concrete domain that maps to a finite abstract cluster domain defined by statistical procedures. Given a set of properties expressed as formulas in a restricted and bounded variant of CTL, we can test the success of the abstraction with respect to a predefined performance measure. In addition, we can perform iterative abstraction-refinement of the clustering by tuning hyperparameters that determine the accuracy of the cluster representations (abstract states) and determine the number of clusters.
Bibliographie:ObjectType-Article-1
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ISSN:1433-2779
1433-2787
DOI:10.1007/s10009-023-00709-y