Result: Static Analysis using Parameterised Boolean Equation Systems

Title:
Static Analysis using Parameterised Boolean Equation Systems
Contributors:
Universidad de Málaga [Málaga] = University of Málaga [Málaga], Lavoisier grant from the French Ministry of Foreign Affairs and Spanish MEC under grant TIN2004-7943-C04
Publisher Information:
HAL CCSD, 2006.
Publication Year:
2006
Original Identifier:
ARXIV: cs.SE/0606092
HAL:
Document Type:
other<br />Other publications
Language:
English
Relation:
info:eu-repo/semantics/altIdentifier/arxiv/cs.SE/0606092
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.inria.00080518v2
Database:
HAL

Further Information

Submitted to an international 2006 conference
Report
The well-known problem of state space explosion in model checking is even more critical when applying this technique to programming languages, mainly due to the presence of complex data structures. One recent and promising approach to deal with this problem is the construction of an abstract and correct representation of the global program state allowing to match visited states during program model exploration. In particular, one powerful method to implement abstract matching is to fill the state vector with a minimal amount of relevant variables for each program point. In this paper, we combine the on-the-fly model-checking approach (incremental construction of the program state space) and the static analysis method called influence analysis (extraction of significant variables for each program point) in order to automatically construct an abstract matching function. Firstly, we describe the problem as an alternation-free value-based mu-calculus formula, whose validity can be checked on the program model expressed as a labeled transition system (LTS). Secondly, we translate the analysis into the local resolution of a parameterised boolean equation system (PBES), whose representation enables a more efficient construction of the resulting abstract matching function. Finally, we show how our proposal may be elegantly integrated into CADP, a generic framework for both the design and analysis of distributed systems and the development of verification tools.