Abstract
We consider verification algorithms in a wide sense. The out-come of a verification algorithm can be a definite (yes or no) answer, a “don’t know” answer, or a conditional answer or no answer at all (divergence). We obtain these kinds of verification algorithms if we apply the existing technology of abstraction to least-fixpoint checking, i.e., checking whether the least fixpoint of a given operator in a given lattice is smaller than a given bound. The formulation of the verification algorithm as least-fixpoint checking is classical for the class of correctness properties that are reducible to non-reachability (validity of assertions, partial correctness, safety properties). We need to investigate the approach also for the class of correctness properties that are reducible to termination (validity of intermittent assertions, total correctness, liveness properties), for all classes of programs including procedural (recursive) programs and concurrent programs.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Podelski, A. (2008). Verification, Least-Fixpoint Checking, Abstraction. In: Shankar, N., Woodcock, J. (eds) Verified Software: Theories, Tools, Experiments. VSTTE 2008. Lecture Notes in Computer Science, vol 5295. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87873-5_3
Download citation
DOI: https://doi.org/10.1007/978-3-540-87873-5_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87872-8
Online ISBN: 978-3-540-87873-5
eBook Packages: Computer ScienceComputer Science (R0)