Abstract
Many of the current verification approaches can be classified into automatic and interactive techniques, each having different strengths and weaknesses. Thus, one of the current open problems is to design solutions to combine the two approaches and accelerate technology transfer. We outline four existing techniques that might be able to contribute to combination solutions: (1) Conditional model checking is a technique that gives detailed information (in form of a condition) about the verified state space, i.e., informs the user (or tools later in a tool chain) of the outcome. Also, it accepts as input detailed information (again as condition) about what the conditional model checker has to do. (2) Correctness witnesses, stored in a machine-readable exchange format, contain (partial) invariants that can be used to prove the correctness of a system. For example, tools that usually expect invariants from the user can read the invariants from such correctness witnesses and ask the user only for the remaining invariants. (3) Abstraction-refinement based approaches that use a dynamically adjustable precision (such as in lazy CEGAR approaches) can be provided with invariants from the user or from other tools, e.g., from deductive methods. This way, the approach can succeed in constructing a proof even if it was not able to come up with the required invariant. (4) The technique of path invariants extracts (in a CEGAR method) a path program that represents an interesting part of the program for which an invariant is needed. Such a path program can be given to an expensive (or interactive) method for computing invariants that can then be fed back to a CEGAR method to continue verifying the large program. While the existing techniques originate from software verification, we believe that the new combination ideas are useful for verifying general systems.
Item Type: | Book Section |
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Faculties: | Mathematics, Computer Science and Statistics > Computer Science |
Subjects: | 000 Computer science, information and general works > 004 Data processing computer science |
ISBN: | 978-3-319-47165-5; 978-3-319-47166-2 |
Place of Publication: | Cham |
Language: | English |
Item ID: | 47347 |
Date Deposited: | 27. Apr 2018, 08:12 |
Last Modified: | 04. Nov 2020, 13:24 |