Deductive program verification (a practitioner's commentary)

Minds and Machines 2 (3):283-307 (1992)
A proof of ‘correctness’ for a mathematical algorithm cannot be relevant to executions of a program based on that algorithm because both the algorithm and the proof are based on assumptions that do not hold for computations carried out by real-world computers. Thus, proving the ‘correctness’ of an algorithm cannot establish the trustworthiness of programs based on that algorithm. Despite the (deceptive) sameness of the notations used to represent them, the transformation of an algorithm into an executable program is a wrenching metamorphosis that changes a mathematical abstraction into a prescription for concrete actions to be taken by real computers. Therefore, it is verification of program executions (processes) that is needed, not of program texts that are merely the scripts for those processes. In this view, verification is the empirical investigation of: (a) the behavior that programs invoke in a computer system and (b) the larger context in which that behavior occurs. Here, deduction can play no more, and no less, a role than it does in the empirical sciences.
Keywords Algorithms  computers  computer programs  program executions (processes)  program verification (‘correctness’ proofs, testing)  representations (objects)  software reliability
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DOI 10.1007/BF02454224
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References found in this work BETA
James H. Fetzer (1988). Program Verification: The Very Idea. Communications of the Acm 31 (9):1048--1063.
Brian Cantwell Smith (1985). The Limits of Correctness. Acm Sigcas Computers and Society 14 (1):18-26.

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