AN EMPIRICAL EVALUATION OF AUTOMATED THEOREM PROVERS IN SOFTWARE CERTIFICATION

Author:

DENNEY EWEN1,FISCHER BERND1,SCHUMANN JOHANN1

Affiliation:

1. RIACS/NASA Ames Research Center, M/S 269-2, Moffett Field, California 94035, USA

Abstract

We describe a system for the automated certification of safety properties of NASA software. The system uses Hoare-style program verification technology to generate proof obligations which are then processed by an automated first-order theorem prover (ATP). We discuss the unique requirements this application places on the ATPs, focusing on automation, proof checking, traceability, and usability, and describe the resulting system architecture, including a certification browser that maintains and displays links between obligations and source code locations. For full automation, the obligations must be aggressively preprocessed and simplified, and we demonstrate how the individual simplification stages, which are implemented by rewriting, influence the ability of the ATPs to solve the proof tasks. Our results are based on 13 comprehensive certification experiments that lead to 366 top-level safety obligations and ultimately to more than 25,000 proof tasks which have been used to determine the suitability of the high-performance provers DCTP, E-Setheo, E, Gandalf, Otter, Setheo, Spass, and Vampire, and our associated infrastructure. The proofs found by Otter have been checked by Ivy.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Artificial Intelligence

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Formal Verification Methods;Encyclopedia of Information Science and Technology, Third Edition;2015

2. ATP-based Cross-Verification of Mizar Proofs: Method, Systems, and First Experiments;Mathematics in Computer Science;2008-10-28

3. Certifiable Program Generation;Generative Programming and Component Engineering;2005

4. ATP Cross-Verification of the Mizar MPTP Challenge Problems;Logic for Programming, Artificial Intelligence, and Reasoning

5. Model-Based Quality Assurance of Automotive Software;Model Driven Engineering Languages and Systems

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