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arXiv · 1405.4189

Termination Analysis by Learning Terminating Programs

Matthias Heizmann·Jochen Hoenicke·Andreas Podelski
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Abstract

We present a novel approach to termination analysis. In a first step, the analysis uses a program as a black-box which exhibits only a finite set of sample traces. Each sample trace is infinite but can be represented by a finite lasso. The analysis can "learn" a program from a termination proof for the lasso, a program that is terminating by construction. In a second step, the analysis checks that the set of sample traces is representative in a sense that we can make formal. An experimental evaluation indicates that the approach is a potentially useful addition to the portfolio of existing approaches to termination analysis.

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Matthias Heizmann, Jochen Hoenicke, Andreas Podelski. 2014-05-16. Termination Analysis by Learning Terminating Programs. https://arxiv.org/abs/1405.4189

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