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- | ====== Introduction ====== | ||
- | SVMRanker is a general framework for proving termination of loop programs.SVMRanker utilizes SVM techniques to synthesize multiphase ranking functions to prove program termination. | ||
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- | ====== Future Work ====== | ||
- | * Support more types of templates, such as fractional and with n-roots, and ranking functions, such as lexicographic ranking functions, piece-wise ranking functions and so on, as described in [1]. | ||
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- | * Strengthen the ability of SVMRanker to prove nontermination, | ||
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- | * Synthesizing coefficients of ranking functions with deep neural networks. | ||
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- | ====== Main References ====== | ||
- | - Jan Leike and Matthias Heizmann. 2015. Ranking Templates for Linear Loops. LMCS 11, 1 (2015). | ||
- | - Ben-Amram A.M., Genaim S. (2017) On Multiphase-Linear Ranking Functions. In: Majumdar R., Kunčak V. (eds) Computer Aided Verification. CAV 2017. Lecture Notes in Computer Science, vol 10427. Springer, Cham. | ||
- | - Yi Li, Xuechao Sun, Yong Li, Andrea Turrini, and Lijun Zhang. 2019. Synthesizing Nested Ranking Functions for Loop Programs via SVM. In ICFEM (LNCS, Vol. 11852). 438–454. | ||
- | - Michael Colón and Henny Sipma. 2001. Synthesis of Linear Ranking Functions. In TACAS (LNCS, Vol. 2031). 67–81. |