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Fri 13 Nov 2020 01:39 - 01:40 at Virtual room 2 - SAT and Synthesis

Deciding termination of programs is probably the most famous problem in computer science. Synthesizing ranking functions for programs is a standard way to prove termination of programs. Currently, specific synthesis algorithms have to be developed for each specific type of programs. For instance, the synthesis of ranking functions for programs with linear variables updates is usually based on linear programming techniques and the like, while for programs with polynomial updates, it usually relies on semi-definite programming and the like. The same also applies to the synthesis of different types of ranking functions needed for proving program termination. Each time faced with a new type of programs and a new type of ranking functions, researchers have to spend a considerable amount of effort to develop specialized synthesis algorithms. In this paper, to save this extra effort, we present \textsc{SVMRanker}, a general framework for proving termination of programs, which is able to synthesize different types of ranking functions for programs with both linear and polynomial updates, based on Support-Vector Machines (SVM). We compare \textsc{SVMRanker} with the state-of-the-art tool \textsc{LassoRanker} on standard benchmarks. Empirical results show that \textsc{SVMRanker} is comparable with \textsc{LassoRanker} on programs with linear updates and can manage more programs with polynomial updates, making \textsc{SVMRanker} a valid complement to \textsc{LassoRanker} in proving program termination.

Fri 13 Nov

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01:30 - 02:00
01:30
2m
Talk
AlloyMC: Alloy Meets Model Counting
Tool Demos
Jiayi Yang University of Texas at Austin, USA, Wenxi Wang University of Texas at Austin, USA, Darko Marinov University of Illinois at Urbana-Champaign, Sarfraz Khurshid University of Texas at Austin
DOI
01:32
2m
Talk
HISyn: Human Learning-Inspired Natural Language Programming
Research Papers
Zifan Nan North Carolina State University, USA, Hui Guan University of Massachusetts at Amherst, USA, Xipeng Shen North Carolina State University, USA
DOI
01:35
1m
Talk
Inductive Program Synthesis over Noisy Data
Research Papers
Shivam Handa Massachusetts Institute of Technology, USA, Martin C. Rinard Massachusetts Institute of Technology, USA
DOI
01:37
1m
Talk
MCBAT: A Practical Tool for Model Counting Constraints on Bounded Integer Arrays
Tool Demos
Abtin Molavi Harvey Mudd College, USA, Mara Downing Harvey Mudd College, USA, Tommy Schneider Harvey Mudd College, USA, Lucas Bang Harvey Mudd College
DOI
01:39
1m
Talk
SVMRanker: A General Termination Analysis Framework of Loop Programs via SVM
Tool Demos
Xie Li , Yi Li Nanyang Technological University, Singapore, Yong Li Institute of Software, Chinese Academy of Sciences, Xuechao Sun Institute of Software at Chinese Academy of Sciences, China, Andrea Turrini State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Lijun Zhang Institute of Software, Chinese Academy of Sciences
DOI
01:41
19m
Talk
Conversations on SAT and Synthesis
Paper Presentations
Abtin Molavi Harvey Mudd College, USA, Jiayi Yang University of Texas at Austin, USA, Lucas Bang Harvey Mudd College, Xie Li , Zifan Nan North Carolina State University, USA, Shivam Handa Massachusetts Institute of Technology, USA, M: Abhik Roychoudhury National University of Singapore, Singapore