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Xuechao Sun

dblp:234/6262 · DBLP profile ↗
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6ranked-venue papers
0as first author
2since 2021 · last 2022
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 5 · 1 since 2021Theory of computation · 2 · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
2 papers
Program verification · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Distributed systems · 100%
Databases, data mining, and information retrieval
1 paper
Distributed and cloud data management · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Distributed systems
consensus
0.512021
Formal Verification of Consensus in the Taurus Distributed Database · FM 2021
Program verification › termination analysis
ranking function synthesis
0.412020
SVMRanker: a general termination analysis framework of loop programs via SVM · ESEC/SIGSOFT FSE 2020
Program verification
termination analysis
0.412020
SVMRanker: a general termination analysis framework of loop programs via SVM · ESEC/SIGSOFT FSE 2020

Methods — techniques the papers use, named apart from their topics

formal verification · 1.5support vector machine · 0.4
YearPublicationVenuePosition
2022 Synthesizing ranking functions for loop programs via SVM
Xie Li, Yong Li 0031, Xuechao Sun, Andrea Turrini, Lijun Zhang 0001
Theor. Comput. Sci.4
2021 Formal Verification of Consensus in the Taurus Distributed Database
Song Gao 0014, Bohua Zhan, Depeng Liu, Xuechao Sun, Yanan Zhi, David N. Jansen, Lijun Zhang 0001
FM4
2020 Proving Non-inclusion of Büchi Automata Based on Monte Carlo Sampling
Yong Li 0031, Andrea Turrini, Xuechao Sun, Lijun Zhang 0001
ATVA3
2020 SVMRanker: a general termination analysis framework of loop programs via SVM
abstract
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 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 SVMRanker with the state-of-the-art tool LassoRanker on standard benchmarks. Empirical results show that SVMRanker is comparable with LassoRanker on programs with linear updates and can manage more programs with polynomial updates, making SVMRanker a valid complement to LassoRanker in proving program termination.
Xie Li, Yong Li 0031, Xuechao Sun, Andrea Turrini, Lijun Zhang 0001
ESEC/SIGSOFT FSE4
2019 Synthesizing Nested Ranking Functions for Loop Programs via SVM
Xuechao Sun, Yong Li 0031, Andrea Turrini, Lijun Zhang 0001
ICFEM2
2019 ROLL 1.0: \omega -Regular Language Learning Library
abstract
We present ROLL 1.0, an $$\omega $$ -regular language learning library with command line tools to learn and complement Büchi automata. This open source Java library implements all existing learning algorithms for the complete class of $$\omega $$ -regular languages. It also provides a learning-based Büchi automata complementation procedure that can be used as a baseline for automata complementation research. The tool supports both the Hanoi Omega Automata format and the BA format used by the tool RABIT. Moreover, it features an interactive Jupyter notebook environment that can be used for educational purpose.
Yong Li 0031, Xuechao Sun, Andrea Turrini, Yu-Fang Chen 0001, Junnan Xu
TACAS (1)2