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Found 13 papers, 6 papers with code
MELT: Mining Effective Lightweight Transformations from Pull Requests
By leveraging code examples mined from the library source and automatically generated code examples based on the pull requests, we infer transformation rules in \comby, a language for structural code search and replace.
Graph Neural Networks For Mapping Variables Between Programs -- Extended Version
Typically, in order to compare two programs, a relation between both programs' sets of variables is required.
UpMax: User partitioning for MaxSAT
It has been shown that Maximum Satisfiability (MaxSAT) problem instances can be effectively solved by partitioning the set of soft clauses into several disjoint sets.
InvAASTCluster: On Applying Invariant-Based Program Clustering to Introductory Programming Assignments
Due to the vast number of students enrolled in Massive Open Online Courses (MOOCs), there has been an increasing number of automated program repair techniques focused on introductory programming assignments (IPAs).
C-Pack of IPAs: A C90 Program Benchmark of Introductory Programming Assignments
Due to the vast number of students enrolled in Massive Open Online Courses (MOOCs), there has been an increasing number of automated program repair techniques focused on introductory programming assignments (IPAs).
New Core-Guided and Hitting Set Algorithms for Multi-Objective Combinatorial Optimization
In the last decade, a plethora of algorithms for single-objective Boolean optimization has been proposed that rely on the iterative usage of a highly effective Propositional Satisfiability (SAT) solver.
Exact and approximate determination of the Pareto set using minimal correction subsets
First, we show that it is possible to use MCS enumeration to solve MOBO problems such that each MCS necessarily corresponds to a Pareto-optimal solution.
SQUARES: A SQL Synthesizer Using Query Reverse Engineering
As a result, many of them can provide examples of data transformations but are unable to produce the desired query.
Reflections on "Incremental Cardinality Constraints for MaxSAT"
To celebrate the first 25 years of the International Conference on Principles and Practice of Constraint Programming (CP) the editors invited the authors of the most cited paper of each year to write a commentary on their paper.
Generalized Totalizer Encoding for Pseudo-Boolean Constraints
We show the superiority of GTE with respect to other encodings when large pseudo-Boolean constraints have low number of distinct coefficients.
DistMS: A Non-Portfolio Distributed Solver for Maximum Satisfiability
The most successful parallel SAT and MaxSAT solvers follow a portfolio approach, where each thread applies a different algorithm (or the same algorithm configured differently) to solve a given problem instance.
Exploiting Resolution-based Representations for MaxSAT Solving
Usually, these MaxSAT algorithms perform better when small unsatisfiable subformulas are found early.
Incremental Cardinality Constraints for MaxSAT
In general, MaxSAT algorithms perform a succession of SAT solver calls to reach an optimum solution making extensive use of cardinality constraints.
