Search Results for author:
Found 11 papers, 5 papers with code
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.
Large Language Models for Test-Free Fault Localization
Specifically, we propose to overcome the left-to-right nature of LLMs by fine-tuning a small set of bidirectional adapter layers on top of the representations learned by LLMs to produce LLMAO, the first language model based fault localization approach that locates buggy lines of code without any test coverage information.
Approximation Strategies for Incomplete MaxSAT
Incomplete MaxSAT solving aims to quickly find a solution that attempts to minimize the sum of the weights of the unsatisfied soft clauses without providing any optimality guarantees.
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.
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.
Relating Complexity-theoretic Parameters with SAT Solver Performance
Over the years complexity theorists have proposed many structural parameters to explain the surprising efficiency of conflict-driven clause-learning (CDCL) SAT solvers on a wide variety of large industrial Boolean instances.
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.
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.
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.
FOREST: An Interactive Multi-tree Synthesizer for Regular Expressions
Experimental results show that FOREST successfully returns the desired regular expression in 72% of the instances and outperforms REGEL, a state-of-the-art regular expression synthesizer.
