Underapproximate types with symbolic traces guide synthesis of test generators that outperform defaults in property-based testing and model checking for effectful programs.
Title resolution pending
7 Pith papers cite this work. Polarity classification is still indexing.
7
Pith papers citing it
citation-role summary
background 3
citation-polarity summary
roles
background 3polarities
background 3representative citing papers
ML Defender achieves F1=0.9985 on CTU-13 Neris botnet detection with a dual fast-detector plus random forest model, outperforming Suricata (zero alerts) and Zeek (F1=0.042) in a three-paradigm comparison.
A Lean library called Palamedes uses synthesis rules from generator semantics and catamorphism-anamorphism rewriting to automatically produce correct constrained random generators.
ContractEval benchmark on 364 tasks shows code LLMs achieve 75-82% functional pass@1 but 0% contract satisfaction under standard prompting, rising only to 23-41% with explicit contracts.
Allegro applies multi-stage programming to PBT generators and pairs it with faster randomness to achieve up to 13x faster bug discovery while exactly preserving generator semantics.
A symbolic protocol operationalizes Peirce's tripartite reasoning for LLMs using five algebraic invariants including a Weakest Link bound to enforce logical consistency and prevent weak premises from supporting strong conclusions.
Aporia makes design decisions explicit and interactive in AI-assisted programming, leading to higher engagement and 5x fewer mental model disagreements with code in a 14-person user study compared to a baseline agent.
citing papers explorer
-
Trace-Guided Synthesis of Effectful Test Generators
Underapproximate types with symbolic traces guide synthesis of test generators that outperform defaults in property-based testing and model checking for effectful programs.
-
ML Defender (aRGus NDR): An Open-Source Embedded ML NIDS for Botnet and Anomalous Traffic Detection in Resource-Constrained Organizations
ML Defender achieves F1=0.9985 on CTU-13 Neris botnet detection with a dual fast-detector plus random forest model, outperforming Suricata (zero alerts) and Zeek (F1=0.042) in a three-paradigm comparison.
-
The Search for Constrained Random Generators
A Lean library called Palamedes uses synthesis rules from generator semantics and catamorphism-anamorphism rewriting to automatically produce correct constrained random generators.
-
ContractEval: A Benchmark for Evaluating Contract-Satisfying Assertions in Code Generation
ContractEval benchmark on 364 tasks shows code LLMs achieve 75-82% functional pass@1 but 0% contract satisfaction under standard prompting, rising only to 23-41% with explicit contracts.
-
Fail Faster: Staging and Fast Randomness for High-Performance PBT
Allegro applies multi-stage programming to PBT generators and pairs it with faster randomness to achieve up to 13x faster bug discovery while exactly preserving generator semantics.
-
Structured Abductive-Deductive-Inductive Reasoning for LLMs via Algebraic Invariants
A symbolic protocol operationalizes Peirce's tripartite reasoning for LLMs using five algebraic invariants including a Weakest Link bound to enforce logical consistency and prevent weak premises from supporting strong conclusions.
-
Decision-Oriented Programming with Aporia
Aporia makes design decisions explicit and interactive in AI-assisted programming, leading to higher engagement and 5x fewer mental model disagreements with code in a 14-person user study compared to a baseline agent.