01
Neuro-symbolic architectures
LLM agents integrated with proof assistants, model checkers, solvers, static analyzers, and compiler feedbackverifier-guided training and inference
02
Specification generation and quality
autoformalizationspecification miningambiguity and inconsistency detectionproperty-based validationhuman-guided refinement
03
Proof search and engineering
premise selectiontactic learningproof repairmaintenancescalabilitycompatibility across theorem-proving systems
04
Program verification and repair
deductive verificationmodel checkingsymbolic executionabstract interpretationtestingdebuggingcertified repairequivalence checkingbehavior preservation
05
Verification applications
securitysmart contractsmemory safetysupply chainsaccess-control policiesnetwork configurationsinfrastructure-as-codedistributed protocols
06
Verification of and for AI
formal validation of generated outputsruntime monitoring of agentsverified guardrailsconstrained tool use
07
Solver and trusted infrastructure
scalable SAT/SMT solvinglearned heuristicsproof certificatesindependent checkingtrusted computing basesverifier validation
08
Human-centered verification
mixed-initiative interfacesexplanationstrust calibrationaccessibility for developers without formal-methods expertise
09
Benchmarks and deployment
datasets and metrics for end-to-end guaranteesscalability studiesreproducibilitynegative resultsindustrial experience