Results for “detection-gap-analysis”

Analyzes production code to find gaps in existing tests by reasoning about hypothetical mutations and checking whether tests would catch them.

Identifies the weakest samples per ground-truth label in NVIDIA TAO VCN Classify experiments by running a Docker container that performs threshold sweep, weakness scoring, and per-lighting expansion, then surfaces top-K weak samples for downstream augmentation or relabeling.

Extract false-positive and false-negative gaps from VLM binary-classification-question predictions by comparing model responses against ground truth, producing a structured JSONL file and summary report for downstream root-cause analysis.

Automates detection engineering workflows in Google SecOps by extracting threat intelligence, generating detection opportunities, simulating attacker behavior with synthetic events, evaluating rule coverage, and creating new YARA-L 2.0 rules to close gaps.

Analyzes .NET project code coverage and CRAP (Change Risk Anti-Patterns) scores to identify risk hotspots, methods blocking coverage gains, and prioritize where to add tests.