What is the fastest path for Code Radar benchmark methodology?
Code Radar benchmark methodology measures cold, warm, full, quick, and diff-scope scan behavior on real repositories with reproducible inputs.
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Benchmark Methodology
Measure Code Radar scan time on real repositories with repeatable cold, warm, full, and diff-scope benchmark runs.
Direct answer
Benchmark Methodology
Measure Code Radar scan time on real repositories with repeatable cold, warm, full, and diff-scope benchmark runs.
Which commands matter first for Code Radar benchmark methodology?
Start with `radar scan . --quick --no-cache`, `radar scan . --quick`, and `radar trend`. These commands keep implementation proof close to the repository instead of turning the docs page into a generic product description.
What evidence confirms Code Radar benchmark methodology works?
Confirm repository size, selected files, duration, scan mode, cache state, platform, and slow phases when relevant. This evidence should be visible before moving from documentation to a paid or shared workflow.
What should the reader avoid for Code Radar benchmark methodology?
Do not compare benchmark numbers without matching repository scope, cache state, scan mode, and platform. Next step: Use benchmarks for performance proof, then inspect sample reports to decide whether the finding quality justifies rollout.
Content decision bridge
Turn benchmark workflow into a product decision.
Readers on Benchmark Methodology need a short route from answer-seeking to proof, rollout, and purchase evidence. Measure Code Radar scan time on real repositories with repeatable cold, warm, full, and diff-scope benchmark runs.
Verify the proof surface.
Benchmark Methodology should lead to product proof, not only more reading. For this page, proof means a first local scan on real code with inspectable findings.
sast benchmarklocal sast speed
Run local proofApply the repeat workflow.
Benchmark Methodology becomes useful when the reader can repeat the workflow from the guide on a real repository. Here, rollout means a repeatable local scan, report, hook, or agent handoff.
developer first sastlocal security review tool
Apply workflowChoose the paid boundary.
Benchmark Methodology should create a purchase path only when the product owns the next repeated job. For this intent, buying is justified by full local scans, exports, MCP, hooks, or repository validation.
repository security gateteam sast pricing
Review plansCold and warm runs
Use `--no-cache` for a cold run, then run again to measure warm cache behavior. Keep output in terminal mode when measuring local UX.
radar scan . --quick --no-cache
radar scan . --quick
radar trendWhat to report
Report repository size, selected files, duration, scan mode, cache state, platform, and top slow phases when relevant.
Implementation FAQ
Confirm the command, expected evidence, failure boundary, and next workflow before treating the task as complete.
What is the fastest path for Code Radar benchmark methodology?
Code Radar benchmark methodology measures cold, warm, full, quick, and diff-scope scan behavior on real repositories with reproducible inputs.
Which commands matter first for Code Radar benchmark methodology?
Start with `radar scan . --quick --no-cache`, `radar scan . --quick`, and `radar trend`. These commands keep implementation proof close to the repository instead of turning the docs page into a generic product description.
What evidence confirms Code Radar benchmark methodology works?
Confirm repository size, selected files, duration, scan mode, cache state, platform, and slow phases when relevant. This evidence should be visible before moving from documentation to a paid or shared workflow.
What should the reader avoid for Code Radar benchmark methodology?
Do not compare benchmark numbers without matching repository scope, cache state, scan mode, and platform. Next step: Use benchmarks for performance proof, then inspect sample reports to decide whether the finding quality justifies rollout.