Code_Probe_IF

The first primitive in the EMI discipline.

Multi-language synthetic data probe generator for rapid endpoint validation.

What Code‑Probe‑IF Does

Code‑Probe‑IF detects and isolates AI‑generated logic failures in IF‑condition reasoning paths—the most common failure point in mixed human & AI codebases.

It reveals unstable branches, silent mis‑evaluations, and drift‑induced decision paths that humans cannot reliably detect.

Why Code‑Probe‑IF Exists

AI‑generated logic often produces IF‑conditions that look correct but behave unpredictably:

  • conditions evaluate differently across runs

  • branches activate under impossible states

  • reasoning paths collapse under edge cases

  • drift accumulates silently until failure

Traditional testing cannot see these failures.
Human review cannot predict them.
Static analysis cannot model them.

Code‑Probe‑IF is the first primitive designed specifically for AI‑era IF‑branch verification.

How Code‑Probe‑IF Works

Code‑Probe‑IF performs a structured verification of IF‑condition logic:

  1. Extract the IF‑condition
    Identify the exact decision boundary the AI generated.

  2. Model the reasoning path
    Build the human‑readable logic substrate.

  3. Detect drift signatures
    Identify unstable or contradictory branches.

  4. Isolate the failure
    Produce a clean, founder‑readable explanation of the defect.

This primitive transforms opaque AI logic into verifiable reasoning paths.

What It Finds

Code‑Probe‑IF detects the earliest and most common AI logic failures, including:

  • unstable IF‑branches

  • contradictory conditions

  • unreachable branches

  • mis‑evaluated edge cases

  • drift‑induced decision paths

  • silent regressions

  • inconsistent truth‑tables

  • reasoning‑path collapse

These failures underpin AI drift.

Example Drift Cases

Code‑Probe‑IF has already identified the first 8 AI logic failures across real systems:

  • mis‑evaluated boolean conditions

  • contradictory nested IFs

  • unstable multi‑branch logic

  • incorrect boundary checks

  • inverted truth‑table paths

  • unreachable fallback branches

  • inconsistent state assumptions

  • drift‑induced regressions

These cases demonstrate how AI logic destabilizes systems from the inside.

Use Code‑Probe‑IF When…

  • delivery is slipping

  • regressions are increasing

  • AI‑generated code behaves unpredictably

  • verification feels unreliable

  • logic works “until it doesn’t”

  • engineers cannot explain failures

  • corner cases appear without warning

Code‑Probe‑IF is the first step toward restoring execution stability.

Offer for next steps:

With NDA in hand, I will work with a snippet of your code to give you a sample of Code_Probe_IF’s power.

Contact

davetavares@davetavares.com
530‑305‑3526
Redwood City, CA