Automated Regression Test Matrix (2D)

Test Suite Controls

Code modules (rows) 6

Test cases per module (cols) 7

Injected bug severity (drag coeff.) 0.10

Pass tolerance (RMSE, m) 5.00

CI flakiness (rerun noise) 15%

CI reruns per case 3

Sweep speed (tests/s) 10

Live Results

Progress

0 / 0

Pass rate

—

Avg RMSE

— m

Current run

—

Flaky tests detected

0 (0%)

Pass Fail Pending Flaky

How it works

Each grid cell is one automated test case: module (row) versus test case (column). A projectile is launched with speed v (columns) and angle θ (rows); the expected result is the closed-form, drag-free trajectory:

y_exp(x) = x·tanθ − g·x² / (2v²cos²θ)
R_exp    = v²·sin(2θ) / g

The simulated result — the "code under test" — numerically integrates Newton's second law with explicit Euler steps, including a quadratic drag term whose strength is the injected bug severity k:

ax = −k·|v|·vx,  ay = −g − k·|v|·vy

Five checkpoints along the expected range are compared to the simulated trajectory and combined into a Root Mean Square Error. A case turns green when RMSE stays under the tolerance and red when it exceeds it — the same pass/fail logic a CI pipeline applies after every code change.

The CI flakiness slider adds independent random noise to each case's RMSE on every rerun (real CI infrastructure jitter: timing, resource contention, race conditions — unrelated to the actual bug). The suite reruns every case the configured number of times; a case whose pass/fail verdict changes between reruns is flagged flaky and drawn with a yellow border, regardless of its latest verdict — exactly what a flaky-test detector looks for in a real regression matrix.

RUNNER: idle