test_reference_edge_cases

Edge Case Tests

This file tests boundary conditions and edge cases from the Scriba reference.

%% ========================================================== %% EDGE CASE A: Animation with exactly 1 step (minimum) %% ==========================================================

A: Single-Step Animation

%% ========================================================== %% EDGE CASE B: Animation with 30 steps (soft limit boundary) %% ==========================================================

B: 30-Step Animation (Soft Limit)

Step 1 / 30

Step 1 of 30.

Step 2 / 30

Step 2 of 30.

Step 3 / 30

Step 3 of 30.

Step 4 / 30

Step 4 of 30.

Step 5 / 30

Step 5 of 30.

Step 6 / 30

Step 6 of 30.

Step 7 / 30

Step 7 of 30.

Step 8 / 30

Step 8 of 30.

Step 9 / 30

Step 9 of 30.

Step 10 / 30

Step 10 of 30.

Step 11 / 30

Step 11 of 30.

Step 12 / 30

Step 12 of 30.

Step 13 / 30

Step 13 of 30.

Step 14 / 30

Step 14 of 30.

Step 15 / 30

Step 15 of 30.

Step 16 / 30

Step 16 of 30.

Step 17 / 30

Step 17 of 30.

Step 18 / 30

Step 18 of 30.

Step 19 / 30

Step 19 of 30.

Step 20 / 30

Step 20 of 30.

Step 21 / 30

Step 21 of 30.

Step 22 / 30

Step 22 of 30.

Step 23 / 30

Step 23 of 30.

Step 24 / 30

Step 24 of 30.

Step 25 / 30

Step 25 of 30.

Step 26 / 30

Step 26 of 30.

Step 27 / 30

Step 27 of 30.

Step 28 / 30

Step 28 of 30.

Step 29 / 30

Step 29 of 30.

Step 30 / 30

Step 30 of 30 — exactly at the soft limit.

%% ========================================================== %% EDGE CASE C: Empty narrate %% ==========================================================

C: Empty Narrate

%% ========================================================== %% EDGE CASE D: Multiple primitives of same type %% ==========================================================

D: Two Arrays and Two Graphs

%% ========================================================== %% EDGE CASE E: Very long narrate with lots of inline math %% ==========================================================

E: Long Narrate with Heavy Math

Step 1 / 2

Consider the recurrence $T(n) = 2T(n/2) + O(n)$ which by the Master Theorem yields $T(n) = O(n \log n)$ . For dynamic programming, the transition is $dp[i][j] = \min_{k=i}^{j-1}(dp[i][k] + dp[k+1][j] + \sum_{m=i}^{j} a_m)$ . The expected value is $E[X] = \sum_{x} x \cdot P(X = x) = \int_{-\infty}^{\infty} x f(x) dx$ and the variance satisfies $\text{Var}(X) = E[X^2] - (E[X])^2 \geq 0$ . By the Cauchy–Schwarz inequality, $\left(\sum_{i=1}^{n} a_i b_i\right)^2 \leq \left(\sum_{i=1}^{n} a_i^2\right)\left(\sum_{i=1}^{n} b_i^2\right)$ . Furthermore, $\binom{n}{k} = \frac{n!}{k!(n-k)!}$ and $\sum_{k=0}^{n}\binom{n}{k} = 2^n$ .

Step 2 / 2

After all that math, we highlight cell 1 with $O(1)$ cost.

%% ========================================================== %% EDGE CASE F: Array with size=1 (minimum) %% ==========================================================

F: Size-1 Array

%% ========================================================== %% EDGE CASE G: Graph with single node, no edges %% ==========================================================

G: Single-Node Graph

%% ========================================================== %% EDGE CASE H: Highlight ephemeral clearing across steps %% ==========================================================

H: Highlight Ephemeral Clearing

%% ========================================================== %% EDGE CASE I: Multiple annotate on same target, different arrow_from %% ==========================================================

I: Multiple Annotations Same Target

%% ========================================================== %% EDGE CASE J: Deeply nested foreach (2 levels) %% ==========================================================