When implementing algorithms for pairing/alignment, matching/routing, search, or event fan-out, require a clearly stated invariant and explicit boundary/edge-case behavior, then back it with targeted tests.

Practical checklist: 1) Define the mapping/invariant precisely

2) Make boundary behavior unambiguous

3) Use data structures that support required operations directly

4) Test the invariants at the boundaries

Mini example (alignment invariant style):

// Within each hunk: D deletions followed by A additions.
// Invariant: row indices correspond across panes.
let pairs = d.min(a);
for i in 0..pairs {
  left_row(i) = deleted[i];
  right_row(i) = added[i];
}
// Excess
for i in pairs..d {
  left_row(i) = deleted[i];
  right_row(i) = blank();
}
for i in pairs..a {
  left_row(i) = blank();
  right_row(i) = added[i];
}

Adopting this standard prevents “almost correct” algorithms that break only at boundaries (chunk edges, quota-trigger thresholds, prefix boundary rules, uneven hunk sizes) and makes future maintenance safer because invariants are explicit and testable.