The v1.3.1 comparator used a sum-of-weights priorityScore. With weights
15..1 across 15 specs, three lower-priority specs (BNK+BRM+CRF, sum 39)
could outrank a single top-priority spec (HCR alone, sum 15). In
priority-order mode this surfaced lower-priority plans above the user's
top spec — the opposite of intent.
Fix: replace sum-of-weights with a lexicographic rank weight. Each spec
encodes as a bit, top-ranked spec = highest bit. So [HCR] = 16384 beats
[BNK,BRM,CRF,EMT,ENT,FIN,FIM,GLB,LCM,MGT,MKT,MTO,SBI,STR] = 16383. A plan
containing a higher-ranked spec ALWAYS outranks any plan that doesn't,
regardless of how many lower-ranked specs the latter contains. Lower
specs only act as tiebreakers among plans that all contain the same
higher-ranked spec.
Both modes use lex weight as the priority key; modes still differ in
ordering:
priority-order: (rankWeight desc, count desc, key asc)
maximize-count: (count desc, rankWeight desc, key asc)
Score display changes from the legacy sum (e.g. "score 29") to the lex
weight in compact form (e.g. "score 24.6k"). Hover for full integer.
The display now actually corresponds to ranking order.
Other:
- Cache cap (500k leaves) now retains existing entries instead of
clearing on overflow. New entries past the cap are dropped; the
cached subset stays available as a warm starting point.
- Two new lex-weight tests in searchDecisionTree.test.ts:
- single top-ranked spec outweighs all 14 others combined
- tiebreaker is the next-ranked spec
- All 84 tests pass; cached leaves stay valid across the comparator
change since achievedSpecs (the input to lex compare) is unchanged.
Files: solver/priority.ts (new functions), solver/decisionTree.ts
(comparators take ranking), components/{TopPlans,CourseSelection}.tsx
(score display + Recommended badge), state/appState.ts (cache-cap
behavior), vite.config.ts, CHANGELOG.md.
The v1.3.0 saturation termination silently capped the search after only
the heuristic-favored part of the tree, leaving most per-set ceiling cells
stuck at "0 specs" and hiding genuinely-feasible 3-spec plans in
maximize-count mode. Replace with full exhaustive enumeration plus a
batch of UX refinements that emerged during testing.
Algorithm:
- Drop the saturation early-termination entirely. Search now runs the
full open-set cartesian product to completion; the iteration cap is
also removed so no scenario exits partial.
- Add mode-dependent DFS child ordering: priority-order keeps the
priority-target-first heuristic; maximize-count orders children by
descending count of qualifications for reachable specs (generalist
courses tried first).
- Make the (count, priorityScore) comparator mode-aware: priority-order
ranks by (priorityScore, count) so the user's top spec surfaces;
maximize-count ranks by (count, priorityScore) so the highest count
wins. The same rule drives both top-K position and per-cell ceiling
selection (and the Recommended badge).
- Add an evaluated boolean to each ChoiceOutcome and set it on first
leaf evaluation. Distinguishes "still searching" from "evaluated, no
specs achieved" so the UI never shows misleading 0 specs for a cell
the search hasn't reached yet.
- Throttled progress events (~100ms) carrying iterations / total leaf
count, drive both the per-set spinner and the global progress bar.
UI:
- Top Plans header shows a horizontal progress bar with
"iterations / total · NN%" while the search runs; collapses to
"Search complete · N explored" on completion.
- Per-set spinner next to each elective set heading while any choice
in that set is unevaluated.
- Per-cell pulsing dot + "searching" text for unevaluated cells.
- Replace the "(HCR, BNK, ...)" text labels on each course with
color-coded SpecTag pills using a new fixed per-spec palette
(app/src/data/specColors.ts). Same palette applied to the Top Plans
achievement badges so the two views are visually consistent.
- "Top outcome if picked ↓" caption above the right side of each open
elective set so the spec tags are clearly identified as decision-tree
outcomes (not the course's own qualifications).
- Recommended badge moved inline next to the course name (instead of
on a separate row below) to keep button heights stable.
Tests:
- Replace the saturation early-termination test with an exhaustion test
asserting every cell ends with evaluated: true and partial: false.
- Add mode-dependent ordering test (max-count visits Climate Finance
before Corporate Governance in fall3).
- Add evaluated-flag transition test.
- Add throttled progress-event test (>= ~100ms between consecutive
emits).
- Performance smoke updated to a 60s budget for the exhaustive
user-scenario search; 8-open-set typical case completes in ~7s.
Files: solver/decisionTree.ts, solver/priority.ts (already shipped),
data/specColors.ts (new), components/{TopPlans,CourseSelection}.tsx,
state/appState.ts, workers/decisionTree.worker.ts,
__tests__/searchDecisionTree.test.ts, vite.config.ts, CHANGELOG.md,
openspec/changes/decision-tree-exhaustive-search/* (full change spec).
- Course info popovers with description, instructors, and specialization
tags; opens on hover (desktop) or tap (mobile) with smart positioning
- Page title and graduation cap favicon in NYU Stern purple
- Desktop layout fits viewport without page-level scrolling
- Mark "Managing Growing Companies" as cancelled with visual indicator and solver exclusion
- Prevent selecting duplicate courses across elective sets (e.g., same course in Spring and Summer)
- Add 2.5-credit interval tick marks to specialization progress bars
- Bump version to 1.1.0 with date display in UI header
- Replace terse one-line optimization mode descriptions with clearer multi-sentence
explanations of how Maximize Count and Priority Order algorithms behave
- Add skeleton loading placeholders on course buttons while analysis is pending
- Auto-expand achieved specializations to show credit breakdown by default
- Add instructional subtitles to Course Selection and Specializations sections
- Make Clear and Clear All buttons more prominent with visible backgrounds
Replace top-level mutual exclusion banner with dynamic per-course
"Required for ..." labels derived from specialization data. Labels
appear on any course that is a specialization prerequisite, across
all elective sets.
Bill