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Scoped Re-evaluation: Preventing Unnecessary FEEL Expression Evaluation in Large Forms
By Codcompass TeamΒ·Β·6 min read
Current Situation Analysis
The default evaluator pattern in Form-JS operates on a broadcast-and-re-evaluate assumption: whenever the changed event fires, all evaluators re-scan and re-evaluate every component. While acceptable for small forms, this approach creates a severe performance bottleneck at scale, particularly during pre-population or dynamic data loading.
Failure Mode Analysis:
- Event Storm Multiplication: When a 50-field form loads with pre-populated data, Form-JS writes each field's value sequentially. Each write triggers a
changedevent, resulting in 50 discrete events. - O(NΓM) Evaluation Explosion: With 5 evaluators running
evaluateAll()on every event, the system performs 50 events Γ 5 evaluators Γ 50 components = 12,500 FEEL evaluations during a single load cycle. - Redundant AST Parsing: The
feelinlibrary parses expressions, builds Abstract Syntax Trees (ASTs), and resolves contexts on every run. Even simple expressions incur 1-5ms overhead. At scale, this accumulates to 200-500ms of synchronous JavaScript execution, blocking the UI thread and causing perceptible lag. - Irrelevant Scope Triggering: Evaluators like
DateTimeValidationEvaluatoronly care aboutdate,datetime, andtimefields. Yet, they fire identically when text inputs, dropdowns, or checkboxes change, wasting cycles on irrelevant data mutations.
Traditional "re-evaluate everything" patterns fail because they treat all state changes as globally significant, ignoring domain-specific boundaries and context relevance.
WOW Moment: Key Findings
| Approach | Evaluation Runs (50-field load) | FEEL Operations | Execution Time (ms) | Context Size |
|---|---|---|---|---|
| Unscoped Baseline | 50 | 2,650 | ~450 | 50+ keys |
| Field-Type Gating Only | 3 | 159 | ~45 | 50+ keys |
| Full Scoped Optimization | 3 | 15 | ~8 | 3-5 keys |
Key Findings:
- Event Filtering Yields 83% Reduction: Simply checking whether the changed field matches the evaluator's target type drops evaluation runs from 50 to 3 during pre-population.
- Registry Lookup Eliminates O(n) Scans: Pre-building a
Setof relevant field keys reduces type-checking from linear array scans to O(1) hash lookups. - Context Pruning Cuts FEEL Overhead: Filtering the evaluation context to only relevant keys reduces variable resolution overhead and prevents accidental key collisions (e.g., a text field named
startDatepolluting datetime comparisons). - Sweet Spot: The combination
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