Select algorithms and data structures that match the problem domain and access patterns rather than using convenient but suboptimal approaches. For complex parsing tasks, use proper AST-based parsing instead of regex. Design data structures that align with how data will be accessed and modified.
Select algorithms and data structures that match the problem domain and access patterns rather than using convenient but suboptimal approaches. For complex parsing tasks, use proper AST-based parsing instead of regex. Design data structures that align with how data will be accessed and modified.
For example, when parsing structured expressions:
// Avoid regex for complex parsing
const objectLiteralRegex = /^\s*\{\s*([^}]*)\s*\}\s*$/;
// Use AST-based parsing instead
const parsed = new HtmlParser().parse(template, '', {
tokenizeExpansionForms: true,
tokenizeBlocks: true,
preserveLineEndings: true,
});
When designing data structures, consider access patterns:
// Instead of complex nested mappings
private _hostNodes = new Map<Node, Map<Node, Node[]>>();
// Consider simpler structures that match usage
private _hostNodes = new Map<Node, { insertionPoint: Node; styles: Node[] }>();
Create consistent interfaces for strategy patterns to eliminate conditional logic:
// Update strategies to share interface with consistent parameters
interface Strategy {
supports(element: Element): boolean;
build(element: Element, index?: number): ComponentTreeNode[];
}
This approach reduces complexity, improves maintainability, and ensures algorithms scale appropriately with data size and usage patterns.
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