Array.map() creates a new array with transformed elements, returning the result of applying a function to each element. In contrast, forEach() executes a function for each element but returns undefined, primarily used for side effects. Map preserves array length and maintains a one-to-one relationship with elements, making it ideal for data transformation. Consider performance implications for large arrays and memory usage when choosing between them.
reduce() processes array elements from left to right, while reduceRight() processes from right to left. Both methods take an accumulator and current value, combining elements into a single result. They're useful for sum calculations, object transformations, and array flattening. Consider initial value provision to avoid type errors and unexpected results with empty arrays. The direction matters particularly when order affects the result, such as string concatenation or mathematical operations.
Array.sort() accepts comparison function returning negative, zero, or positive values. Implement stable sorting for consistent results. Handle special values (null, undefined) appropriately. Consider case sensitivity and locale-specific sorting. Document comparison logic and requirements. Implement proper error handling for invalid comparisons.
Pre-allocate array size when possible. Use appropriate array methods for operations. Consider memory usage and garbage collection. Implement proper caching strategies. Handle large array operations efficiently. Document performance requirements and constraints. Monitor array operation performance.
slice() creates a shallow copy of array portion without modifying the original array, taking start and end indices. splice() modifies the original array by removing, replacing, or adding elements, returning removed elements. slice() is used for array copying and extraction, while splice() is for array mutation. Consider immutability requirements when choosing between them. splice() changes array length and indices, requiring careful handling in iterations.
Typed arrays provide fixed-length arrays of specific numeric types. Used for binary data manipulation, WebGL, and performance-critical operations. Consider memory usage and numeric precision requirements. Handle endianness appropriately. Implement proper bounds checking and type conversion. Document data format requirements.
Implement efficient chunking algorithms. Handle remainder elements properly. Consider memory usage with large arrays. Implement proper validation. Document chunking requirements. Handle edge cases appropriately.
Array.find() returns first matching element, while filter() returns all matching elements. For sorted arrays, consider binary search implementation for better performance. indexOf() and includes() check element existence. For complex objects, use custom comparison functions. Consider performance implications with large arrays and implement proper indexing strategies for frequent searches.
Use immutable methods (map, filter, reduce) for data transformation. Implement proper error handling for array operations. Consider performance with large arrays. Use appropriate array methods instead of loops when possible. Handle sparse arrays and holes appropriately. Maintain type consistency within arrays. Document array structure and element requirements.
Use Set object for simple value deduplication. Implement custom comparison for objects. Consider memory usage with large arrays. Handle reference equality vs value equality appropriately. Implement efficient algorithms for complex objects. Document deduplication criteria and requirements.
WeakMap and WeakSet hold weak references to objects, allowing garbage collection of keys. Used for private data storage, caching, and memory-sensitive operations. Consider garbage collection implications. Handle key object lifecycle properly. Implement proper cleanup strategies. Document memory management requirements.
Use Array.flat() or reduce() for nested array flattening. Consider depth of nesting and performance implications. Handle circular references appropriately. Implement custom flattening for complex structures. Document flattening depth requirements. Handle special cases and error conditions.
Check array bounds before access. Handle undefined and null values appropriately. Implement type checking for array operations. Consider error recovery strategies. Document error conditions and handling. Implement proper validation for array modifications.
Array-like objects have length property and indexed elements but lack array methods. Convert to arrays using Array.from() or spread operator. Consider performance implications of conversion. Handle proper method delegation. Document array-like object requirements. Implement proper type checking.
Consider holes in array iteration. Use appropriate methods for sparse array operations. Handle undefined values properly. Implement proper array compaction when needed. Document sparse array handling requirements. Consider performance implications.
Choose appropriate iteration method (for...of, forEach, map). Consider performance requirements and use case. Handle early termination properly. Implement proper error handling during traversal. Document traversal requirements. Monitor traversal performance.
Use spread operator or slice() for shallow copy. Implement deep cloning for nested structures. Handle circular references appropriately. Consider performance implications of deep cloning. Document cloning requirements. Implement proper validation.
