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* Retranslate the complete English edition from Simplified Chinese * Polish three English explanations after reader-focused review
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1.2 KiB
Summary
Key takeaways
- Binary search relies on sorted data and repeatedly halves the search interval. It requires ordered input and applies only to arrays or data structures based on arrays.
- Brute-force search locates data by traversing a data structure. Linear search suits arrays and linked lists; breadth-first and depth-first search suit graphs and trees. These algorithms are broadly applicable and require no preprocessing, but their
O(n)time complexity is relatively high. - Hash lookup, tree search, and binary search efficiently locate targets in particular data structures. Their time complexities can be
O(\log n)or evenO(1), but they usually rely on additional data structures. - In practice, choose a search method by considering dataset size, required search performance, query frequency, update frequency, and related factors.
- Linear search suits small or frequently updated datasets; binary search suits large, sorted datasets; hash lookup suits fast queries without range-query requirements; tree search suits large, dynamic datasets that need ordering and range queries.
- Replacing linear search with hash lookup is a common optimization that reduces lookup time from
O(n)toO(1).