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This article explains the Knuth-Morris-Pratt (KMP) string‑matching algorithm, describes how the next array is built to capture prefix‑suffix information, shows Java implementations of the search and next‑array construction, and discusses common optimizations to reduce redundant comparisons.
This article introduces Kotlin Multiplatform (KMP), explains its core concepts and advantages, walks through a simple demo project with code snippets and build configurations, and discusses the underlying compilation process, Compose UI sharing, ecosystem libraries, and real‑world industry adoption.
This article introduces common graph concepts and several advanced string‑matching algorithms—including Brute‑Force, Rabin‑Karp, KMP, Boyer‑Moore, AC automaton, Trie, and Double‑Array Trie—explaining their principles, implementations, complexity analyses, and typical application scenarios for search systems.
This article explains the Brute‑Force (BF), Boyer‑Moore (BM), and Knuth‑Morris‑Pratt (KMP) string‑matching algorithms, illustrates their operation with step‑by‑step visual examples, discusses the inefficiencies of BF, the shift rules of BM, and the prefix‑suffix logic of KMP, and provides a complete Java implementation including the construction of the next array.
This article explains the KMP string‑matching algorithm, how it builds the prefix (next) table to avoid the O(M·N) worst‑case of naive search, provides JavaScript implementations, compares it with Boyer‑Moore and V8's indexOf strategy, and includes detailed code examples.
This article introduces several classic string‑matching algorithms—including Brute‑Force, KMP, Boyer‑Moore, BMH, Sunday, Shift‑And/Or, and bitmap techniques—explaining their principles, preprocessing steps, and practical considerations for improving text search performance.