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Comprehensive solutions to 9 classic searching algorithm problems with detailed explanations, Go implementations, and complexity analysis. From easy to hard difficulty levels for technical interview preparation.
Leetcode
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- system-design (116)
- database (30)
- low-level-design (22)
- oop (15)
- databases (15)
- normalization (10)
- misc (10)
- load-balacing (9)
- indexes (8)
- interview-prep (7)
- erd (7)
- golang (7)
- caching (7)
- networking (7)
- uml (6)
- solid (6)
- messaging (6)
- security (6)
- theorem (6)
- oop-pillars (5)
- data-partitioning (5)
- data-structures (4)
- scalability (4)
- data-modeling (4)
- functional-dependency (4)
- bloom-filters (4)
- cdn (4)
- dbms (3)
- relational-data-model (3)
- api-gateway (3)
- recovery (3)
- distributed-file-system (3)
- dns (3)
- proxy (3)
- replication (3)
- trade-offs (2)
- relational-model (2)
- searching-algorithms (2)
- programming (2)
- oop-principle (2)
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- redundancy (2)
- key-concepts (1)
- tips (1)
- armstrong-axioms (1)
- integrity-constraints (1)
- er-diagram (1)
- algorithms (1)
leetcode (1)
- binary-search (1)
- problem-solving (1)
- strings (1)
- oop-relationship (1)
- concurrency (1)
- high-availability (1)
- availability (1)
- observability (1)
- monitoring (1)
- error-handling (1)
- leader-follower (1)
- architectural-pattern (1)
- load-balacing-algorithms (1)
- load-balacing-uses (1)
- batch-processing (1)
- streams (1)
- heart-beat (1)
- synchronous (1)
- asynchronous (1)
- quorum (1)
- go-command (1)
- hello-world (1)
- history (1)
- setup (1)