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Curated collection of core computer science concepts and algorithmic problem-solving techniques implemented in Java, Golang, Kotlin, Python. It is designed for learners and professionals aiming to strengthen their understanding of the JVM, OOP, concurrency, and practical coding interview problems.

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Core Concepts and Problem Solving

A practical study repository for data structures and algorithms, coding interviews, language fundamentals, software quality, system design, and cloud engineering. The main interview-preparation track contains complete Go and Java solutions for the shared LeetCode Top Practice Problems list.

LeetCode Top Practice Problems

The Go and Java problem collection contains 333 problems, organized as one independently compilable directory per problem.

Difficulty Problems
Easy 85
Medium 204
Hard 44
Total 333

Each problem directory follows the same interview-focused structure:

0001-two-sum/
|-- README.md     # Problem statement, examples, and constraints
|-- solution.md   # Brute force through optimized interview approach
|-- solution.go   # Go implementation
|-- Solution.java # Java implementation
|-- types.go      # Local Go judge types or callbacks when required
`-- Types.java    # Local Java judge types or callbacks when required

Use the complete problem index to browse by list order, difficulty, or algorithmic approach.

Interview Study Workflow

  1. Read the problem statement and clarify inputs, outputs, constraints, and edge cases.
  2. Explain a direct or brute-force solution before optimizing it.
  3. Identify the reusable pattern and state the invariant that makes the optimized approach correct.
  4. Implement the solution in Go or Java without referring to the checked-in implementation.
  5. Compare implementations, analyze time and space complexity, and test boundary cases aloud.

The solution guides are written for FAANG-style interview discussion: pattern recognition, baseline reasoning, optimization, correctness, complexity, edge cases, and language-specific implementation notes.

Repository Map

Path Contents
leetcode-top-practice-problems/ 333 documented LeetCode solutions in Go and Java
cs-core-concepts/java-and-oop/ Java, OOP, SOLID, and design-pattern notes
cs-core-concepts/golang-learning/ Go fundamentals, libraries, SOLID, and design patterns
cs-core-concepts/java-vs-go-learning-path/ Java-to-Go comparison and migration-focused learning path
cs-core-concepts/sqa/ Software quality assurance and testing concepts
cs-core-concepts/github-best-practices/ GitHub workflows and collaboration practices
cs-core-concepts/project-managment-best-practices/ Agile and project-management notes
cloud-and-devops/ Cloud and DevOps concepts
system-design-concepts/ System-design notes, patterns, and white papers
src/leetcode/ Earlier Java problem-solving implementations
src/others/ Additional exercises and experiments

Verify the Problem Collection

Go 1.22 or newer and JDK 17 or newer are required.

cd leetcode-top-practice-problems
go test ./...
go vet ./...
go run ./tools/verify-java

The repository test validates the problem manifest and required files. The Go command compiles every Go package, and the Java verifier compiles every Java solution in isolation with its local judge types.

Documentation Tooling

Problem metadata and documentation indexes are maintained by tools/general-docs. Run the generator from the Go module directory:

cd leetcode-top-practice-problems
go run ./tools/general-docs

Some problem descriptions are derived from attributed third-party material. See the collection's notice and third-party license for details.

About

Curated collection of core computer science concepts and algorithmic problem-solving techniques implemented in Java, Golang, Kotlin, Python. It is designed for learners and professionals aiming to strengthen their understanding of the JVM, OOP, concurrency, and practical coding interview problems.

Topics

Resources

Stars

3 stars

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1 watching

Forks

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