A collection of Go solutions for problems from the Elements of Programming Interviews book.
epi is a GitHub repository containing Go language solutions to problems from the *Elements of Programming Interviews* book. It provides implemented code for a vast array of algorithmic challenges, serving as a study resource for software engineers preparing for technical interviews. The project translates complex problem statements into working Go code, covering fundamental to advanced computer science topics.
Software engineers and computer science students preparing for coding interviews, particularly those interested in or required to use the Go programming language. It's also useful for developers seeking to improve their algorithmic problem-solving skills with practical, tested examples.
Developers choose epi for its focused collection of interview problems implemented in modern, idiomatic Go. It offers a direct bridge between textbook algorithms and production-ready code, with the added benefit of accompanying tests to verify understanding and correctness.
Solutions for Elements of Programming Interviews problems written in Golang (work-in-progress)
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Covers diverse topics from primitive types to graphs, mirroring the EPI book's structure, with solutions for key problems like parity checks and binary tree traversals.
Implementations use Go's standard libraries and concurrency patterns, such as in recursion and heap problems, offering practical examples for Go developers.
Each solved problem includes unit tests (e.g., for Dutch flag or merge sorted lists), ensuring correctness and serving as a learning tool for testing in Go.
Code is logically grouped by domains like arrays and trees, making it easy to navigate and reference specific problem types, as shown in the README's table format.
Many problems are marked as 'in progress' or unsolved (e.g., in dynamic programming and parallel computing), limiting its usefulness as a comprehensive reference.
Focuses solely on code without algorithmic explanations or complexity analysis, which might hinder understanding for learners who need conceptual guidance.
As a work-in-progress personal project, updates may be infrequent, and code quality or consistency could vary across different sections.