Hashing-and-Dictionary-Patterns

What the guide covers

Hashing and Dictionary Patterns is a concise, practical guide to interview patterns, hashing problem solutions, and error handling for Google and Microsoft interviews, maintained by mwakidenis. The README states the focus plainly and repeats it, which suggests the author wants the scope to be unambiguous: it is a study aid, not a framework or a library. The listed features are HashMap and Dictionary concepts in both C++ and Python, error handling best practices, and common interview patterns such as Two Sum, Anagrams, Frequency Counting, Sliding Window, and Mapping. The guide also promises visual diagrams and step-by-step explanations, plus company-specific expectations and follow-up questions. The structure section says the repository holds a docs directory for main documentation and a docs and problems directory for practice problems. For a candidate preparing for a coding interview, the combination of pattern names and side-by-side language comparisons is the main draw, because the same idea often looks different in C++ and Python and interviewers may expect either. The maintainer field points to the single GitHub account mwakidenis, so this is a personal project rather than a large team effort, which fits its compact and opinionated scope. The README repeats the project description twice at the top, which suggests the author wanted the scope, interview preparation for Google and Microsoft, to be impossible to miss.

How the material is organized

The README outlines a project outline that shows how the content is meant to be consumed. The documentation portion covers conceptual explanations for HashMaps and Dictionaries, C++ versus Python comparisons, and specific patterns such as Two Sum, Anagrams, and value mapping. It also mentions flowcharts for algorithm steps, comparison tables for complexity and language features, and diagrams for memory models and access patterns, which tells the reader that the guide leans on visuals rather than only prose. A code examples section promises simple, clear C++ and Python code for each topic with side-by-side syntax and structure comparisons, so a learner can see the same algorithm expressed in both languages at once. The repository organization places problem-specific guides under docs and problems. The README even includes a short clone command for a repository named Interview-Patterns-for-Google-Microsoft, which is a slight mismatch with the current repository name but points to the same body of work. Contact is routed to the maintainer's GitHub account for questions or suggestions. The overall shape is a teaching repository where each pattern is explained, diagrammed, and then implemented in two languages, which is a sensible order for interview study. The repository also places problem specific guides under a docs and problems directory, so a learner can move from the pattern explanation straight to a worked example.

Who the guide is for

The guide is aimed at people preparing for technical interviews at large software employers, and the README names Google and Microsoft specifically because those companies use pattern-heavy coding rounds where hashing and dictionary tricks appear often. The listed patterns, Two Sum, Anagrams, Frequency Counting, Sliding Window, and Mapping, are exactly the kinds of problems that reward knowing when a hash map turns an O(n squared) scan into an O(n) pass. By pairing each pattern with error handling best practices, the guide also addresses the part of an interview where candidates lose points: off-by-one loops, missing null checks, and unclear edge case handling. The company-specific expectations and follow-up questions feature suggests the author wants readers to practice not only the first solution but the extensions an interviewer typically asks for once the base case works. Because the examples are given in both C++ and Python, the guide serves readers who will interview in either language, and the visual diagrams help those who reason from pictures before code. For a solo learner, the compact size is an advantage: it is possible to work through the whole guide in a focused weekend rather than getting lost in a larger course. The listed patterns, Two Sum, Anagrams, Frequency Counting, Sliding Window, and Mapping, are the kinds of problems where a hash map turns a slow scan into a single pass, which is the core lesson the guide repeats across examples.

Editorial conclusion

Hashing and Dictionary Patterns is released under the MIT license, has no primary language recorded in its metadata, and was last updated on GitHub on 2026-08-24 with 54 stars recorded.