Common Hashing Patterns
Explore how to recognize and implement two key hashing patterns in C++ coding interviews: frequency counting for element occurrences and prefix sum with hashing for subarray sum problems. Understand how to use std::unordered_map to optimize lookups and avoid common pitfalls, improving your problem-solving efficiency in interview scenarios.
Recognizing a hash table as the right data structure is only the first step. The next is knowing which pattern to apply. This lesson covers the two most important hashing patterns in coding interviews: frequency counting and prefix sum with hashing. In C++, these are usually implemented with std::unordered_map. Together, they cover the majority of hash table-based interview problems.
Interview lens: Both patterns share a common signal: repeated lookup or counting over a sequence. Any problem that requires us to know how many times something appeared, or whether a subarray with a given sum exists, is almost certainly one of these two patterns. Spotting that signal early and reaching for an std::unordered_map is the reflex this lesson builds.
Frequency counting
The frequency counting pattern uses a hash table to count how many times each element appears in a collection during a single pass. In C++, we usually map each unique element to its count with std::unordered_map<T, int>, incrementing the count each time we encounter the element. Once the pass is complete, the hash table gives us
This pattern eliminates the need for nested loops. Without a hash table, counting occurrences of every element requires an