Coding Interview Pattern Guides

Maintain a contiguous range without recomputing from scratch. Learn when to expand, shrink, and avoid sum-based windows with negative values.

• Fixed and variable windows
• Window state and invariants
• Expand and shrink templates

Replace repeated scans with boundaries that move for a reason. Compare opposite-end, same-direction, fast-slow, and read-write pointer models.

• Pointer placement
• Movement invariants
• Sorted and in-place problems

Precompute cumulative state to turn range totals and subarray relationships into direct lookups with prefix sums, hash maps, and difference arrays.

• Range queries
• Prefix sum plus hash map
• Difference arrays

Search sorted data and monotonic decision spaces with explicit boundaries. Learn exact search, first and last true, and rotated-array variations.

• Boundary definitions
• First and last occurrence
• Rotated arrays

Trade repeated lookups for stored information. Learn frequency maps, complements, grouping, visited state, and when a set is enough.

• Frequency counting
• One-pass lookups
• Sets versus maps

Explore one branch before returning. Compare recursive and iterative traversal, tree return values, visited state, components, and cycle handling.

• Trees and graphs
• Visited state
• Recursive return values

Process a graph frontier in distance layers. Learn queue mechanics, seen-on-enqueue, shortest paths, multi-source search, and state-space modeling.

• Distance layers
• Shortest unweighted paths
• Multi-source BFS

Keep unresolved work in last-in, first-out order. Apply stacks to nesting, monotonic scans, expressions, and simulations.

• Matching and nesting
• Monotonic stacks
• Expression evaluation

Change references without losing the structure. Learn reversal, dummy nodes, fast-slow pointers, cycle detection, and merging.

• Reference-safe reversal
• Dummy nodes
• Fast and slow pointers

Maintain the next best candidate as data changes. Learn min and max heaps, bounded top-k structures, k-way merge, and streams.

• Min heap versus max heap
• Top-k problems
• K-way merge

Commit to a local choice only when it preserves the best global result. Learn recognition, correctness arguments, and failure cases.

• Greedy-choice property
• Correctness arguments
• Counterexamples

Sort ranges so overlap decisions become local. Learn merging, insertion, scheduling, room counts, and endpoint ties.

• Merge and insert
• Scheduling
• Endpoint sweeps

Explore a decision tree while restoring shared state between choices. Learn subsets, permutations, combinations, pruning, and constraint search.

• Choose, recurse, undo
• Choice boundaries
• Pruning

Store strings by shared prefixes. Learn trie nodes, insertion, exact and prefix search, autocomplete, and trie-backed board search.

• Prefix-tree structure
• Insert and search
• Trie plus DFS

Track changing connectivity without retraversing the graph. Learn parent links, path compression, union by size, and cycle detection.

• Find and union
• Path compression
• Dynamic connectivity

Define what one state answers, derive its recurrence, and evaluate dependencies in order. Learn memoization, tabulation, and major DP families.

• State and recurrence
• Memoization and tabulation
• DP families