Variable Size (Condition-Based) — Sliding Window
The Variable Size (Condition-Based) pattern applies when you need the Variable Size (Condition-Based) technique within the Sliding Window pattern. Its time complexity is O(n) and space complexity O(1). It is used in 20 problems on Thita, including Contains Duplicate II, Continuous Subarrays and Find Longest Special Substring That Occurs Thrice I. Common variations are Character Frequency Matching and Fixed Size (Subarray Calculation).
Master variable-size sliding window for condition-based problems like longest substring without repeating characters.
Variable Size (Condition-Based) is one of the 4 subpatterns of the Sliding Window pattern, which covers fixed-size, variable-size, and character frequency matching window techniques. The whole pattern is about 2.5 hours of study. This subpattern is a core technique: expect it to come up directly in interviews.
What Variable Size (Condition-Based) covers
Master the sliding window technique for subarray and substring problems. Learn fixed size windows, variable size windows, and monotonic queue optimizations. Problems in this subpattern are usually searched for as variable window, longest substring, minimum window, condition based window, leetcode 3, leetcode 76.
How to practise Variable Size (Condition-Based) on Thita.ai
Read the theory for Variable Size (Condition-Based), then work the problems attached to it in the browser editor. Your solution runs against the problem's test cases, and the AI coach offers a hint about the technique you are missing rather than a finished solution. Progress is tracked per subpattern, so the Sliding Window tracker shows this one as covered once you have solved its problems.
Other subpatterns in Sliding Window
- Fixed Size (Subarray Calculation) — Learn fixed-size sliding window for subarray calculations like maximum average, moving average, and k-size subarray problems.
- Character Frequency Matching — Learn sliding window with character frequency matching for anagram and permutation substring problems.
- Monotonic Queue for Max/Min — Master monotonic queue (deque) to find maximum or minimum in sliding windows efficiently in O(n) time.
Related DSA patterns
- Two Pointers — Fast-slow, converging, expanding from center, and in-place modification techniques.
- Binary Search Patterns — Standard binary search, rotated arrays, first/last occurrence, and search on answer space.
- Array/Matrix Manipulation Patterns — In-place operations, hashing, prefix sums, spiral traversal, and cyclic sort.
- Linked List Manipulation Patterns — In-place reversal, merging sorted lists, reordering, and intersection detection.
Where to go next
Variable Size (Condition-Based) is one lesson in a 16-pattern DSA course. If you are preparing end to end, work the interview-critical patterns first and use the pattern sheet as the checklist; if you are here for one technique, the Sliding Window guide is the shortest path back to the rest of it.