The NeetCode 150 in C#

Working through the NeetCode 150 in C# is not just a matter of translating an algorithm into another language. C# has collection APIs, integer behaviour and string operations that can make a solution concise and safe—or introduce avoidable bugs during a coding interview. This guide focuses on the NeetCode 150 list, practised on thita: how to organise your preparation and which C# idioms to know before you start.

The NeetCode 150 contains 150 problems: 28 Easy, 101 Medium and 21 Hard. Every problem on the list that is live on thita runs in the browser in C# against the problem’s test cases, and the NeetCode 150 by pattern shows which ones are live. Use the NeetCode 150 sheet as your list, then use the examples below to make your implementation style deliberate.

Thita is not affiliated with NeetCode.

How should you work through the NeetCode 150 in C#?

Start by recognising the underlying pattern rather than memorising a finished implementation. Thita groups its problems into 99 DSA patterns in 16 families, while the NeetCode 150 sheet retains NeetCode’s topic as a tag. You can also use the DSA patterns sheet to move between list-based preparation and pattern-based revision.

A practical workflow is:

• Read the question and state the input assumptions aloud.
• Describe a straightforward approach before improving its time complexity.
• Select the C# data structure that expresses the invariant clearly.
• Implement without hiding the main loop behind unnecessary abstractions.
• Run the code against the problem’s test cases in the browser.
• Review failures, complexity and language-specific choices.
• Return later and explain the solution without looking at your notes.

Do not treat a passing submission as the end of practice. In an interview, you also need to explain why a HashSet is sufficient, why a heap has the ordering it has, or why a long is required even when the input array contains int values.

The list is broad. Trees has 15 problems, Linked List has 11, 1-D Dynamic Programming has 12, and Graphs has 13. Those topics reward repeated pattern recognition. Arrays & Hashing has 9 problems, so it is a useful place to establish the C# collection habits that recur elsewhere.

Which C# standard-library pieces should you know cold?

Dictionary<TKey, TValue> is the default tool for a key-to-value relationship. Prefer TryGetValue when you need to distinguish “the key is absent” from “the stored value is the default value”. GetValueOrDefault is useful when absence naturally maps to a sentinel or zero, but make that choice explicit.

HashSet<T> expresses membership and deduplication. Its Add method returns false when the value was already present, which is often cleaner than checking with Contains and then adding.

Stack<T> and Queue<T> are the direct standard-library representations of last-in-first-out and first-in-first-out behaviour. Use Push, Pop and Peek for a stack; use Enqueue, Dequeue and Peek for a queue. Do not use List<T>.RemoveAt(0) as a queue operation: shifting elements changes the intended complexity.

Valid Anagram — practise it on thita

This solution counts characters in one string, then consumes those counts while scanning the other string.

CSHARP
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using System.Collections.Generic;

public class Solution
{
    public bool IsAnagram(string s, string t)
    {
        if (s.Length != t.Length)
        {
            return false;
        }

        var counts = new Dictionary<char, int>();
        foreach (char c in s)
        {
            counts[c] = counts.GetValueOrDefault(c, 0) + 1;
        }

        foreach (char c in t)
        {
            if (!counts.TryGetValue(c, out int remaining) || remaining == 0)
            {
                return false;
            }

            if (remaining == 1)
            {
                counts.Remove(c);
            }
            else
            {
                counts[c] = remaining - 1;
            }
        }

        return true;
    }
}

The GetValueOrDefault call makes a missing frequency start at zero. TryGetValue then distinguishes a missing character from a character whose remaining count has reached zero. Empty strings return true, and repeated characters are handled by the counts.

Complexity: The solution runs in O(n + m) time for string lengths n and m, with O(k) auxiliary space for the distinct characters.

Longest Substring Without Repeating Characters — practise it on thita

This sliding window keeps only characters that occur in the current window, using a HashSet rather than a LINQ pipeline in the hot loop.

CSHARP
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using System.Collections.Generic;

public class Solution
{
    public int LengthOfLongestSubstring(string s)
    {
        var window = new HashSet<char>();
        int left = 0;
        int best = 0;

        for (int right = 0; right < s.Length; right++)
        {
            while (!window.Add(s[right]))
            {
                window.Remove(s[left]);
                left++;
            }

            int length = right - left + 1;
            if (length > best)
            {
                best = length;
            }
        }

        return best;
    }
}

HashSet<T>.Add both tests membership and inserts a new character. When it returns false, the loop removes characters from the left until the invariant is restored. This also handles an empty input without a special result calculation.

Complexity: The algorithm runs in O(n) time and O(n) space.

Which C# string and stack habits matter in interviews?

C# strings are immutable. Repeated concatenation inside a loop creates new string values, so use StringBuilder when constructing a result incrementally. For parsing, indexing and comparison, ordinary string operations are fine; the important distinction is whether you are repeatedly changing the value.

For bracket matching, Stack<char> mirrors the algorithm directly. Use a dictionary for closing-to-opening bracket lookup, and reject a closing bracket when the stack is empty. Avoid LINQ in hot loops: methods such as Where, Select and ToList can obscure allocation and iteration costs when a simple loop is clearer.

Valid Parentheses — practise it on thita

This method checks whether each closing bracket matches the most recent unmatched opening bracket.

CSHARP
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using System.Collections.Generic;

public class Solution
{
    public bool IsValid(string s)
    {
        var openings = new Dictionary<char, char>
        {
            [')'] = '(',
            [']'] = '[',
            ['}'] = '{'
        };
        var stack = new Stack<char>();

        foreach (char c in s)
        {
            if (!openings.TryGetValue(c, out char opening))
            {
                stack.Push(c);
                continue;
            }

            if (stack.Count == 0 || stack.Pop() != opening)
            {
                return false;
            }
        }

        return stack.Count == 0;
    }
}

The stack invariant is simple: its top item must be the opening bracket matched by the next closing bracket. Checking Count before Pop prevents an empty-stack failure, while a final count check catches unmatched opening brackets.

Complexity: The algorithm runs in O(n) time and O(n) space.

The same discipline applies to string serialisation. A length-prefixed format avoids ambiguity when an input string contains a separator. StringBuilder handles construction, while a cursor avoids repeatedly slicing the input during traversal.

Encode and Decode Strings — practise it on thita

The encoder writes each string’s length before its contents, and the decoder uses that length to locate the next value.

CSHARP
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using System;
using System.Collections.Generic;
using System.Text;

public class Solution
{
    public string Encode(IList<string> strs)
    {
        var builder = new StringBuilder();
        foreach (string value in strs)
        {
            builder.Append(value.Length).Append(':').Append(value);
        }

        return builder.ToString();
    }

    public List<string> Decode(string encoded)
    {
        var result = new List<string>();
        int index = 0;

        while (index < encoded.Length)
        {
            int separator = encoded.IndexOf(':', index);
            int length = int.Parse(encoded.Substring(index, separator - index));
            int start = separator + 1;
            result.Add(encoded.Substring(start, length));
            index = start + length;
        }

        return result;
    }
}

An empty collection encodes to an empty string, and an empty member encodes with a zero length before the separator. The cursor advances by the declared length, so separators inside a value do not confuse the decoder. The input passed to Decode is expected to use the format produced by Encode.

Complexity: Encoding uses O(total input length) time and output space. Decoding uses O(total encoded length) time and O(total decoded length) space.

When should you use a queue or a priority queue in C#?

A breadth-first traversal needs a FIFO queue. In C#, Queue<TreeNode> communicates the operation and supplies the expected interface. Track the current queue size before removing a level when the result needs level boundaries.

Binary Tree Level Order Traversal — practise it on thita

This traversal records each tree depth as a separate list while processing nodes in FIFO order.

CSHARP
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using System.Collections.Generic;

public class Solution
{
    public IList<IList<int>> LevelOrder(TreeNode? root)
    {
        var levels = new List<IList<int>>();
        if (root is null)
        {
            return levels;
        }

        var queue = new Queue<TreeNode>();
        queue.Enqueue(root);

        while (queue.Count > 0)
        {
            int width = queue.Count;
            var level = new List<int>(width);

            for (int i = 0; i < width; i++)
            {
                TreeNode node = queue.Dequeue();
                level.Add(node.val);
                if (node.left is not null)
                {
                    queue.Enqueue(node.left);
                }

                if (node.right is not null)
                {
                    queue.Enqueue(node.right);
                }
            }

            levels.Add(level);
        }

        return levels;
    }

    public class TreeNode
    {
        public int val;
        public TreeNode? left;
        public TreeNode? right;

        public TreeNode(int value = 0, TreeNode? leftChild = null, TreeNode? rightChild = null)
        {
            val = value;
            left = leftChild;
            right = rightChild;
        }
    }
}

The null-root check handles an empty tree. The helper TreeNode is included so the block compiles independently under .NET 8, while nullable annotations make absent children explicit.

Complexity: The traversal runs in O(n) time and O(n) space.

For heap problems, know PriorityQueue<TElement, TPriority> from .NET 6 onward. It is a min-heap: the element with the smallest priority is removed first. It has no decrease-key operation. If a shortest-path implementation discovers a better distance, enqueue a new entry and ignore stale entries when they are removed; do not expect to update an existing heap node in place.

K Closest Points to Origin — practise it on thita

This method keeps a bounded max-by-distance collection by giving a min-heap negative distance priorities.

CSHARP
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using System;
using System.Collections.Generic;

public class Solution
{
    public int[][] KClosest(int[][] points, int k)
    {
        int take = Math.Min(Math.Max(k, 0), points.Length);
        if (take == 0)
        {
            return Array.Empty<int[]>();
        }

        var heap = new PriorityQueue<int[], long>();
        foreach (int[] point in points)
        {
            long x = point[0];
            long y = point[1];
            long distance = checked(x * x + y * y);
            heap.Enqueue(point, -distance);

            if (heap.Count > take)
            {
                heap.Dequeue();
            }
        }

        var answer = new int[take][];
        for (int i = 0; i < take; i++)
        {
            answer[i] = heap.Dequeue();
        }

        return answer;
    }
}

Because PriorityQueue removes the smallest priority, negative distances cause the farthest retained point to be removed when the bounded heap grows. Widening the coordinates before multiplication prevents int squaring, and checked makes an arithmetic assumption visible instead of silently wrapping. Equal distances and duplicate points remain valid heap entries.

Complexity: The implementation runs in O(n log k) time and O(k) auxiliary space, apart from the returned array.

How do tuples, sorting and overflow affect NeetCode 150 solutions in C#?

Value tuples are useful for carrying related temporary state without defining a small class. Named fields such as Start and End make an interval invariant easier to read. They are value types, so use them for compact local data rather than assuming they behave like reference objects.

Array.Sort accepts a Comparison<T>, which is useful when the input is an array and the ordering is local to the solution. Be careful with subtraction comparers such as (a, b) => a[0] - b[0]: subtraction can overflow. Prefer CompareTo.

Overflow is a correctness issue, not merely an edge case. int arithmetic can overflow before assignment to a long, so widen operands first. Use checked when an overflow should be detected rather than silently wrapped. For a problem whose required return type is int[], cast back only after confirming that the problem’s constraints make the result representable.

Product of Array Except Self — practise it on thita

This solution stores products from the left in the output, then multiplies them by products accumulated from the right.

CSHARP
Copy
using System;

public class Solution
{
    public int[] ProductExceptSelf(int[] nums)
    {
        var result = new int[nums.Length];
        long prefix = 1;

        for (int i = 0; i < nums.Length; i++)
        {
            result[i] = checked((int)prefix);
            prefix = checked(prefix * (long)nums[i]);
        }

        long suffix = 1;
        for (int i = nums.Length - 1; i >= 0; i--)
        {
            result[i] = checked((int)(result[i] * suffix));
            suffix = checked(suffix * (long)nums[i]);
        }

        return result;
    }
}

The empty array returns an empty result. The explicit widening and checked blocks make the numeric assumptions visible: multiplication takes place in long, while conversion back to the required int[] result is checked rather than silently truncated.

Complexity: The algorithm runs in O(n) time and uses O(1) auxiliary space, excluding the returned array.

Merge Intervals — practise it on thita

This method sorts intervals by their start values and keeps the active interval in a named value tuple.

CSHARP
Copy
using System;

public class Solution
{
    public int[][] Merge(int[][] intervals)
    {
        if (intervals.Length == 0)
        {
            return Array.Empty<int[]>();
        }

        Array.Sort(intervals, (left, right) => left[0].CompareTo(right[0]));
        var merged = new int[intervals.Length][];
        int count = 0;
        var current = (Start: intervals[0][0], End: intervals[0][1]);

        for (int i = 1; i < intervals.Length; i++)
        {
            if (intervals[i][0] <= current.End)
            {
                current.End = Math.Max(current.End, intervals[i][1]);
            }
            else
            {
                merged[count++] = new[] { current.Start, current.End };
                current = (intervals[i][0], intervals[i][1]);
            }
        }

        merged[count++] = new[] { current.Start, current.End };
        Array.Resize(ref merged, count);
        return merged;
    }
}

The empty-input guard prevents access to the first interval when there is no input. Overlapping intervals, including intervals with equal starts, are combined by extending current.End. CompareTo avoids the overflow risk of subtraction-based comparisons.

Complexity: Sorting makes the solution O(n log n) time; the merge pass is O(n), and the output requires O(n) space.

Which NeetCode topics are easier or harder in C#?

Arrays & Hashing, Two Pointers, Sliding Window and many Greedy problems are usually comfortable in C# once Dictionary, HashSet, arrays and loops are familiar. The language gives you strong array indexing, clear generic collections and useful sorting overloads. These topics also benefit from avoiding LINQ in the critical loop, because the invariant remains visible to the interviewer.

Stack and queue problems are similarly direct with Stack<T> and Queue<T>. Basic tree traversal is readable, although nullable reference annotations mean you should be intentional about whether a child can be absent. Linked-list questions are algorithmically simple but can be more error-prone because C# references and nullable nodes make pointer updates easy to misread.

Heap and Priority Queue questions are harder to express correctly if you assume the API works like a decrease-key heap or a max-heap. State clearly that PriorityQueue is a min-heap, choose priorities deliberately, and use stale-entry checks where the algorithm needs them. Graphs and advanced graphs combine that issue with adjacency-list construction, visited-state representation and numeric distances.

Dynamic programming is not uniquely difficult in C#, but array initialisation, sentinel values and integer overflow deserve attention. Backtracking can be clear with List<T>, yet remember that a mutable list is shared across recursive calls: add, recurse, then remove. Tries and custom design problems require more classes and comparer decisions, so keeping helper types small and explicit helps in an interview.

What C# bugs should you check before submitting?

• Integer division: a / b is integer division when both operands are integers. Convert deliberately when a fractional result is required.
• Overflow before widening: write (long)a * b, not (long)(a * b). Consider checked when wrapping would hide a defect.
• Priority direction: PriorityQueue removes the smallest priority. Negate a numeric priority for max-heap behaviour, or store a reversed comparer where appropriate.
• No decrease-key: enqueue improved states and discard stale states when dequeued.
• Queue misuse: List.RemoveAt(0) shifts elements. Use Queue<T>.
• String concatenation: repeated result += piece creates new immutable strings. Use StringBuilder for incremental construction.
• Comparer subtraction: x - y can overflow. Use CompareTo.
• Reference aliasing: assigning one List<T> or array variable to another does not copy its contents.
• Recursive depth: a highly skewed tree can make recursive traversal deep. Discuss an iterative alternative if the constraints make depth a concern.
• LINQ in hot loops: concise does not always mean allocation-free or easy to analyse. A for or foreach loop is often the better interview choice.

How can you practise the NeetCode 150 in C# on thita?

Open the NeetCode 150 by pattern, choose a problem available on thita, and write the C# solution in the browser. Run it against the problem’s test cases, then inspect any failure rather than immediately replacing the implementation. Record the pattern, the invariant, the complexity and the C# API decision that mattered.

After a group of related problems, rehearse the explanation aloud. Use the AI mock interview to practise a spoken round that asks follow-ups and runs your code. Explain why your data structure is sufficient, what happens on empty input, and where overflow or duplicate values could affect the result.

The goal is not to make every solution look identical. It is to make your C# choices predictable: hash for lookup, sets for membership, stacks and queues for traversal order, a min-heap for priority work, tuples for local state, StringBuilder for construction, and explicit numeric types when the bounds demand them. That is how the NeetCode 150 list, practised on thita, becomes preparation for a C# coding interview rather than a collection of copied answers.