Is Maximum Transactions Without Negative Balance easy or hard?

The problem is typically classified as Medium difficulty. The main challenge is recognizing the greedy insight: when the balance becomes negative, removing the worst negative transaction maximizes how many total transactions remain feasible.

Maximum Transactions Without Negative Balance Python/Java solution

Most implementations use a max‑heap (or simulate one using a min‑heap with negated values). The algorithm iterates through the array, updates the balance, pushes negative transactions into the heap, and removes the largest loss whenever the balance drops below zero. The same logic works in Python, Java, C++, and Go using their standard priority queue libraries.

How to solve Maximum Transactions Without Negative Balance in O(n log n)?

Traverse the transactions while maintaining a running balance. Push every negative transaction into a max‑heap. If the balance becomes negative, remove the largest negative value from the heap and add it back to the balance. This greedy removal keeps the balance valid while maximizing the total number of accepted transactions.

What is the best approach for Maximum Transactions Without Negative Balance?

The best approach uses a greedy strategy with a heap (priority queue). Iterate through transactions while maintaining a running balance and store negative transactions in a max structure. If the balance becomes negative, remove the transaction with the largest loss. This ensures the maximum number of transactions while keeping the balance non‑negative, with O(n log n) time complexity.

Is Maximum Transactions Without Negative Balance asked at Google/Amazon/Meta?

Problems using greedy selection with heaps and prefix balance constraints frequently appear in interviews at companies like Amazon, Google, and Meta. Variations of this pattern show up in scheduling, resource allocation, and prefix‑sum constraint problems.

What data structure is used in Maximum Transactions Without Negative Balance?

The key data structure is a heap (priority queue) or an ordered set. It stores negative transactions so the algorithm can quickly remove the one with the largest negative impact when the running balance becomes invalid.

What is the time complexity of Maximum Transactions Without Negative Balance?

The optimal solution runs in O(n log n) time. Each transaction is processed once, and negative transactions may be inserted or removed from a heap, which costs O(log n) per operation. Space complexity is O(n) to store the selected negative transactions.

3711. Maximum Transactions Without Negative Balance - Practice Online

You are given an integer array transactions, where transactions[i] represents the amount of the i^th transaction:

A positive value means money is received.
A negative value means money is sent.

The account starts with a balance of 0, and the balance must never become negative. Transactions must be considered in the given order, but you are allowed to skip some transactions.

Return an integer denoting the maximum number of transactions that can be performed without the balance ever going negative.

Example 1:

Input: transactions = [2,-5,3,-1,-2]

Output: 4

Explanation:

One optimal sequence is [2, 3, -1, -2], balance: 0 → 2 → 5 → 4 → 2.

Example 2:

Input: transactions = [-1,-2,-3]

Output: 0

Explanation:

All transactions are negative. Including any would make the balance negative.

Example 3:

Input: transactions = [3,-2,3,-2,1,-1]

Output: 6

Explanation:

All transactions can be taken in order, balance: 0 → 3 → 1 → 4 → 2 → 3 → 2.

Constraints:

1 <= transactions.length <= 10⁵
-10⁹ <= transactions[i] <= 10⁹