November 25, 2021

CarryGold In C Plus Plus

Solving the Problem of Conditional Statement Optimization in C++

CarryGold in CPP

Programming is all about solving problems efficiently and effectively. In the world of competitive programming and software development, writing optimized code is crucial. Let's dive into the provided code snippet and explore how to optimize the conditional statement for better performance.

Understanding the Problem

The given code snippet is written in C++ and aims to solve a particular problem using conditional statements. Let's break down the problem statement and the code's logic:

  1. The code takes an integer t as input, representing the number of test cases.
  2. For each test case, three integers n, x, and y are input.
  3. The goal is to determine whether the expression (n+1)*y >= x holds true or not.

If the expression is true, the code prints "Yes", otherwise, it prints "No".

Analyzing the Code

The provided code is functional and correctly solves the problem. However, there is an opportunity for optimization in the conditional statement.

The original conditional statement:

if ((n+1)*y >= x)

This statement calculates (n+1)*y every time it's evaluated. Since the value of (n+1)*y remains constant within each test case, it's unnecessary to compute it repeatedly.

Optimizing the Code

We can optimize the code by calculating (n+1)*y once and storing it in a variable before the conditional statement. This way, the calculation is performed only once for each test case, improving the code's efficiency.

Here's the optimized version of the code:

#include <iostream> using namespace std; int main() { int t; cin >> t; while (t--) { int n, x, y; cin >> n >> x >> y; int product = (n + 1) * y; // Calculate (n+1)*y only once if (product >= x) { cout << "Yes" << endl; } else { cout << "No" << endl; } } return 0; }

Benefits of Optimization

Optimizing the conditional statement by precomputing the constant value (n+1)*y provides several benefits:

  1. Improved Performance: By performing the calculation only once, the code becomes more efficient, especially when dealing with a large number of test cases.

  2. Reduced Redundancy: Unnecessary repeated calculations are eliminated, making the code easier to understand and maintain.

  3. Faster Execution: Since the calculation is performed only once per test case, the code execution is faster, which is crucial for competitive programming tasks.


Optimizing code is a valuable skill that can lead to better performance and efficiency in programming tasks. By identifying and eliminating redundant calculations, we can make our programs run faster and more smoothly. In the provided code snippet, optimizing the conditional statement by calculating (n+1)*y once greatly enhances the efficiency of the program while maintaining its correctness.


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