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Discover effective strategies to optimize your code and avoid time limit errors when solving the `String Sorting Problem`.
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This video is based on the question https://stackoverflow.com/q/63423337/ asked by the user 'James Albert' ( https://stackoverflow.com/u/13448651/ ) and on the answer https://stackoverflow.com/a/63423633/ provided by the user 'Prune' ( https://stackoverflow.com/u/4785185/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Unlocking the Secrets to Efficient Code: The String Sorting Problem

Are you tired of hitting the dreaded time limit when submitting your solution to coding problems online? You're not alone! Many programmers face the challenge of optimizing their code, especially when working on problems like the String Sorting Problem that involve intricate calculations and large input sizes. In this guide, we'll explore a common issue faced during coding competitions and offer a robust solution to ensure your code runs efficiently.

Understanding the Problem Statement

Let’s break down the problem at hand. Here you are given:

A binary number represented as a string A made up of 0s and 1s.

You need to perform a cyclic shift on this string. What does that mean? Simply put, if A is [A0, A1, ..., An-1], then after one cyclic shift, it becomes [A1, A2, ..., An-1, A0].

You repeat this cyclic shift until you encounter the maximum binary number represented by A for the Kth time.

Your task is to output the number of shifts performed to see this maximum value again.

The Initial Approach

In the code you have, the focus is on a straightforward methodology: executing one cyclic shift in a loop, checking if the new value of the binary number is greater than the maximum recorded value. While this approach can sometimes provide the correct answer, it is computationally expensive, especially as N (the length of the string) grows larger.

Problems with the Initial Code

Inefficiency: The code performs multiple rotations and calculations to discover if B (the maximum value) has been achieved.

Redundancy: Each iteration brings no new insights as the shifts are repetitive after reaching N iterations.

Clarity: Variable naming and structure can make it hard for others (or even you in the future) to understand what is happening in the code.

An Advanced Solution to Optimize Performance

Identify the Key Elements

To improve the performance of your algorithm, you should familiarize yourself with the following strategies:

Cyclic Properties: Recognize that after N shifts, the string will start to repeat. Use this to your advantage by limiting checks to N iterations.

Direct Maximum Calculation: Instead of shifting repeatedly, find the maximum string value directly and determine how many shifts it takes to return to that position.

Implementing the Strategy

Here's a more efficient way to rewrite the process:

Append the String: To easily find the maximum binary string after the shifts, concatenate A with itself. This allows you to view all possible continuous shifts without executing them.

[[See Video to Reveal this Text or Code Snippet]]

Find the Maximum: Loop through the first N characters of A_extended to find the maximum-valued substring of length N.

Count the Occurrences: Once you have the maximum binary substring, track how many times it appears as you simulate the shifts.

Example Code Snippet

Here’s a more optimized version of your code:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

By utilizing the properties of cyclic strings and optimizing your approach with fewer iterations and calculations, you can effectively address problems like the String Sorting Problem on HackerEarth. It's all about understanding the problem deeply and structuring your code to minimize repetition and maximize clarity.

Happy coding, and may you never face those time limit errors again!