Скачать или смотреть Solving the Selection Sort Algorithm Issue: Handling Negative Numbers in Python

Discover how to fix the `Selection Sort` algorithm in Python for arrays with negative numbers, ensuring correct sorting without errors.
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This video is based on the question https://stackoverflow.com/q/71365517/ asked by the user 'Juan Pablo' ( https://stackoverflow.com/u/5439065/ ) and on the answer https://stackoverflow.com/a/71365534/ provided by the user 'BrokenBenchmark' ( https://stackoverflow.com/u/17769815/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Solving the Selection Sort Algorithm Issue: Handling Negative Numbers in Python

Sorting algorithms are a vital part of programming, allowing us to organize data efficiently. However, even a popular algorithm like Selection Sort can present difficulties, especially when confronted with negative numbers in an array. In this guide, we will explore a common issue encountered with the Selection Sort algorithm and provide a detailed solution.

Understanding the Problem

The crux of the problem occurs when trying to implement a Selection Sort on an array that contains negative numbers. A programmer experienced issues with their implementation, particularly when the array was sorted using the following code:

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

The Selection Sort function was defined, but it produced inaccurate results when sorting array A. This led to confusion and the need to troubleshoot the code.

Breakdown of the Existing Code

Here’s a look at the existing implementation:

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

Issues Identified:

Loop Bounds: The loops incorrectly use len(list) - 1 as their upper bounds, leading to missed checks, particularly on the last element.

Variable Naming: Using list as a variable name shadows the built-in Python list type, which can lead to bugs and confusion in the code.

Solution

To solve the issue, we need to adjust the bounds of the loops and refactor the variable naming. Here’s the revised version of the Selection Sort algorithm:

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

Key Adjustments Made:

Adjusted Loop Bounds: Both for loops are now set to run until len(input_list), allowing the algorithm to evaluate every element in the array.

Renamed Variable: The variable list was replaced with input_list, avoiding conflicts with the built-in list type in Python.

Testing the Solution

Once the adjustments were made, testing the function on the sorted array B produced the correct output:

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

Expected Output:

The above code will successfully sort the array, and you should see the following sorted output:

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

Conclusion

In conclusion, when dealing with the Selection Sort algorithm and arrays that include negative numbers, it is crucial to ensure your loop bounds are correctly defined. Misalignments in these bounds can lead to sorting inaccuracies, as demonstrated by the example provided. Refactoring your code by using clearer variable names also helps maintain clarity and avoid bugs.

Feel encouraged to apply these solutions to your own sorting implementations, and happy coding!