Скачать или смотреть Fixing the Second Generation Bug in Conway's Game of Life Code

Discover the solution to a common bug in Conway's Game of Life by learning how to properly manage matrix states in your C code.
---
This video is based on the question https://stackoverflow.com/q/75276866/ asked by the user 'HerrYetii' ( https://stackoverflow.com/u/20928564/ ) and on the answer https://stackoverflow.com/a/75277966/ provided by the user 'Craig Estey' ( https://stackoverflow.com/u/5382650/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: The second generation is bugged (C, Conways Game of Life)

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Unraveling the Bug in the Second Generation of Conway’s Game of Life

Conway's Game of Life has captured the interest of programmers and enthusiasts for decades. However, when implementing this iconic cellular automation in C, you may run into unexpected issues, especially when generating the next generations of your cells. One common problem arises when the second generation doesn’t align with the expected behavior based on the initial random state.

In this post, we will dissect the problem you've encountered, which is that the second generation of your cells doesn't match the expectations set by the first generation. We'll walk through the root cause of the issue and present a solution to ensure accurate generation transitions.

Understanding the Problem

When you choose to “generate random state” and specify a percentage of living cells, followed by either step-by-step or flowing animation, the output is often not as expected. This discrepancy arises because the current state of the matrix is being modified during the checks for the next generation.

Key terms to note:

Current Matrix: The matrix reflecting the current state of living and dead cells.

Future Matrix (or new state): The matrix that you plan to fill with the next generation’s state based on the current matrix.

So, What Went Wrong?

Your initial implementation modifies the current matrix while still determining the next round of generations. This midpoint modification leads to flawed logic in decision-making for cell states, resulting in unexpected behavior during generation transitions.

The Solution

To resolve the bug, we need to ensure that changes to the current matrix do not affect the calculations needed for determining the next state. Here’s how to implement this:

Step 1: Leveraging Two Matrix Pointers

In the check_cell function, modify the parameters to accept both the current state matrix and a new state matrix. This way, you can read from the old state while writing to the new state without confusion.

Step 2: Modify the Check Cell Function

Below, I’ll present the modified version of the check_cell function that operates on two matrices:

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

Step 3: Adjust the Step Function

The step function will also need a tweak. Ensure it passes both the old matrix and the new matrix to the check_cell function properly.

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

Conclusion

By implementing the above changes, you ensure that the transition from one generation to the next accurately reflects the rules of Conway's Game of Life. This structured approach preserves the integrity of your matrices during generation computation and thus resolves the issue you've been encountering.

Now, you can enjoy a correctly functioning Game of Life, where each generation visually represents your initial configurations, adhering to the fascinating rules established by Conway. Happy coding!