Let’s look upon a real world example to see how we can implement this technique via coding.
Let's say we have a web application that displays a list of products and allows users to add items to their shopping cart. The development team wants to add a new feature that allows users to view recommended products based on their browsing history. However, they also have several other changes they want to make, such as improving the layout of the product page and fixing a few bugs.
To control the change batch size, the team breaks down these changes into smaller batches and works on each change separately:
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Improve the layout of the product page: The team creates a separate branch in the code repository for this change and works on it separately. They use automated tests to ensure that the layout changes don't introduce any new defects.
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Fix bugs: The team creates a separate branch in the code repository for this change and works on it separately. They use automated tests to ensure that the bug fixes don't introduce any new defects.
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Implement recommended products feature: The team creates a separate branch in the code repository for this change and works on it separately. They use automated tests to ensure that the recommended products feature works as expected.
By breaking down the changes into smaller batches and testing each change thoroughly, the team can control the change batch size and reduce the risk of defects. This helps speed up delivery and ensures that the software is of high quality, providing a better user experience for customers.
Thus, it has been established via coding that Controlling change batch size and keeping it small will definitely help in speedy delivery and minimal risk
