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In the tP, you'll be thrown into a codebase of about 6K . It would be hard to understand the design simply by reading the code. That's why the codebase comes with a Developer Guide containing some design models, i.e., the diagrams. That means, you should be able to interpret those models by the time you start the tP in a few weeks. 😨
Let's start getting ready for that today. First, let's go through a high-level explanation of models.
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Now that we have a high-level understanding of the role played by models, let's start learning some UML models, starting with UML class diagrams (and object diagrams which are like a close cousins of class diagrams).
Note that we are learning to interpret these models only, not draw them (that would come later), or design them. Hence, we will be going through these topics fairly rapidly.
Use the UML Reference Sheet to quickly look up UML notation.
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AI's impact on » Reading UML diagrams
You will spend far more time reading diagrams than making them.
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Switching to Java now, let's learn how to write Java GUIs. Fair warning: GUI programming is hard in any language, especially so in Java. Buckle down and get through it; there's no way around it.
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While we are on the topic of Java, also take note of this lesser-known Java 'syntactic sugar' feature that was introduced not long ago, in case you come across it one day or find some use for it in your coding.
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Last week, we started learning about code quality. Let's continue on that, and learn a few other aspects of code quality.
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Next up are two techniques that can be used to improve code quality. You need to learn them as you will be encountering both in your iP soon.
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AI's impact on » Static Analysis
The value of these tools is that they never guess.
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AI's impact on » Code Reviews
Someone still has to say yes to the code, and that someone is you.
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Being able to work with PRs is an essential skill. To get started on that, let's learn how to review PRs properly. Besides, you'll be doing some PR reviews in the iP this week.