2. What strategies can handle complex or nested conditions during selection refinement?

There are several strategies that can handle complex or nested conditions during selection refinement:

1. Use of Conditional Statements: This is the most basic strategy where you use if-else statements to handle complex conditions. You can nest these statements to handle more complex conditions.

2. Use of Logical Operators: Logical operators like AND, OR, NOT can be used to combine or negate conditions. This can be used to handle complex conditions.

3. Use of Functions or Methods: You can encapsulate complex conditions in functions or methods. This not only makes your code cleaner but also allows you to handle complex conditions.

4. Use of Decision Trees: Decision trees are a type of model that can handle complex conditions. They work by creating a tree-like model of decisions based on conditions.

5. Use of Rule-Based Systems: Rule-based systems use a set of if-then rules to handle complex conditions. These rules can be nested and can handle a large number of conditions.

6. Use of Machine Learning Algorithms: Some machine learning algorithms can handle complex conditions. For example, neural networks can learn to handle complex conditions from data.

7. Use of Recursive Functions: Recursive functions are functions that call themselves. They can be used to handle complex conditions that have a recursive nature.

8. Use of State Machines: State machines are models of computation that can handle complex conditions. They work by transitioning from one state to another based on conditions.