You're reviewing a C++ codebase and notice that a function processing large data structures is passed its arguments by value, potentially causing unnecessary copies and overhead. What might be a more efficient way to pass these structures without modifying the original data?
- Passing by pointer
- Passing by reference
- Using lambda functions
- Using std::move
Passing arguments by reference allows functions to access the original memory location without creating a copy, leading to more efficient memory usage. While passing by pointer can achieve a similar outcome, it requires manual dereferencing. Passing by reference is a more idiomatic solution in C++ for this use case.
The goto statement can only jump to labels within the same _______.
- function
- file
- scope
- class
The goto statement in C++ can only jump to labels within the same function. Jumping between functions or other scopes would introduce significant complexity and is not allowed.
A function that calls itself directly or indirectly is known as a _______ function.
- iterative
- recursive
- inline
- overloaded
A function that calls itself, either directly or indirectly through other functions, is known as a recursive function. Recursion is a powerful programming technique where a problem is broken down into smaller instances of the same problem, typically leading to simpler solutions.
An infinite loop can be intentionally created for program structures like event listeners using for(;;), which is often referred to as a _______ loop.
- endless
- continuous
- forever
- looping
The term endless loop is often used to describe loops that have no termination condition, such as for(;;), and they continue executing indefinitely until externally terminated.
While developing a complex algorithm in C++, you notice that multiple nested loops and conditionals are making the logic increasingly hard to follow. How might judicious use of the return statement improve code clarity and reduce nested structures?
- By exiting functions early when conditions are met.
- By skipping iterations in loops.
- By jumping to specific parts of the code.
- By creating nested functions.
The "early return" pattern, where you exit a function as soon as you know the result, can simplify code by reducing the need for deeply nested structures. Instead of having multiple nested conditionals, you can check a condition and return early if it's met, leading to more linear and readable code. Using the return statement to skip iterations or jump to specific code parts is not its intended use in C++.
You are designing a graphics system that involves various shapes like Circle, Rectangle, and Triangle. How might you design the class structure considering reusability and organized hierarchy?
- Encapsulation
- Polymorphism
- Inheritance
- Composition
Inheritance would be the most suitable approach in this case. A base class named "Shape" can have common attributes like coordinates and colors. Derived classes like "Circle", "Rectangle", and "Triangle" can then inherit from this base class and add their unique methods and properties related to their specific shapes.
The result of the expression (true || _______) in C++ will always be true.
- FALSE
- TRUE
- 0
- 1
The logical OR (`
What is slicing in the context of object-oriented programming in C++?
- Removing virtual functions
- Copying an object's base part
- Increasing object size
- Converting to different type
Slicing in C++ refers to the situation where a derived class object is assigned to a base class object. In such cases, only the base class's portion of the derived object is copied, and the additional members of the derived class are 'sliced off'. This can lead to unintended behaviors if not carefully managed.
What is the maximum number of conditions that can be nested within each other using nested if-else structures?
- 10
- 5
- 3
- There is no fixed limit.
There isn't a fixed limit to how many conditions you can nest using if-else structures in C++. However, it's essential to keep code readability and maintainability in mind. Excessively nested conditions can make the code hard to understand and debug.
In a complex software project where multiple classes are interacting with one another, you discover that there is a significant performance bottleneck during the creation and deletion of objects, which is causing inefficiency. What strategy or principle might be applied to manage object creation and deletion more efficiently?
- Use of object pooling.
- Reduce the use of polymorphism.
- Always use inline functions.
- Implement multi-threading.
Object pooling is a design pattern where a set of initialized objects are kept ready to use, rather than allocating and deallocating them on the fly. This can greatly reduce the overhead of object creation and deletion in scenarios where such operations are frequent. Other options, while useful in specific contexts, don't directly address the efficient management of object creation and deletion.
When might using a table of function pointers be preferable over a switch-case statement for handling various cases/conditions?
- When handling a static set of conditions that seldom change.
- When trying to make the code more object-oriented.
- When handling a very large number of cases that might change dynamically or are loaded from an external source.
- When the conditions are based on string values.
Using a table of function pointers can be highly beneficial when there's a need to handle a dynamic set of conditions, especially if these conditions might be loaded from an external source or change during runtime. It allows for a more flexible and extensible approach than hard-coding numerous cases in a switch-case statement. Furthermore, it can lead to cleaner and more maintainable code in some scenarios.
Which access specifier allows a class member to be accessible only within its own class and friends?
- public
- protected
- private
- global
The private access specifier in C++ ensures that class members are accessible only within the class they are defined and by friend functions or classes. This helps in the principle of encapsulation, keeping data and methods secure from unintended access.