AP Computer Science Principles: Big Idea 3 - Algorithms and Programming 🚀

Welcome to your ultimate study guide for Big Idea 3! This section is HUGE, making up 30-35% of your AP exam, and it's also the core of your Create project. Let's get you ready to ace it!

This unit is a major focus of the AP exam. Master these concepts for a strong score!

The Big Idea: Code Fundamentals

This Big Idea covers the core programming concepts you'll need. Think of it as the building blocks of all the code you'll see on the AP test. It introduces variables, lists, and procedures that are common to most programming languages. Instead of a specific language, the AP CSP test uses Pseudocode, a simplified language that's similar to Python. Remember, all pseudocode examples come from the College Board's Exam Reference Sheet.

3.1 Variables and Assignments

Key Concept

Variables are like containers that hold values. Remember, capitalization matters!

Key Ideas

Variables are placeholders for values.
Variable names are case-sensitive (e.g., myVar is different from myvar).
Data types categorize data (e.g., numbers, text).

Vocabulary

Variable: A named storage location in memory.
Data Types: Categories of values (e.g., integer, string, boolean).

Resources

🔗 3.1: Variables and Assignments

Practice Question

Multiple Choice:

What is the value of x after the following code is executed?

x ← 5
x ← x + 2

(A) 5 (B) 2 (C) 7 (D) Error

Which of the following is NOT a valid variable name?

(A) my_variable (B) myVariable (C) 1variable (D) myVar1

Free Response:

Write a pseudocode program that declares a variable named age and assigns it your age, then increases it by one, and then prints the new age.

Scoring:

1 point: Correct declaration and assignment of age.
1 point: Correctly incrementing age by one.
1 point: Correctly printing the new value of age.

3.2 Data Abstraction

Key Ideas

Lists store multiple elements.
Each element has an index (position), starting from 1 in pseudocode.
Data abstraction simplifies data for easier program management.

Vocabulary

List: An ordered collection of elements.
Element: An individual value in a list.
Index: The position of an element in a list.
String: A sequence of characters.
Array: Another term for list (often used interchangeably).

Resources

🔗 3.2: Data Abstraction

Practice Question

Multiple Choice:

What is the value of myList[2] after the following code is executed?

myList ← [10, 20, 30, 40]

(A) 10 (B) 20 (C) 30 (D) 40

Which of the following best describes data abstraction?

(A) Making code more complex (B) Simplifying data representation (C) Writing code in multiple languages (D) Using only integers

Free Response:

Create a pseudocode program that initializes a list called scores with three numbers. Then, print the second element of the list.

Scoring:

1 point: Correct initialization of the list scores.
1 point: Correctly accessing and printing the second element of scores.

3.3 Mathematical Expressions

Key Ideas

Algorithms are the logic behind problem-solving.
Programs execute algorithms step-by-step.
The MOD operator gives the remainder of a division.
Expressions are evaluated using order of operations (PEMDAS).

Vocabulary

Algorithm: A step-by-step procedure for solving a problem.
Sequencing: Executing code statements in order.
Code Statement: A single instruction in a program.
Expression: A combination of values, variables, and operators.

Resources

🔗 3.3: Mathematical Expressions

Practice Question

Multiple Choice:

What is the result of the expression 17 MOD 5?

(A) 2 (B) 3 (C) 3.4 (D) 12
What is the value of result after the following code is executed?

result ← 5 + 3 * 2

(A) 16 (B) 11 (C) 10 (D) 13

Free Response:

Write pseudocode to calculate the average of three numbers: 10, 20, and 30. Store the result in a variable called average and print it.

Scoring:

1 point: Correctly summing the three numbers.
1 point: Correctly dividing by 3 to find the average.
1 point: Correctly assigning the result to average and printing it.

3.4 Strings

Key Ideas

Strings are ordered lists of characters.
Use index values to access characters.
String slicing creates substrings.
Concatenation joins strings.

Vocabulary

String Concatenation: Joining strings together.
Substring: A portion of a string.

Resources

🔗 3.4: Strings

Practice Question

Multiple Choice:

What is the result of the expression "hello" + "world"?

(A) helloworld (B) hello world (C) "hello" + "world" (D) Error
If myString is "computer", what is SUBSTRING(myString, 3, 5)?

(A) comp (B) mput (C) mpu (D) put

Free Response:

Write pseudocode that declares a string variable called message with the value "Hello, World!". Then, print the substring that contains only "World".

Scoring:

1 point: Correctly declaring and assigning the string to message.
1 point: Correctly extracting and printing the substring "World".

3.5 Boolean Expressions

Quick Fact

Boolean values are either true or false.

Key Ideas

Boolean variables store true or false.
Relational operators (e.g., <, >, ==) compare values.
Logical operators (NOT, AND, OR) combine Boolean values.

Vocabulary

Boolean Value: A value that is either true or false.

Resources

🔗 3.5: Boolean Expressions

Practice Question

Multiple Choice:

What is the result of the expression (5 > 3) AND (2 < 1)?

(A) true (B) false (C) Error (D) None of the above
If x is true, what is the result of NOT x?

(A) true (B) false (C) Error (D) None of the above

Free Response:

Write a pseudocode program that declares two boolean variables, isRaining and isSunny. Assign isRaining to true and isSunny to false. Then, print the result of isRaining OR isSunny.

Scoring:

1 point: Correctly declaring and assigning values to isRaining and isSunny.
1 point: Correctly evaluating and printing the result of the OR expression.

3.6 Conditionals

Key Ideas

Conditionals control program flow based on conditions.
IF statements execute code if a condition is true.
ELSE statements execute code if the IF condition is false.

Vocabulary

Selection: Choosing which code to execute based on a condition.

Resources

🔗 3.6: Conditionals

Practice Question

Multiple Choice:

What is printed after the following code is executed?

x ← 10
IF x > 5
    DISPLAY("Greater")
ELSE
    DISPLAY("Less")

(A) Greater (B) Less (C) Both Greater and Less (D) Nothing

Which of the following is the correct way to check if a variable age is greater than or equal to 18?

(A) IF age > 18 (B) IF age >= 18 (C) IF age = 18 (D) IF age == 18

Free Response:

Write a pseudocode program that takes a variable called temperature. If the temperature is above 25, print "It's hot!". Otherwise, print "It's not hot". Assume temperature is already assigned a value.

Scoring:

1 point: Correctly using an IF statement to check the temperature.
1 point: Correctly printing "It's hot!" when the condition is true.
1 point: Correctly printing "It's not hot" when the condition is false.

3.7 Nested Conditionals

Key Ideas

Nested conditionals are IF statements inside other IF statements.
Inner conditions are only checked if outer conditions are true.

Vocabulary

Nested Conditional Statements: Conditionals within conditionals.

Resources

🔗 3.7: Nested Conditionals

Practice Question

Multiple Choice:

What is printed after the following code is executed?

x ← 10
y ← 5
IF x > 5
    IF y > 2
        DISPLAY("Both")
    ELSE
        DISPLAY("Only x")
ELSE
    DISPLAY("Neither")

(A) Both (B) Only x (C) Neither (D) Nothing

Which of the following is a characteristic of nested conditionals?

(A) They are always faster than single conditionals (B) They can only have two levels of nesting (C) Inner conditions are checked only if outer conditions are true (D) They are used only for string manipulation

Free Response:

Write a pseudocode program that takes two variables: age and hasLicense. If age is greater than or equal to 16, then check if hasLicense is true. If both conditions are met, print "Can drive". Otherwise, print "Cannot drive".

Scoring:

1 point: Correctly using an outer IF statement for age.
1 point: Correctly using a nested IF statement for hasLicense.
1 point: Correctly printing the appropriate message based on both conditions.

3.8 Iteration

Memory Aid

Remember: "Repeat n times" is like a for loop, and "Repeat until (condition)" is like a while loop.

Key Ideas

Iteration repeats code blocks.
"Repeat n times" loops execute a set number of times.
"Repeat until (condition)" loops execute until a condition is met.

Vocabulary

Iteration: Repeating a block of code.

Resources

🔗 3.8: Iteration

Practice Question

Multiple Choice:

How many times will the following loop execute?

REPEAT 5 TIMES
    DISPLAY("Hello")

(A) 0 (B) 1 (C) 4 (D) 5

What will be the final value of x after the following code executes?

x ← 0
REPEAT UNTIL x > 3
    x ← x + 1

(A) 2 (B) 3 (C) 4 (D) 5

Free Response:

Write a pseudocode program that uses a REPEAT loop to print the numbers from 1 to 5. Scoring:

1 point: Correctly using a REPEAT loop.
1 point: Correctly initializing a counter variable.
1 point: Correctly printing the numbers 1 to 5.

3.9 Developing Algorithms

Key Ideas

Different algorithms can achieve the same result.
Similar algorithms can have different side effects.
Algorithms can be created by combining and modifying existing ones.

Vocabulary

None

Resources

🔗 3.9: Developing Algorithms

Practice Question

Multiple Choice:

Which of the following is true about algorithms?

(A) There is only one correct algorithm for every problem (B) Algorithms that look similar always yield the same results (C) Different algorithms can achieve the same goals (D) Algorithms are always written in a specific programming language
When developing a new algorithm, it is helpful to:

(A) Always start from scratch (B) Never modify existing algorithms (C) Combine and modify existing algorithms (D) Only use one specific programming language

Free Response:

Describe two different algorithms to find the largest number in a list of numbers. One should use a loop and the other should use a recursive approach. (You don't have to write the pseudocode, just describe the process).

Scoring:

1 point: Correctly describing an iterative algorithm using a loop.
1 point: Correctly describing a recursive algorithm.
1 point: Explaining that both algorithms achieve the same result.

3.10 Lists

Key Ideas

Basic list operations: access, assign, insert, add, remove, length.
Traversing: going through a list, either fully or partially.

Vocabulary

Traverse: To go through each element of a list.
Linear/Sequential Search: Examining each element in order until found.

Resources

🔗 3.10: Lists

Practice Question

Multiple Choice:

If myList is [10, 20, 30, 40], what is the result of INSERT(myList, 2, 25)?

(A) [10, 20, 25, 30, 40] (B) [10, 25, 20, 30, 40] (C) [10, 20, 30, 25, 40] (D) Error
What does LENGTH(myList) return for myList = [1, 2, 3, 4, 5]?

(A) 4 (B) 5 (C) 6 (D) Error

Free Response:

Write a pseudocode program that initializes a list called numbers with the numbers 1, 2, 3, 4, and 5. Then, traverse the list and print each number.

Scoring:

1 point: Correctly initializing the list numbers.
1 point: Correctly using a loop to traverse the list.
1 point: Correctly printing each element of the list.

3.11 Binary Search

Key Concept

Binary search requires the data to be sorted first. It eliminates half the data with each step.

Key Ideas

Binary search eliminates half the data each step.
Data must be sorted before using binary search.

Vocabulary

Binary Search: A search algorithm that repeatedly divides the search interval in half.

Resources

🔗 3.11: Binary Search

Practice Question

Multiple Choice:

Which of the following is a requirement for using binary search?

(A) The data must be unsorted (B) The data must be sorted (C) The data must be strings (D) The data must be integers
In a binary search of a sorted list of 16 elements, what is the maximum number of iterations needed to find a specific value?

(A) 2 (B) 3 (C) 4 (D) 16

Free Response:

Explain the process of binary search. Why is it more efficient than a linear search in a sorted list? (No pseudocode required).

Scoring:

1 point: Correctly explaining the process of binary search.
1 point: Explaining why binary search is more efficient than linear search in a sorted list.

3.12 Calling Procedures

Key Ideas

Procedures are reusable blocks of code.
Procedures may require parameters.
Call procedures using arguments.
Program returns to the point of the call after procedure termination.

Vocabulary

Procedure: A named block of code that performs a specific task.
Parameters: Variables listed in the procedure definition.
Arguments: Values passed to the procedure when it is called.

Resources

🔗 3.12: Calling Procedures

Practice Question

Multiple Choice:

What are the values passed to a procedure when it is called called?

(A) Parameters (B) Arguments (C) Variables (D) Constants
What happens after a procedure terminates?

(A) The program stops (B) The program restarts (C) The program returns to the point of the call (D) The program starts a new procedure

Free Response:

Write a pseudocode program that defines a procedure called greet that takes a parameter name. The procedure should print "Hello, " followed by the name. Then, call the procedure with the argument "Alice".

Scoring:

1 point: Correctly defining the procedure greet with a parameter name.
1 point: Correctly printing the greeting message inside the procedure.
1 point: Correctly calling the procedure greet with the argument "Alice".

3.13 Developing Procedures

Key Ideas

Procedures allow you to use code without knowing its inner workings.
Solve large problems by breaking them into smaller sub-problems.
Procedural abstraction allows modifications without affecting the whole program.

Vocabulary

Procedural Abstraction: Using a procedure without knowing its implementation details.
Modularity: Dividing a program into independent modules or procedures.

Resources

🔗 3.13: Developing Procedures

Practice Question

Multiple Choice:

What is the main benefit of procedural abstraction?

(A) Makes code more complex (B) Allows modification of procedures without affecting the whole program (C) Makes code run slower (D) Requires more code to be written
Which of the following is a benefit of using procedures?

(A) They make code harder to read (B) They increase code duplication (C) They help to solve large problems by breaking them into smaller sub-problems (D) They make code less efficient

Free Response:

Explain how procedural abstraction helps in managing complexity in a program. Give an example. (No pseudocode required).

Scoring:

1 point: Correctly explaining how procedural abstraction manages complexity.
1 point: Providing a relevant example to support the explanation.

3.14 Libraries

Key Ideas

Libraries provide pre-written code.
Import code from libraries to use in new programs.
APIs (Application Program Interfaces) describe how to use library procedures.

Vocabulary

Software Library: A collection of pre-written code.
Application Program Interface (API): A set of rules and specifications that software programs can follow to communicate with each other.

Resources

🔗 3.14: Libraries

Practice Question

Multiple Choice:

What is the purpose of a software library?

(A) To make code more complex (B) To provide pre-written code (C) To confuse programmers (D) To slow down programs
What does API stand for?

(A) Application Program Interface (B) Advanced Programming Instructions (C) Automated Program Input (D) Application Processing Index

Free Response:

Explain how libraries and APIs help in software development. Give an example of a library you might use in a program. (No pseudocode required).

Scoring:

1 point: Correctly explaining how libraries help in software development.
1 point: Correctly explaining how APIs help in software development.
1 point: Providing a relevant example of a library.

3.15 Random Values

Key Ideas

Random number generation produces different results each time.

Vocabulary

None

Resources

🔗 3.15: Random Values

Practice Question

Multiple Choice:

What is a key characteristic of using random number generation in a program?

(A) The program always produces the same result (B) The program may produce different results each time (C) The program always produces an error (D) The program runs faster
Which of the following is a typical use of random values in programming?

(A) Sorting a list (B) Searching for an element (C) Simulating a game (D) Calculating the average

Free Response:

Explain why random values are useful in simulations or games. Give an example. (No pseudocode required).

Scoring:

1 point: Correctly explaining why random values are useful in simulations.
1 point: Correctly explaining why random values are useful in games.
1 point: Providing a relevant example.

3.16 Simulations

Key Ideas

Simulations simplify complex phenomena for a specific purpose.
Simulations involve removing or simplifying real-world details.
Simulations may contain bias based on what is included or excluded.

Vocabulary

Simulation: A simplified representation of a real-world system or process.

Resources

🔗 3.16: Simulations

Practice Question

Multiple Choice:

What is the main purpose of a simulation?

(A) To make a system more complex (B) To simplify a complex system for a stated goal (C) To replace real-world systems (D) To always produce accurate results
What is a potential drawback of using simulations?

(A) They are always too complex (B) They may contain bias (C) They are always faster than real-world systems (D) They are always accurate

Free Response:

Describe how a simulation can be used to model a real-world process. What are some limitations of using simulations? (No pseudocode required).

Scoring:

1 point: Correctly describing how a simulation can model a real-world process.
1 point: Identifying at least one limitation of using simulations.

3.17 Algorithmic Efficiency

Key Ideas

Efficiency is measured by how many times a statement executes.
Polynomial or lower efficiency is considered reasonable.
Exponential or factorial efficiency is considered unreasonable.
Heuristics provide approximate solutions for hard problems.

Vocabulary

Problem: A task to be solved.
Instance: A specific case of a problem.
Decision Problem: A problem with a yes/no answer.
Optimization Problem: A problem that seeks the best solution.
Efficiency: A measure of how well an algorithm uses resources.
Reasonable Amount of Time: Polynomial or lower time complexity.
Unreasonable Amount of Time: Exponential or factorial time complexity.
Heuristic: An approach that may not be optimal but is practical.

Resources

🔗 3.17: Algorithmic Efficiency

Practice Question

Multiple Choice:

What is a characteristic of an algorithm that runs in a reasonable amount of time?

(A) Exponential efficiency (B) Factorial efficiency (C) Polynomial efficiency (D) Unreasonable efficiency
What is a heuristic?

(A) An exact solution to a problem (B) An approximate solution to a problem (C) An algorithm that is always optimal (D) An algorithm that always runs in unreasonable time

Free Response:

Explain the difference between algorithms that run in reasonable time and those that do not. Give an example of a problem where a heuristic solution might be more appropriate. (No pseudocode required).

Scoring:

1 point: Correctly explaining the difference between reasonable and unreasonable time.
1 point: Providing a relevant example of a problem where a heuristic is appropriate.

3.18 Undecidable Problems

Key Ideas

Undecidable problems may be solvable in some cases but not all.
No algorithm can solve an undecidable problem in all cases.

Vocabulary

Decidable Problem: A problem for which an algorithm can always produce a solution.
Undecidable Problem: A problem for which no algorithm can always produce a solution.

Resources

🔗 3.18: Undecidable Problems

Practice Question

Multiple Choice:

What is a characteristic of an undecidable problem?

(A) It can always be solved by an algorithm (B) It cannot be solved by any algorithm (C) It may be solvable in some cases but not all (D) It is always easy to solve
Which of the following is a characteristic of a decidable problem?

(A) It cannot be solved by any algorithm (B) It may be solvable in some cases but not all (C) An algorithm can always produce a solution (D) It is always hard to solve

Free Response:

Explain what an undecidable problem is and why it is important in computer science. (No pseudocode required).

Scoring:

1 point: Correctly explaining what an undecidable problem is.
1 point: Correctly explaining why undecidable problems are important in computer science.

Final Exam Focus

Exam Tip

Prioritize: Focus on variables, conditionals, loops, lists, and procedures.
Pseudocode: Be comfortable reading and writing pseudocode.
Practice: Work through practice problems, especially FRQs.
Time Management: Don't get stuck on one question; move on and come back if you have time.
Common Pitfalls: Pay attention to index starting from 1, order of operations, and correct use of logical operators.

Highest Priority Topics

Variables and Data Types: Understand how to store and manipulate data.
Control Structures: Master IF, ELSE, and nested conditionals, as well as REPEAT loops.
Lists: Know how to access, modify, and traverse lists. 💡
Procedures: Understand how to define, call, and use procedures effectively.
Algorithmic Thinking: Be able to create, compare, and modify algorithms.

Common Question Types

Multiple Choice: Evaluating expressions, tracing code, and understanding concepts.
Free Response: Writing pseudocode, designing algorithms, and explaining concepts.

Last-Minute Tips

Stay Calm: Take deep breaths and approach each question methodically.
Read Carefully: Pay close attention to the details of each question.
Show Your Work: Even if you don't get the final answer, partial credit is often given for showing your process.
Review the Basics: Make sure you're solid on the fundamental concepts.

You've got this! Go ace that exam! 💪

Big Idea 3: Algorithms and Programming

Ben Davis

AP Computer Science Principles: Big Idea 3 - Algorithms and Programming 🚀

The Big Idea: Code Fundamentals

3.1 Variables and Assignments

Key Ideas

Vocabulary

Resources

3.2 Data Abstraction

Key Ideas

Vocabulary

Resources

3.3 Mathematical Expressions

Key Ideas

Vocabulary

Resources

3.4 Strings

Key Ideas

Vocabulary

Resources

3.5 Boolean Expressions

Key Ideas

Vocabulary

Resources

3.6 Conditionals

Key Ideas

Vocabulary

Resources

3.7 Nested Conditionals

Key Ideas

Vocabulary

Resources

3.8 Iteration

Key Ideas

Vocabulary

Resources

3.9 Developing Algorithms

Key Ideas

Vocabulary

Resources

3.10 Lists

Key Ideas

Vocabulary

Resources

3.11 Binary Search

Key Ideas

Vocabulary

Resources

3.12 Calling Procedures

Key Ideas

Vocabulary

Resources

3.13 Developing Procedures

Key Ideas

Vocabulary

Resources

3.14 Libraries

Key Ideas

Vocabulary

Resources

3.15 Random Values

Key Ideas

Vocabulary

Resources

3.16 Simulations

Key Ideas

Vocabulary

Resources

3.17 Algorithmic Efficiency

Key Ideas

Vocabulary

Resources

3.18 Undecidable Problems

Key Ideas

Vocabulary

Resources

Final Exam Focus

Highest Priority Topics

Common Question Types

Last-Minute Tips