Working in Python · AP Computer Science Principles ↳ AP CSP Standards Reference

AP CSP Coverage: Practices, Big Ideas, Topics

Every Computational Thinking Practice, every Big Idea, and every topic inside it, mapped against what the book actually teaches — sourced from standards/apcsp.json. Chapters 14–19 carry no AP content and are omitted.

19/35
topics taught directly in this book
7/35
planned elsewhere in the course, not yet in this book
9/35
carried by Little Brother (Big Ideas 4–5)

This page maps topics. For the same question asked word by word — which AP CSP vocabulary terms the book actually uses — see AP CSP Vocabulary Coverage.

Computational Thinking Practices

Skills tested across every Big Idea, not tied to one. "Coverage" here means whether the book's actual classroom activity builds the skill — not whether a topic is named.

Computational Solution Design

18–25% of MCQ

Choosing procedures, data structures, and program structure to fit a problem, before writing code.

● Strong

Chapter 4's development-plan section models this directly; choosing between list, dict, and tuple in chapters 9–11 is this skill applied concretely.

Algorithms and Program Development

20–28% of MCQ

Writing, completing, and modifying code: expressions, conditionals, iteration, procedures.

● Strong

This is most of what the book's exercises are, chapters 1–13.

Abstraction in Program Development

7–12% of MCQ

Using functions and data abstraction to manage complexity instead of repeating or inlining everything.

● Strong

Functions from chapter 3 on; lists, dicts, and tuples as abstraction in chapters 9–11.

Code Analysis

12–19% of MCQ

Reading code someone else wrote — tracing execution, predicting output, locating an error — without writing anything new.

● Partial

Every chapter's Debugging section builds the mindset, and chapter 7's doctest work is close, but exercises default to "write a function that…," not "here's a snippet — what does it print." Coding-relevant gap, see below.

Computing Innovations

28–33% of MCQ

Analyzing a computing innovation's purpose, data use, and effects — reading and writing about impact, not code.

○ Not this book

Big Idea 5's practice. Carried by Little Brother, by design — not a coding skill.

Responsible Computing

Create PT only — no MCQ weight

Licensing, accessibility, and crediting sources inside a student's own project.

● Mostly not carried

One piece — crediting code taken from elsewhere — is a coding habit with no counterpart anywhere in the book. Coding-relevant gap, see below.

Big Idea 1 — Creative Development

CRD · 10–13% of MCQ
TopicTitleStatusChaptersNote
1.1CollaborationplannedLab pair work + Create PT, not a standalone lesson
1.2Program Function and Purposein book1, 5partial — no event-driven programming
1.3Program Design and Developmentin book4crediting others' code uncarried
1.4Identifying and Correcting Errorsin book113every chapter's Debugging section

Big Idea 2 — Data

DAT · 17–22% of MCQ
TopicTitleStatusChaptersNote
2.1Binary NumbersplannedCS50T Multimedia
2.2Data CompressionplannedCS50T Multimedia
2.3Extracting Information from Datain book12, 13metadata specifically uncarried
2.4Using Programs with Datain book12, 13file/YAML/shelve work

Big Idea 3 — Algorithms and Programming

AAP · 30–35% of MCQ

The book's core, and the exam's biggest single Big Idea.

TopicTitleStatusChaptersNote
3.1Variables and Assignmentsin book2
3.2Data Abstractionin book9, 10, 11
3.3Mathematical Expressionsin book1, 2
3.4Stringsin book1, 8
3.5Boolean Expressionsin book5
3.6Conditionalsin book5
3.7Nested Conditionalsin book5
3.8Iterationin book3, 7no while anywhere
3.9Developing Algorithmsin book6, 7incremental dev., linear search
3.10Listsin book9
3.11Binary Searchplannedlinear search taught; binary search never introduced
3.12Calling Proceduresin book3, 6
3.13Developing Proceduresin book3, 4
3.14Librariesin book2, 4, 8
3.15Random Valuesin book12
3.16Simulationsplannedno simulation content in ch. 1–13
3.17Algorithmic Efficiencyplannedno informal efficiency discussion
3.18Undecidable Problemsplannedconceptual, non-programming topic

Big Idea 4 — Computer Systems and Networks

CSN · 11–15% of MCQ
TopicTitleStatus
4.1The InternetLittle Brother
4.2Fault ToleranceLittle Brother
4.3Parallel and Distributed ComputingLittle Brother

Big Idea 5 — Impact of Computing

IOC · 21–26% of MCQ
TopicTitleStatus
5.1Beneficial and Harmful EffectsLittle Brother
5.2Digital DivideLittle Brother
5.3Computing BiasLittle Brother
5.4CrowdsourcingLittle Brother
5.5Legal and Ethical ConcernsLittle Brother
5.6Safe ComputingLittle Brother

Big Ideas 4 and 5 carry zero topics in this book, entirely by design. Not a finding of this page.

What isn't covered, ranked by relevance to coding

The split below separates gaps about writing or reading code from gaps about computing's effect on the world. The second kind is expected and already carried elsewhere; the first kind is the one worth watching.

  1. No while loop anywhere in the book (topic 3.8).

    The single most consequential finding in this index. Indefinite iteration is taught only through recursion (ch. 5–6) — related, but not the same pseudocode construct the exam tests, and it can't produce the exam's condition-never-flips or zero-iteration edge cases.

  2. Crediting code taken from another source (topic 1.3, and the matching California gap).

    Not an abstract ethics topic — a habit needed while actually writing code. Nothing in the book models it.

  3. Code Analysis as an exercise format (Practice P4).

    Exercises default to "write a function that…" rather than "here's a snippet — what does it print, or where's the bug." Debugging sections build the mindset, not the trace-and-predict format the MCQ uses.

  4. Event-driven programs (part of topic 1.2).

    Every program in the book runs top to bottom; no event loop or callback anywhere.

  5. Binary search, simulations, algorithmic efficiency, undecidable problems (3.11, 3.16–3.18).

    All four are planned for the November algorithms block, not present in the book as written. Linear search is already taught (ch. 7), so binary search in particular is a direct next step, not a cold start.

Not coding-related — carried elsewhere

  • Binary numbers and data compression (2.1–2.2) — CS50T Multimedia.
  • Everything in Big Ideas 4 and 5, and Practice P5 — Little Brother's territory. A different book's job, not a gap in this one.