Following is an outline of the major topics covered by the AP Examinations in Computer Science. These topics are explained in greater detail in the Teacher’s Guide Ñ AP Computer Science. The ordering here is intended to define the scope of the course, but not necessarily the sequence. The topics in the right-hand column will not be tested on the Computer Science A Examination.
I. Program Design
The overall goal for designing a piece of software (a computer program) is to correctly solve the given problem. At the same time, this goal should encompass specifying and designing a program that is understandable, can be adapted to changing circumstances, and has the potential to be reused in whole or in part. The design process needs to be based on a thorough understanding of the problem to be solved.
| Computer Science A and AB | Computer Science AB only |
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A. Problem definition B. Program design |
II. Program Implementation
The overall goals of program implementation parallel those of program design. Modules of the program that fill common needs should be built so that they can be reused easily in other pro- grams. Procedural and data abstraction are important parts of program implementation.
| Computer Science A and AB | Computer Science AB only |
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A. Implementation techniques B. Programming constructs |
III. Program Analysis
The analysis of programs includes analyzing and testing programs to determine whether they correctly meet their specifications. It also includes the analysis of programs or the algorithms they implement so as to understand their time and space requirements when applied to different data sets.
| Computer Science A and AB | Computer Science AB only |
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A. Testing B. Debugging C. Understanding and modifying existing code D. Handling errors — robust behavior
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| E. Reasoning about programs 1. Pre/post conditions 2. Assertions |
3. Invariants |
| F. Analysis of algorithms 1. Informal comparisons of running times 2. Exact calculation of statement execution counts |
3. Big-O notation 4. Worst case/average case time and space analysis |
| G. Numerical limits Limitations of finite representations (e.g., integer bounds, imprecision of floating-point representations, and round-off error) |
IV. Standard Data Structures
Data structures are the means by which the information used by a program is represented within the program. Abstraction is an important theme in the development and application of data structures.
| Computer Science A and AB | Computer Science AB only |
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A. Simple data types (e.g., int, char, bool, double) B. Aggregate data types C. Classes |
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| D. Linked lists E. Stacks F. Queues G. Trees H. Heaps I. Priority queues |
V. Standard Algorithms
Standard algorithms can serve as examples of good solutions to standard problems. Programs implementing them can serve as models of good program design. They provide examples for analysis of program efficiency. Many are intertwined with standard data structures.
| Computer Science A and AB | Computer Science AB only |
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A. Operations on data structures |
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| B. Operations on dynamic data structures 1. Traversals 2. Insertion 3. Deletion 4. Allocation/deallocation of memory |
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| C. Searching 1. Sequential (linear) 2. Binary |
3. Hashing |
| D. Sorting 1. Selection 2. Insertion 3. Mergesort 4. Quicksort |
5. Heapsort |
VI. Computer Systems
A working knowledge of the major hardware and software components of computer systems is necessary for the study of computer science, as is the importance of considering the ethical and social implications of computing systems. These topics need not be covered in detail, but they should be considered throughout the course.
| Computer Science A and AB | Computer Science AB only |
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A. Major hardware components B. System software |