AP CS A

Descripción

(Course Outline) AP Computer Science Mapa Mental sobre AP CS A, creado por KonSpiral el 27/11/2013.
KonSpiral
Mapa Mental por KonSpiral, actualizado hace más de 1 año
KonSpiral
Creado por KonSpiral hace casi 11 años
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Resumen del Recurso

AP CS A
  1. Object Oriented Analysis and Design
    1. Program Design

      Nota:

      • 1. Read and understand a problem description, purpose, and goals. 2. Apply data abstraction and encapsulation. 3. Read and understand class specifications and relationships among the classes (“is-a,” “has-a” relationships). 4. Understand and implement a given class hierarchy. 5. Identify reusable components from existing code using classes and class libraries.
      1. Class Design

        Nota:

        • 1. Design and implement a class. 2. Choose appropriate data representation and algorithms. 3. Apply functional decomposition. 4. Extend a given class using inheritance.
      2. Program Implementation
        1. Programming constructs
          1. Primitive types vs. objects
            1. Declaration

              Nota:

              • a. Constant declarations b. Variable declarations c. Class declarations d. Interface declarations e. Method declarations f. Parameter declarations
              1. Console output (System.out.print/println)
                1. Control

                  Nota:

                  • a. Methods b. Sequential c. Conditional d. Iteration e. Understand and evaluate recursive methods
                2. Implementation Techniques
                  1. Methodology

                    Nota:

                    • a. Object-oriented development b. Top-down development c. Encapsulation and information hiding d. Procedural abstraction
                  2. Java library classes (included in the AP Java subset)
                  3. Program Analysis
                    1. Debugging

                      Nota:

                      • 1. Categorize errors: compile-time, run-time, logic. 2. Identify and correct errors. 3. Employ techniques such as using a debugger, adding extra output statements,
                      1. Understand and modify existing code
                        1. Extend existing code using inheritance
                          1. Understand error handling

                            Nota:

                            • Understand runtime exceptions
                            1. Reason about prograing

                              Nota:

                              • 1. Pre- and post-conditions 2. Assertions
                              1. Analysis of algorithms

                                Nota:

                                • 1. Informal comparisons of running times 2. Exact calculation of statement execution counts
                                1. Numerical representations and limits

                                  Nota:

                                  • 1. Representations of numbers in different bases 2. Limitations of finite representations (e.g., integer bounds, imprecision of floating-point representations, and round-off error)
                                  1. Testing

                                    Nota:

                                    •  Testing 1. Test classes and libraries in isolation. 2. Identify boundary cases and generate appropriate test data. 3. Perform integration testing.
                                  2. Standard Data Structures

                                    Nota:

                                    • Data structures are used to represent information within a program. Abstraction is an important theme in the development and application of data structures.
                                    1. Simple Data Types

                                      Nota:

                                      • int, boolean
                                      1. Classes
                                        1. Lists
                                          1. Arrays
                                          2. Standard Algorithms

                                            Nota:

                                            • Standard algorithms serve as examples of good solutions to standard problems. Many are intertwined with standard data structures. These algorithms provide examples for analysis of program efficiency.
                                            1. Operations on Data Structures

                                              Nota:

                                              • 1. Traversals 2. Insertions 3. Deletions
                                              1. Searching

                                                Nota:

                                                • 1. Sequential 2. Binary
                                                1. Sorting

                                                  Nota:

                                                  • 1. Selection 2. Insertion 3. Mergesort
                                                2. Computing in Context

                                                  Nota:

                                                  • An awareness of the ethical and social implications of computing systems is necessary for the study of computer science. These topics need not be addressed in detail but should be considered throughout the course.
                                                  1. System reliability
                                                    1. Privacy
                                                      1. Legal issues and intellectual property
                                                        1. Social and ethical ramifications of computer use
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