Section 9.1: Computational Thinking Skills

Abstraction

• Need and Benefits of Using Abstraction:
• Simplifies Complexity: By focusing only on the necessary details, abstraction helps in managing and understanding complex systems.
• Improves Efficiency: It allows developers to break down complex processes into simpler, more manageable components.
• Enhances Reusability: Abstract solutions can be generalized across different problems, making them reusable for other applications.

• Purpose of Abstraction:
• The primary purpose of abstraction is to hide complex details from the user, presenting only the necessary information. This aids in focusing on what matters most, solving the problem at hand without getting lost in details.

• Producing an Abstract Model:
• To create an abstract model, identify the core components and functionalities needed to address the user’s needs or solve the problem. Exclude all non-essential details. This model represents the system at a high level, without delving into the specifics of implementation.

Decomposition

• Breaking Down Problems:
• Start by identifying the major components of the problem.
• Break these components into smaller parts that are easier to understand and solve.
• These sub-problems can often be modularized into procedures or functions in a program.

Section 9.2: Algorithms

Understanding Algorithms

• Characteristics of Algorithms:
• Well-defined steps: Each step is clear and unambiguous.
• Finiteness: Algorithms must finish after a finite number of steps.
• Effectiveness: Each step must be sufficiently basic that it can be carried out, in principle, by a person using only pencil and paper.
• Input and Output: Algorithms take inputs and produce outputs.

Writing and Documenting Algorithms

• Pseudocode: This is a method used to write down an algorithm. It involves writing the steps of the algorithm in a form that mimics code but is simpler and not tied to any specific programming language.
• Basic Constructs of Pseudocode:
• Sequence: Instructions are executed in a linear progression.
• Selection: Decision-making (if-else conditions).
• Iteration (Repetition): Repeating a sequence of instructions (loops like for, while).

• Documenting Algorithms:
• Can be done using structured English (a verbose form of pseudocode), flowcharts, or directly in pseudocode.

Stepwise Refinement

• Using Stepwise Refinement:
• Begin with a high-level overview of the solution.
• Break it down into more detailed steps.
• Continue refining each step until the algorithm can be directly implemented in code.

Logic Statements in Algorithms

• Using Logic Statements:
• These are often expressed in pseudocode as IF, AND, OR, NOT conditions that control the flow of the algorithm based on certain criteria being met.

第 9.1 节：计算思维技能

抽象化

• 使用抽象化的必要性和益处：
• *简化复杂性：**通过只关注必要的细节，抽象化有助于管理和理解复杂系统。
• *提高效率：**它允许开发者将复杂过程分解为更简单、更易管理的组件。
• *增强可重用性：**抽象解决方案可以泛化到不同的问题上，使其可用于其他应用。

• 抽象化的目的：
• 抽象化的主要目的是向用户隐藏复杂的细节，仅呈现必要信息。这有助于专注于最重要的事项，解决手头的问题而不会迷失在细节中。

• 产生抽象模型：
• 创建抽象模型时，要确定解决问题或满足用户需求所需的核心组件和功能。排除所有非关键细节。这个模型代表了系统的高层次表示，而不深入具体实现的细节。

分解

• 分解问题的步骤：
• 首先识别问题的主要组件。
• 将这些组件进一步细分为更易理解和解决的小部分。
• 这些子问题通常可以在程序中模块化为过程或函数。

第 9.2 节：算法

理解算法

• 算法的特征：
• *明确的步骤：**每一步都是清晰且不含糊的。
• *有限性：**算法必须在有限的步骤后结束。
• *有效性：**每一步都必须足够基本，以至于原则上可以通过使用纸笔由人执行。
• *输入与输出：**算法接收输入并产生输出。

编写和记录算法

• *伪代码：**这是一种记录算法的方法。它涉及以模拟代码的形式写下算法的步骤，但比代码更简单，且不绑定于任何特定的编程语言。
• 伪代码的基本结构：
• *顺序：**指令按线性进展执行。
• *选择：**决策制作（如 if-else 条件）。
• *迭代（重复）：**重复执行一系列指令（如 for, while 循环）。

• 记录算法：
• 可以使用结构化英语（一种冗长的伪代码形式）、流程图或直接用伪代码来完成。

分阶段细化

• 使用分阶段细化：
• 从解决方案的高层概览开始。
• 将其细分为更详细的步骤。
• 继续细化每个步骤，直到算法可以直接在代码中实现。

算法中的逻辑语句

• 使用逻辑语句：
• 这些通常在伪代码中表达为 IF, AND, OR, NOT 条件，控制算法的流程，基于满足特定标准。