What term refers to the act of picking out important bits of information from a problem?

What term refers to the act of picking out important bits of information from a problem?

• A. Simplification
• B. Abstraction
• C. Decomposition
• D. Analysis

Answer: (B)

The term that refers to the act of picking out important bits of information from a problem is abstraction. In computer science and programming, abstraction involves simplifying complex systems by focusing on the essential features while omitting unimportant details. This allows for a clearer understanding of the problem at hand, enabling developers to address issues effectively without getting bogged down by unnecessary information. In this context, abstraction is crucial because it helps in the creation of models and algorithms that represent real-world problems, making them easier to analyze and solve. By identifying only the relevant aspects of a problem, programmers can create more efficient solutions and streamline their coding processes. The other choices—while related to problem-solving and understanding—do not emphasize the act of isolating important information in the same way that abstraction does. For instance, simplification generally involves making something easier to understand or do, while decomposition refers to breaking down a problem into smaller, more manageable parts. Analysis typically involves examining data or systems to draw conclusions but does not specifically refer to the extraction of key information from a problem.

The term that refers to the act of picking out important bits of information from a problem is abstraction. In computer science and programming, abstraction involves simplifying complex systems by focusing on the essential features while omitting unimportant details. This allows for a clearer understanding of the problem at hand, enabling developers to address issues effectively without getting bogged down by unnecessary information.

In this context, abstraction is crucial because it helps in the creation of models and algorithms that represent real-world problems, making them easier to analyze and solve. By identifying only the relevant aspects of a problem, programmers can create more efficient solutions and streamline their coding processes.

The other choices—while related to problem-solving and understanding—do not emphasize the act of isolating important information in the same way that abstraction does. For instance, simplification generally involves making something easier to understand or do, while decomposition refers to breaking down a problem into smaller, more manageable parts. Analysis typically involves examining data or systems to draw conclusions but does not specifically refer to the extraction of key information from a problem.