What aspect of algorithms is directly linked to feasibility?

What aspect of algorithms is directly linked to feasibility?

• A. The ability to run indefinitely
• B. The possibility of being understood differently
• C. The requirement for finite resources and time
• D. The necessity of complex designs

Answer: (C)

The aspect of algorithms that is directly linked to feasibility is the requirement for finite resources and time. Feasibility in the context of algorithms refers to whether an algorithm can be realistically executed within the constraints of available resources—such as time, memory, and processing power. An algorithm must be able to complete its task within a reasonable timeframe and using manageable amounts of computational resources. This is crucial because even if an algorithm theoretically works, if it requires more resources than are available or takes an impractically long time to run, it is not feasible. Feasible algorithms are those that can be practically implemented and run to completion, delivering outputs without exceeding the limits of time and resources. In contrast, if algorithms run indefinitely, use excessive resources, or require overly complex designs without clear benefits, they could become impractical for real-world applications, rendering them infeasible despite potentially interesting theoretical properties.

The aspect of algorithms that is directly linked to feasibility is the requirement for finite resources and time. Feasibility in the context of algorithms refers to whether an algorithm can be realistically executed within the constraints of available resources—such as time, memory, and processing power. An algorithm must be able to complete its task within a reasonable timeframe and using manageable amounts of computational resources. This is crucial because even if an algorithm theoretically works, if it requires more resources than are available or takes an impractically long time to run, it is not feasible.

Feasible algorithms are those that can be practically implemented and run to completion, delivering outputs without exceeding the limits of time and resources. In contrast, if algorithms run indefinitely, use excessive resources, or require overly complex designs without clear benefits, they could become impractical for real-world applications, rendering them infeasible despite potentially interesting theoretical properties.