What is the purpose of modularization in algorithms?

The purpose of modularization in algorithms centers around enhancing code efficiency by promoting the reuse of code through functions or modules. This practice allows a programmer to break down complex problems into smaller, manageable components, which can be developed, tested, and debugged independently. By creating these smaller modules, you facilitate code reuse across different parts of a program or even in different projects, which streamlines development and reduces redundancy.

This approach improves maintainability, as changes or fixes can be made in one module without having to alter other parts of the code extensively. Additionally, modularization often leads to improved readability and organization, making collaboration among developers more straightforward and lowering the chance of introducing errors as updates are applied.

While other choices suggest practices that may involve different aspects of programming, they do not capture the essence of modularization effectively. For instance, creating monolithic code contradicts the principles of modularization, as it involves writing large, single blocks of code rather than subdividing problems. Limiting the size of a program does not accurately reflect the intent behind modularization, which focuses on the structure rather than merely the size. Storing data in arrays is unrelated to modularization as it pertains more to data storage techniques rather than the organization of code and functionality.