Newbie to Newbie Algorithms and Data Structures

As a newbie myself, I can see how this topic can be a little daunting or even pointless at times. However, understanding how algorithms and data structures work fundamentally will lay the foundation for all of your future work in the information technology field.

All computers depend on fundamental algorithms and data structure, so better understanding

them helps you better understand the machine. The structure of knowledge and the algorithm

function together since they are interdependent. Before designing the actual algorithm, the

choice of proper data structures is needed.

Only for specific data structures can certain algorithmic designs and data structure techniques

be used, while some for some data structures cannot be used. To construct the most effective

structure, in order to optimize the data structure, you must decide which algorithm is most

appropriate for that particular data structure. With that being said, each data system has its

own advantages and disadvantages. In all cases, it's uncommon to have a data structure that is

better for use than another structure. The inferior data structure would finally be forgotten if

this were the case and replaced by the superior data structure. Queue, stack, tree, connected

lists, etc are some general examples of data structures (Dourish, Et al, 2016). It can decide

which data structure should be used for each case based on the necessary usage of the

software, as well as the choice of the developer, as they are not universal algorithms.

The designer needs to follow a design strategy as the design process includes taking the

requirements and developing solutions to the problems. It should function correctly in all

situations when designing a solution plan. The individuals who use the framework are not

aware of the nature of the software that you have implemented. There is therefore a machine

manual that is a detailed guide to how the design was accomplished. Through following one

of the two decomposition methods, top-down or bottom-up, a large program should be

divided into small modules and submodules (Bianconi, Filippucci & Buffi, 2019). Execution

time or storage requirements are other significant factors on which software may be

measured.

References

Dourish, P. (2016). Algorithms and their others: Algorithmic culture in context. Big Data &

Society, 3(2), 2053951716665128.

De Veaux, R. D., Agarwal, M., Averett, M., Baumer, B. S., Bray, A., Bressoud, T. C., ... &

Kim, A. Y. (2017). Curriculum guidelines for undergraduate programs in data

science. Annual Review of Statistics and Its Application, 4, 15-30.

Bianconi, F., Filippucci, M., & Buffi, A. (2019). Automated design and modeling for mass-

customized housing. A web-based design space catalog for timber structures. Automation in

construction, 103, 13-25.