Computer Programming is the comprehensive process that leads from an original formulation of a computing problem to executable programs. It involves activities such as analysis, understanding, and generically solving such problems resulting in an algorithm, verification of requirements of the algorithm including its correctness and its resource consumption. Implementation of the build systems and management of derived artifacts such as machine code of computer programs. Computer programming has it’s problems, solutions and how to correct and handle these situations.
Planning the solution to a problem are to draw a flowchart and write pseudo-code, or possibly both. A flowchart is a pictorial representation of a step-by-step solution to a problem. It consists of arrows representing the direction the program takes and boxes and other symbols representing actions. It is a map of what your program is going to do and how it is going to do it. Pseudo-code is an English-like nonstandard language that lets you state your solution with more precision than you can in plain English, but with less precision than is required when using a formal programming language.
Algorithms describe the solution to a problem in terms of the data needed to represent the problem instance and the set of steps necessary to produce the intended result. Algorithms require constructs that perform sequential processing, selection for decision-making, and iteration for repetitive control. The difficulty that often arises for us is the fact that problems and their solutions are very complex. These simple, language- provided constructs and data types, although certainly sufficient to represent complex solutions, are typically at a disadvantage as we work through the problems-solving process.
To manage the complexity of problems and the problem-solving process, computer scientists use abstractions to allow them to focus on the big picture without getting lost in details. By creating models of the problem domain, we are able to utilize a better and more efficient problem-solving process. These models allow us to describe the data that our algorithms will manipulate in a much more consistent way with respect to the problem itself.
Being exposed to different problem-solving techniques and seeing how different algorithms are designed helps us to take on the next challenging problem that we are given. By considering a number of different algorithms, we can begin to develop pattern recognition so that the next time a similar problem arises, we are better able to solve it. There will often be trade-offs that we will need to identify and decide upon. As a computer scientists we will need to know and understand solution evaluation techniques. There are often many ways to solve a problem.
Finding a solution and then deciding whether it is a good one are tasks that we will do over and over again. Computer programming solutions can be handle in many ways. Computer scientists have come up with ways on different solutions for computer programming and making it easier to handle these solutions. Computer programming plays a big part in our world today. Giving us the tools to move forward in the computer world. With the world growing comes more way on solving these computer programming situations and to make then better than before.