Your cart is empty now.
A computer programmer sometimes called more recently a coder (especially in more informal contexts), is a person who creates computer software. The term computer programmer can refer to a specialist in one area of computers, or to a generalist who writes code for many kinds of software. In order to be a successful programmer, one needs to have basic skills.
Here is a set of best skills every programmer must-have!
1) Qualifications and skills
According to developer Eric Sink, the differences between system design, software development, and programming are more apparent. Already in the current market place, there can be found a segregation between programmers and developers, in that one who implements is not the same as the one who designs the class structure or hierarchy. Even more, so that developers become software architects or systems architects, those who design the multi-leveled architecture or component interactions of a large software system.
2) Testing and debugging
Programmers test a program by running it and looking for bugs (errors). As they are identified, the programmer usually makes the appropriate corrections, then rechecks the program until an acceptably low level and severity of bugs remain. This process is called testing and debugging. These are important parts of every programmer’s job. Programmers may continue to fix these problems throughout the life of a program. Updating, repairing, modifying, and expanding existing programs is sometimes called maintenance programming. Programmers may contribute to user guides and online help, or they may work with technical writers to do such work.
3) Problem Solving
In computer science and in the part of artificial intelligence that deals with algorithms (“algorithmics”), problem-solving includes techniques of algorithms, heuristics, and root cause analysis. In these disciplines, problem-solving is part of a larger process that encompasses problem determination, de-duplication, analysis, diagnosis, repair, and other steps.
Other problem-solving tools are linear and nonlinear programming, queuing systems, and simulation.
Much of computer science involves designing completely automatic systems that will later solve some specific problem—systems to accept input data and, in a reasonable amount of time, calculate the correct response or a correct-enough approximation.
In addition, people in computer science spend a surprisingly large amount of human time finding and fixing problems in their programs — debugging.
In psychology and in cognitive neuroscience, patience is studied as a decision-making problem, involving the choice of either a small reward in the short-term, versus a more valuable reward in the long-term. When given a choice, all animals, humans included, are inclined to favor short-term rewards over long-term rewards. This is despite the often greater benefits associated with long-term rewards.
The patience of human users in an online world has been the subject of much recent scientific research. In a 2012 study involving tens of millions of users who watched videos on the Internet, Krishnan and Sitaraman show that online users lose patience in as little as two seconds while waiting for their chosen video to start playing. The study also shows that users who are connected to the Internet at faster speeds are less patient than their counterparts connected at slower speeds, demonstrating a link between the human expectation of speed and human patience. These and other scientific studies of patience have led many social commentators to conclude that the rapid pace of technology is rewiring humans to be less and less patient.
5) Logic and rationality
The ability to reason logically is a fundamental skill of rational agents, hence the study of the form of correct argumentation is relevant to the study of critical thinking. It is, therefore, linked to the field of logic, which is concerned with the analysis of arguments, including the appraisal of their correctness or incorrectness. Another interpretation holds that in the field of epistemology, critical thinking is considered as the logically correct thinking, which allows the differentiation between the logically true and the logically false statements.
“First wave” logical thinking consists of understanding the connections between two concepts or points in thought. It follows a philosophy where the thinker is removed from the train of thought, while the connections and its analysis are devoid of any bias. Kerry S. Walters describes this ideology in his essay Beyond Logicism in Critical Thinking as follows:
“A logistic approach to critical thinking conveys the message to students that thinking is legitimate only when it conforms to the procedures of informal (and, to a lesser extent, formal) logic and that the good thinker necessarily aims for styles of examination and appraisal that are analytical, abstract, universal, and objective. This model of thinking has become so entrenched in conventional academic wisdom that many educators accept it as canon”. The adoption of these principals parallels themselves with the increasing reliance on a quantitative understanding of the world.
In the ‘second wave’ of critical thinking, as defined by Walters, many authors moved away from the logocentric mode of critical thinking that the ‘first wave’ privileged, especially in institutions of higher learning. Scholars began to take a more inclusive view of what constituted critical thinking, but rationality and logic are still widely accepted in many circles as the primary examples of critical thinking. Walters summarizes logicism as “the unwarranted assumption that good thinking is reducible to logical thinking.
6) Applied Mathematics
Applied mathematics is the application of mathematical methods by different fields such as science, engineering, business, computer science, and industry. Thus, applied mathematics is a combination of mathematical science and specialized knowledge. The term “applied mathematics” also describes the professional specialty in which mathematicians work on practical problems by formulating and studying mathematical models.
In the past, practical applications have motivated the development of mathematical theories, which then became the subject of study in pure mathematics where abstract concepts are studied for their own sake. The activity of applied mathematics is thus intimately connected with research in pure mathematics.