Computer science

Common tasks for a computer scientist

Asking questions

This is so people can find new and easier ways to do things, and the way to approach problems with this information.

While computers can do some things easily (like simple math, or sorting out a list of names from A-to-Z), computers cannot answer questions when there is not enough information, or when there is no real answer. Also, computers may take too much time to finish long tasks. For example, it may take too long to find the shortest way through all of the towns in the USA — so instead a computer will try to make a close guess. A computer will answer these simpler questions much faster.

Answering the question

Algorithms are a specific set of instructions or steps on how to complete a task. For example, a computer scientist wants to sort playing cards. There are many ways to sort them — by suits (diamonds, clubs, hearts, and spades) or by numbers (2, 3, 4, 5, 6, 7, 8, 9, 10, Jack, Queen, King, and Ace). By deciding on a set of steps to sort the cards, the scientist has created an algorithm. The scientist then needs to test whether this algorithm works. This shows how well and how fast the algorithm sorts cards.

A simple but slow algorithm is: from one end of the deck, take the first and second cards and check whether they are sorted in the correct order. If they are not, switch them so they are sorted. Do this again with the second and third cards. Repeat these steps with the third and fourth cards, and continue until you get to the end of the deck. Then, starting from the beginning of the deck again, repeat the same steps going though the deck over and over until the deck is sorted. This is called a bubble sort. This method will work, but it will take a very long time.

A better algorithm is: find the first card with the smallest suit and smallest number (ace of spades, according to New Deck Order), and place it at the start. After this, look for the second card, and so on. This algorithm is much faster than bubble sort. This algorithm is called a "selection sort".

Ada Lovelace wrote the first computer algorithm in 1843, for a computer that was never finished. Computers began during World War II.^[1] Computer science separated from the other sciences during the 1960s and 1970s. Now, computer science has its own methods, and has its own technical terms. It is related to electrical engineering, mathematics, and language science.

Computer science has two areas of study. They are known as theoretical computer science and applied computer science. Theoretical computer science looks at how computers do things so that computers can be faster. It also tries to figure out what the limits of computers are. Applied computer science looks at what computers can do to help people solve problems.

Computer engineering looks at the physical parts of computers (hardware). Software engineering looks at the use of computer programs and how to make them.

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Parts of computer science

Central math

Boolean algebra (when something can only be true or false)
Computer numbering formats (how computers count)
Discrete mathematics (math with numbers a person can count)
Symbolic logic (clear ways of talking about math)
Order of operations (which math operations are performed first)

How an ideal computer works

Algorithmic information theory (how easily can a computer answer a question?)
Complexity theory (how much time and memory does a computer need to answer a question?)
Computability theory (can a computer do something?)
Information theory (math that looks at data and how to process data)
Theory of computation (how to answer questions on a computer using algorithms)
Graph theory (math that looks for directions from one point to another)
Type theory (what kinds of data should computers work with?)
Denotational semantics (math for computer languages)
Algorithms (looks at how to answer a question)
Compilers (turning words into computer programs)
Lexical analysis (how to turn words into data)
Microprogramming (how to control the most important part of a computer)
Operating systems (big computer programs, e.g. Linux, Microsoft Windows, Mac OS) to control the computer hardware and software.
Cryptography (hiding data)
Parallel computing (many instructions are carried out simultaneously)
Theoretical computer science (how information can be processed)