What is something a computer program can have that an algorithm Cannot?

For example, a program can have an easter egg, but a thing properly called an algorithm should not. You can have a virus or trojan lurking in a program, but not in an algorithm.

Can every problem be solved with algorithms?

Well, an algorithm is a sequence of steps that solves a problem. With that definition (and in fact most definitions of algorithm) any computer program is also an algorithm. Every Euler problem can be solved with a computer program, so the answer is yes.

What is an unsolvable problem in computer science?

(definition) Definition: A computational problem that cannot be solved by a Turing machine. The associated function is called an uncomputable function. See also solvable, undecidable problem, intractable, halting problem.

What is the problem of algorithm?

Algorithms are commonly used to solve certain types of computational problems. We can often describe such a problem by specifying a relationship between input and output. The sorting problem, for example, can be described like this: Input: a sequence a1, a2., an of n numbers.

What is computer program algorithm?

A programming algorithm is a computer procedure that is a lot like a recipe (called a procedure) and tells your computer precisely what steps to take to solve a problem or reach a goal. The ingredients are called inputs, while the results are called the outputs.

What kinds of problems are solved by algorithms?

This list is about algorithmic problems that would serve a purpose should someone find a solution for them.

• Dealing with text searches.
• Differentiating words.
• Determining whether an application will end.
• Creating and using one-way functions.
• Multiplying really large numbers.
• Dividing a resource equally.

What are problems in computer science?

A problem in computer science is considered unsolved when no solution is known, or when experts in the field disagree about proposed solutions.

What are some problems in computer science?

4 Challenges for Computer Scientists in the 21st Century

• Algorithmic Bias. Susanne isn’t old enough to have a credit rating yet.
• Security in the internet of things. Your fridge might know your every move.
• Encryption and quantum computing. Well, it looks alive, but you never can tell…
• Artificial intelligence.