Modular programming is the process of subdividing a computer program into separate sub-programs. Modularity provides flexibility in a structured programming design the following way: Modularity enables multiple programmers to work on a program at the same time. Correct answer: A
It provides developers flexibility in module maintenance.This makes the program easier to read and understand.
Answer:
look up ultrasurf and just follow the thingy and it will download a vpn ive had it on my computer for a fat min
Explanation:
Answer:
The output is second half of the month, refers to both
Answer:
a. Password length, password encryption, password complexity
Explanation:
Under this scenario, the best combination would be Password length, password encryption, password complexity. This is because the main security problem is with the user's passwords. Increasing the password length and password complexity makes it nearly impossible for individuals to simply guess the password and gain access, while also making it extremely difficult and time consuming for hackers to use software to discover the password as well. Password excryption would be an extra layer of security as it encrypts the password before storing it into the database, therefore preventing eavesdroppers from seeing the password and leaked info from being used without decryption.
The discipline of building hardware architectures, operating systems, and specialized algorithms for running a program on a cluster of processors is known as <u>parallel computing.</u>
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<h3>What is Parallel Computing?</h3>
Parallel computing refers to the process of breaking down larger problems into smaller, independent, often similar parts that can be executed simultaneously by multiple processors communicating via shared memory, the results of which are combined upon completion as part of an overall algorithm. The primary goal of parallel computing is to increase available computation power for faster application processing and problem solving.
<h3>Types of parallel computing</h3>
There are generally four types of parallel computing, available from both proprietary and open source parallel computing vendors:
- Bit-level parallelism: increases processor word size, which reduces the quantity of instructions the processor must execute in order to perform an operation on variables greater than the length of the word.
- Instruction-level parallelism: the hardware approach works upon dynamic parallelism, in which the processor decides at run-time which instructions to execute in parallel; the software approach works upon static parallelism, in which the compiler decides which instructions to execute in parallel.
- Task parallelism: a form of parallelization of computer code across multiple processors that runs several different tasks at the same time on the same data.
- Superword-level parallelism: a vectorization technique that can exploit parallelism of inline code.
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