What does robust mean in computer science?

Robust systems are able to continue functioning properly under any circumstances. robustness can be defined as the ability to remain operational under unexpected conditions, for example, if the system is exposed to extreme temperatures or is damaged. Robust software is essential in today’s technology. Robustness in the field of software is essential for self-driving cars, medical devices, and the Internet of things.

What does robust mean in cryptography?

robust cryptographic algorithms have been designed to withstand the computational power of specialized hardware. If you imagine using an online shopping website, it is vital for the website to use robust cryptographic algorithms because of the sensitive data that is being stored. The website needs to use algorithms that are difficult to break even with the most powerful computers in the world. This ensures that the website is protected from cyber attacks.

What does robust mean in software engineering?

A robust software system is one that can still function properly under changing conditions, even if the system has faults. Robust software is designed to handle unexpected conditions and errors. It is well-documented, has test cases, and can recover automatically from faults. Robust software is faster than software that is not robust because it avoids redundant checks.

What does robust mean in computer science terms?

Robustness is the ability of a system to continue to function correctly even in the face of failures. This is very different from reliability, which refers to the ability of a system to keep functioning correctly when it is not stressed, or in other words, the probability that a system will continue to function correctly when no failures occur.

What does robust mean in computing?

Robustness is a measure of how well a system or component can continue to function under stress. It can be affected by a variety of factors, such as random errors, unexpected hardware failures, human errors, and environmental conditions. It can be defined in terms of the likelihood of failure, the impact of failures, and the complexity of the system. Robust systems continue to function under these potential failures.