In the context of computersoftware, robustness is the resilience of the system, especially when under stress or when confronted with invalid input. For example, an operating system is considered robust if it operates correctly when it is starved of memory or storage space, or when confronted with an application that has bugs or is behaving in an illegal fashion - such as trying to access memory or storage belonging to other tasks in a multitasking system. Jump to: navigation, search A computer is a device or machine for processing information from data according to a program — a compiled list of instructions. ... Computer software (or simply software) refers to one or more computer programs and data held in the storage of a computer for some purpose. ... Jump to: navigation, search In computing, an operating system (OS) is the system software responsible for the direct control and management of hardware and basic system operations. ...
Most modern computer designs have memory protection hardware allowing processes to be forcibly confined to their own memory space. In older designs, such as most 8-bit systems and many early 16-bit ones, this was not available, and thus system integrity was preserved mainly by clean design and careful coding. Thus the perceived robustness of a system became a major factor in debates about different machines and operating systems' quality and performance. 8-bit refers to the number of bits used in the data bus of a computer. ... In computer science, 16-bit is an adjective used to describe integers that are at most two bytes wide, or to describe CPU architectures based on registers, address buses, or data buses of that size. ...
It is the ability of the software system to maintain function even with the changes in internal structure or external enviornment
Robust statistics seeks to provide methods that emulate classical methods, but which are not unduly affected by outliers or other small departures from model assumptions.
Robust parameteric statistics tends to rely on replacing the normal distribution in classical methods with the t-distribution with low degrees of freedom (high kurtosis; degrees of freedom between 4 and 6 have often been found to be useful in practice) or with a mixture of two or more distributions.
Robust statistical methods, of which the trimmed mean is a simple example, seek to outperform classical statistical methods in the presence of outliers, or, more generally, when underlying parametric assumptions are not quite correct.
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