Robustness (computer science): Difference between revisions

Revision as of 01:09, 7 November 2016

Revision as of 01:09, 7 November 2016

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== Introduction ==

In general, building robust systems that encompass every point of possible failure is difficult because of the vast quantity of possible inputs and input combinations.<ref name="MIT">http://groups.csail.mit.edu/mac/users/gjs/6.945/readings/robust-systems.pdf</ref> Since all inputs and input combinations would require too much time to test, developers cannot run through all cases exhaustively. Instead, the developer will try to generalize such cases.<ref>http://www.softwaretestingclub.com/profiles/blogs/importance-of-making</ref> For example, imagine inputting in some [[Integer (computer science)|integer values]]. Some selected inputs might consist of a negative number, zero, and a positive number. When using these numbers to test software in this way, the developer generalizes the set of all reals into three numbers. This is a more efficient and manageable method, but more prone to failure. Generalizing test cases is an example of just one technique to deal with failure—specifically, failure due to invalid user input. Systems generally may also fail due to other reasons as well, such as disconnecting from a network.

Regardless, complex systems should still handle any errors encountered gracefully. There are many examples of such successful systems. Some of the most robust systems are evolvable and can be easily adapted to new situations.<ref name="MIT" />