Difference between revisions of "Robustness (computer science)"
From Wiki @ Karl Jones dot com
Karl Jones (Talk | contribs) (Created page with "In computer science, '''robustness''' is the ability of a computer system to cope with errors during execution and cope with erroneous input. == Description == Robustnes...") |
Karl Jones (Talk | contribs) |
||
| Line 5: | Line 5: | ||
Robustness can encompass many areas of computer science, such as robust programming, robust machine learning, and Robust Security Network. | Robustness can encompass many areas of computer science, such as robust programming, robust machine learning, and Robust Security Network. | ||
| − | Formal techniques, such as fuzz testing, are essential to showing robustness since this type of testing involves invalid or unexpected inputs. Alternatively, fault injection can be used to test robustness. | + | Formal techniques, such as [[fuzz testing]], are essential to showing robustness since this type of testing involves invalid or unexpected inputs. Alternatively, fault injection can be used to test robustness. |
Various commercial products perform robustness testing of software systems, and is a process of failure assessment analysis. | Various commercial products perform robustness testing of software systems, and is a process of failure assessment analysis. | ||
| Line 12: | Line 12: | ||
* [[Defensive programming]] | * [[Defensive programming]] | ||
| + | * [[Fuzz testing]] | ||
* [[Non-functional requirement]] | * [[Non-functional requirement]] | ||
Latest revision as of 10:25, 24 August 2016
In computer science, robustness is the ability of a computer system to cope with errors during execution and cope with erroneous input.
Description
Robustness can encompass many areas of computer science, such as robust programming, robust machine learning, and Robust Security Network.
Formal techniques, such as fuzz testing, are essential to showing robustness since this type of testing involves invalid or unexpected inputs. Alternatively, fault injection can be used to test robustness.
Various commercial products perform robustness testing of software systems, and is a process of failure assessment analysis.
See also
External links
- Robustness (computer science) @ Wikipedia
