Difference between revisions of "Relevant test case"

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A relevant test case is a combination of data set, application and parameters which reflects production behaviour or at least allow assumptions about true production state (to be proven). The definition of a relevant test case is essential and vital for performance engeneering. Typically it need (at least basic) knowledge about algorithms used in the application, preduction about needed size of computation jobs, and of course which features of software will be used.
 
A relevant test case is a combination of data set, application and parameters which reflects production behaviour or at least allow assumptions about true production state (to be proven). The definition of a relevant test case is essential and vital for performance engeneering. Typically it need (at least basic) knowledge about algorithms used in the application, preduction about needed size of computation jobs, and of course which features of software will be used.
  

Revision as of 11:16, 11 May 2020



A relevant test case is a combination of data set, application and parameters which reflects production behaviour or at least allow assumptions about true production state (to be proven). The definition of a relevant test case is essential and vital for performance engeneering. Typically it need (at least basic) knowledge about algorithms used in the application, preduction about needed size of computation jobs, and of course which features of software will be used.

In the first approximation a [set of] real production test cases[s] is a relevant test case for himself, sic! However these test cases are typicall large, long-running and unhandy to impossible to analyse, so a reduced relevant test case is needed.

  • The same software path as in production must be used. Needless to say that if you use in production a compute kernel A, a data set for kernel B would be not relevant.
  • The hotspots of production runs must also be hotspost in the reduced relevant test case (rule-of-thumb: about of the half of overall excution time should be in hotspots). This in turn lead to the rule: Do not downsize too much (for performance engineering