Because of their slow execution, interpreters are now rarely used outside of program development, where they may help a programmer to locate errors quickly.
These findings suggest that as a system evolves, the use of some commonly used metrics to identify which classes are more prone to errors becomes increasingly difficult and we should seek alternative methods (to the metric-prediction models) to locate error-prone classes if we want high accuracy.
Finally, the checker performs verification: if there is a violation of specifications, NuSMV allows to locate errors in WA design and appropriate adjustments are carried out.
Unlike ten Raa [23] and ten Raa and van der Ploeg [26] who use a priori estimated errors, Steenge proposes a way to locate errors a posteriori.
As lexical resources become increasingly larger, it becomes correspondingly more difficult to locate errors in them.
However, in false negative cases, only a comprehensive set of experiments (one attempted deletion per gene) can locate errors.
Correctness is currently evaluated dichotomously (i.e., both, the located error and the reason need to be correct).
This analysis avoids the earlier difficulty, since both items are things that are, and it locates error in our having latched on to the wrong item.
In this sense, the mobile devices could be well located (location error below 1 m), thanks to external network localization processes like infrared laser and UWB.
The two-stage approach here thus combines a constructed-response format (the click on an arbitrary position in the model to locate the error) with a selected-response format (the selection of the error type from a provided list).
While model checking is capable of automatically testing that a concurrent system satisfies its formal specification, it can not precisely locate an error and suggest a repair, i.e., a suitable correction, to the system.
