The accuracy of a measurement system is analyzed by segmenting into two main elements: repeatability (the ability of a particular evaluator to assign the same value or attribute several times under the same conditions) and reproducibility (the ability of several assessors to agree on a set of circumstances). In the case of an attribute measurement system, repeatability or reproducibility problems necessarily pose precision problems. In addition, if global accuracy, repeatability and reproducibility are known, distortions can also be detected in situations where decisions are always wrong. Attribute analysis can be an excellent tool for detecting the causes of inaccuracies in a bug tracking system, but it must be used with great care, reflection and minimal complexity, should it ever be used. The best way to do this is to first monitor the database and then use the results of that audit to perform a targeted and optimized analysis of repeatability and reproducibility. In this example, a repeatability assessment is used to illustrate the idea, and it also applies to reproducibility. The fact is that many samples are needed to detect differences in an analysis of the attribute, and if the number of samples is doubled from 50 to 100, the test does not become much more sensitive. Of course, the difference that needs to be identified depends on the situation and the level of risk that the analyst is prepared to bear in the decision, but the reality is that in 50 scenarios, it is difficult for an analyst to think that there is a statistical difference in the reproducibility of two examiners with match rates of 96 percent and 86 percent. With 100 scenarios, the analyst will not be able to see any difference between 96% and 88%. If the test is planned and designed effectively, it can reveal enough information about the causes of the accuracy problems to justify a decision not to use attribute analysis at all. In cases where the trial does not provide sufficient information, the analysis of the attribute agreement allows for a more detailed review to inform the introduction of training changes and error correction in the measurement system. An attribute analysis was developed to simultaneously assess the effects of repeatability and reproducibility on accuracy.
It allows the analyst to review the responses of several reviewers if they look at multiple scenarios multiple times. It establishes statistics that assess the ability of evaluators to agree with themselves (repeatability), with each other (reproducibility) and with a master or correct value (overall accuracy) known for each characteristic – over and over again. However, a bug tracking system is not an ongoing payment. The assigned values are correct or not; There is no (or should not) grey area. If codes, locations and degrees of gravity are defined effectively, there is only one attribute for each of these categories for a particular error. Like any measurement system, the accuracy and accuracy of the database must be understood before the information is used (or at least during use) to make decisions.