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%. 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. Yes, for example. B Repeatability is the main problem, evaluators are disoriented or undecided by certain criteria. When it comes to reproducibility, evaluators have strong opinions on certain conditions, but these opinions differ. If the problems are highlighted by several assessors, the problems are naturally systemic or procedural.
If the problems only concern a few assessors, then the problems might simply require a little personal attention. In both cases, training or work aids could be tailored to either specific individuals or all evaluators, depending on the number of evaluators who were guilty of imprecise attribution of attributes. Second, the evaluation of the attribute agreement should be applied and the detailed results of the audit should provide a number of information that will help to understand how evaluation can be the best way to be organized. First, the analyst should determine that there is indeed attribute data. One can assume that the assignment of a code – that is, the division of a code into a category – is a decision that characterizes the error with an attribute. Either a category is correctly assigned to an error, or it is not. Similarly, the appropriate source location is either attributed to the defect or not. These are “yes” or “no” and “correct allocation” or “wrong allocation” answers.
This part is pretty simple. Despite these difficulties, performing an attribute analysis on bug tracking systems is not a waste of time.