Analyzing Attribute Agreement Analysis

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. In addition to the sample size problem, logistics can ensure that listeners do not remember the original attribute they attributed to a scenario when they see it for the second time, also a challenge. Of course, this can be avoided a bit by increasing the sample size and, better yet, waiting a while before giving the scenarios to the evaluators a second time (perhaps one to two weeks). Randomization of transitions from one audit to another can also be helpful. In addition, evaluators tend to work differently when they know they are being examined, so that the fact that they know it is a test also distorts the results. Hiding this in one way or another can help, but it`s almost impossible to achieve, despite the fact that it borders on the inthesis. And in addition to being at best marginally effective, these solutions increase an already demanding study with complexity and time. Despite these difficulties, performing an attribute analysis on bug tracking systems is not a waste of time.

In fact, it is (or may be) an extremely informative, valuable and necessary exercise. The analysis of attributes should only be applied with caution and with a certain focus. 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. At first glance, it appears that the apparent starting point begins with an analysis of the attribute (or attribute-Gage-R-R). That may not be a very good idea. 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. 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.