Keseimbangan lintasan perakitan atau assembly line balancing problem (ALBP) merupakan masalah yang sering terjadi di teknik industri sebagai bagian dari NP-hard combinatorial optimization problem. They also provide insight into costs and benefits of the various parameters used in the approach. The obtained results show relative advantage of using feedback mechanism for some objects in terms of early fault detection. The study is performed on five open source Java objects. Second, a comprehensive empirical study is performed to evaluate the performance of the approach and to identify the effects of using different parameters included in the technique. First, we introduce a feedback mechanism and a new change information gathering strategy. We have previously introduced a new approach for test case prioritization using Bayesian Networks (BN) which integrates different types of information to estimate the probability of each test case finding bugs. An analysis of Grundy's performance shows that its user models are effective in guiding its performance.Ī cost effective approach to regression testing is to prioritize test cases from a previous version of a software system for the current release. Some techniques to modify stereotypes on the basis of experience are discussed. If stereotypes are to be useful to Grundy, they must accurately characterize the users of the system. A system, Grundy, is described that builds models of its users, with the aid of stereotypes, and then exploits those models to guide it in its task, suggesting novels that people may find interesting. The issue of how to resolve the conflicts that will arise among such inferences is discussed. In order to build user models quickly, a large amount of uncertain knowledge must be incorporated into the models. It first outlines the issues, and then proposes stereotypes as a useful mechanism for building models of individual users on the basis of a small amount of information about them. This paper addresses the problems that must be considered if computers are going to treat their users as individuals with distinct personalities, goals, and so forth.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |