Robust Dynamic Selection of Tested Modules in Software Testing for Maximizing Delivered Reliability

Software testing is aimed to improve the delivered reliability of the users. Delivered reliability is the reliability of using the software after it is delivered to the users. Usually the software consists of many modules. Thus, the delivered reliability is dependent on the operational profile which specifies how the users will use these modules as well as the defect number remaining in each module. Therefore, a good testing policy should take the operational profile into account and dynamically select tested modules according to the current state of the software during the testing process. This paper discusses how to dynamically select tested modules in order to maximize delivered reliability by formulating the selection problem as a dynamic programming problem. As the testing process is performed only once, risk must be considered during the testing process, which is described by the tester's utility function in this paper. Besides, since usually the tester has no accurate estimate of the operational profile, by employing robust optimization technique, we analysis the selection problem in the worst case, given the uncertainty set of operational profile. By numerical examples, we show the necessity of maximizing delivered reliability directly and using robust optimization technique when the tester has no clear idea of the operational profile. Moreover, it is shown that the risk averse behavior of the tester has a major influence on the delivered reliability.Comment: 19 pages, 4 figure

Self-Powered Electronics for Piezoelectric Energy Harvesting Devices

International audienc

What Drives Click-Through Rates of Tourism Product Advertisements on Group Buying Websites?

AbstractObtaining stable customer base has become the key mission to the development of group-buying platforms, improving the CTR of product ads on group-buying platform is necessary for formation of stable customer base. This research uses the data about 54 relevant variables covering 7,991 group-buying products of 171 days which from a large tourism group-buying platform in China, and explores the influence factors of click-through rates of group-buying products. The results show that: product name, product discount-level, time pressure showed on product page has significant effect on the CTR of product