捷孚凯

Traditional software fault tolerance makes use of design-diversity-based redundancy. While proven to be effective, the independent development of multiple versions of a program or component is connected with high costs. This article shows that failures caused by so-called Mandelbugs (i.e., software faults whose activation and/or error propagation depends on the system environment) can often be treated by generating or forcing a new or modified execution environment. In the case of aging-related bugs, a subtype of Mandelbugs, failures can be postponed/prevented via a proactive technique known as software rejuvenation. Indeed, techniques based on environmental diversity, such as retry, reboot, or failover to an identical replica, are successfully used in practice. We discuss two such real-case examples, the IBM Session Initiation Protocol (SIP) Application Server cluster and Avaya gateway servers.

Team Energy Theory proposes using the metaphor of energy to describe team work. Specifically, TET explores how the rules of energy can be used to describe team work. This paper describes a workshop which explored the theory. The workshop decided the theory was useful and provides some insight. It was agreed the model could be usefully applied with other groups to discuss what made for an effective team and how less effective teams came to be. Several parallels were explored, e.g. natural tendency to minimise energy expenditure, and several more were identified for further exploration, e.g. the different forms of energy and conversation of energy between these forms.

Online businesses are increasingly relying on targeted advertisements as a revenue stream, which might lead to privacy concerns and hinder product adoption. Therefore, it is crucial for online companies to understand which types of targeted advertisements consumers will accept. In recent years, users have been increasingly targeted by political advertisements, which has caused adverse reactions in media and society. Nonetheless, few studies experimentally investigate user privacy concerns and their role in acceptance decisions in response to targeted political advertisements. To fill this gap, we explore the magnitude of privacy concerns towards targeted political ads compared to “traditional” targeting in the product context. Surprisingly, we find no notable differences in privacy concerns between these data use purposes. In the next step, user preferences over ad types are elicited with the help of a discrete choice experiment in the mobile app adoption context. Our findings suggest that while targeted political advertising is somewhat less desirable than targeted product advertising, the odds of choosing an app are statistically insignificant between two data use purposes. Together, these results contribute to a better understanding of users’ privacy concerns and preferences in the context of targeted political advertising online.

Sample size analysis is a key part of the planning phase of any research. So far, however, hardly any literature focuses on sample size analysis methods for two-sample linear rank tests, although these methods have optimal properties for different distributions. This article provides a new sample size analysis method for linear rank tests for location shift alternatives based on score-generating functions. Results show a slightly anti-conservative behavior, no severe risk of an occurring circular argument at small to moderate variances of the population’s distribution, and good performance compared to alternate sample size analysis methods for the most well-known linear rank test, the Wilcoxon-Mann-Whitney test.