The size and complexity of cloud environments make them prone to failures. The traditional approach to achieve a high dependability for these systems relies on constant monitoring. However, this method is purely reactive. A more proactive approach is provided by online failure prediction (OFP) techniques. In this paper, we describe a OFP system for private IaaS platforms, currently under development, that combines different types of data input, including monitoring information, event logs, and failure data. In addition, this system operates at both the physical and virtual planes of the cloud, taking into account the relationships between nodes and failure propagation mechanisms that are unique to cloud environments. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit Categories and Subject Descriptors

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The concept of service oriented architecture has been extensively explored in software engineering, due to the fact that it produces architectures made up of several interconnected modules, easy to reuse when building new systems. This approach to design would be impossible without interconnection mechanisms such as REST (Representational State Transfer) services, which allow module communication while minimizing coupling. . However, this low coupling brings disadvantages, such as the lack of transparency, which makes it difficult to systematically create tests without knowledge of the inner working of a system. In this article, we present an automatic error detection system for REST services, based on a statistical analysis over responses produced at multiple service invocations. Thus, a service can be systematically tested without knowing its full specification. The method can find errors in REST services which could not be identified by means of traditional testing methods, and provides limited testing coverage for services whose response format is unknown. It can be also useful as a complement to other testing mechanisms.

Nowadays, integration of e-learning platforms has become a key issue in e-learning. In order to facilitate this integration, most e-learning platforms depict their functionality in terms of web services. However, the availability of these services in every platform is very heterogeneous. In addition, every platform follows its own philosophy when designing its services. This paper analyses three of the most successful elearning platforms (Blackboard, Moodle and Sakai), identifying their web services, and comparing their readiness for the development of a virtual campus based on these services. The goal of the paper is to facilitate the integration of these platforms in an information technology infrastructure.

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