Marc Oriol

Usage-Based Online Testing for Proactive Adaptation of Service-Based Applications

Increasingly, service-based applications (SBAs) are composed of third-party services available over the Internet. Even if third-party services have shown to work during design-time, they might fail during the operation of the SBA due to changes in their implementation, provisioning, or the communication infrastructure. As a consequence, SBAs need to dynamically adapt to such failures during run-time to ensure that they maintain their expected functionality and quality. Ideally the need for an adaptation is proactively identified, i.e., failures are predicted before they can lead to consequences such as costly compensation and roll-back activities. Currently, approaches to predict failures are based on monitoring. Due to its passive nature, however, monitoring might not cover all relevant service executions, which can diminish the ability to correctly predict failures. In this paper we demonstrate how online testing, as an active approach, can improve failure prediction by considering a broader range of service executions. Specifically, we introduce a framework and prototypical implementation that exploits synergies between monitoring, online testing and quality prediction. For online test selection and assessment we adapt usage-based testing strategies. We experimentally evaluate the strengths of our approach in predicting the need for an adaptation of an SBA.

Quality models for web services: A systematic mapping

Context: Quality of Service (QoS) is a major issue in various web service related activities. Quality models have been proposed as the engineering artefact to provide a common framework of understanding for QoS, by defining the quality factors that apply to web service usage. Objective: The goal of this study is to evaluate the current state of the art of the proposed quality models for web services, specifically: (1) which are these proposals and how are they related; (2) what are their structural characteristics; (3) what quality factors are the most and least addressed; and (4) what are their most consolidated definitions. Method: We have conducted a systematic mapping by defining a robust protocol that combines automatic and manual searches from different sources. We used a rigorous method to elicitate the keywords from the research questions and a selection criteria to retrieve the final papers to evaluate. We have adopted the ISO/IEC 25010 standard to articulate our analysis. Results: We have evaluated 47 different quality models from 65 papers that fulfilled the selection criteria. By analyzing in depth these quality models, we have: (1) distributed the proposals along the time dimension and identified their relationships; (2) analyzed their size (visualizing the number of nodes and levels) and definition coverage (as indicator of quality of the proposals); (3) quantified the coverage of the different ISO/IEC 25010 quality factors by the proposals; (4) identified the quality factors that appeared in at least 30% of the surveyed proposals and provided the most consolidated definitions for them. Conclusions: We believe that this panoramic view on the anatomy of the quality models for web services may be a good reference for prospective researchers and practitioners in the field and especially may help avoiding the definition of new proposals that do not align with current research.

Enhancing Federated Cloud Management with an Integrated Service Monitoring Approach

Cloud Computing enables the construction and the provisioning of virtualized service-based applications in a simple and cost effective outsourcing to dynamic service environments. Cloud Federations envisage a distributed, heterogeneous environment consisting of various cloud infrastructures by aggregating different IaaS provider capabilities coming from both the commercial and the academic area. In this paper, we introduce a federated cloud management solution that operates the federation through utilizing cloud-brokers for various IaaS providers. In order to enable an enhanced provider selection and inter-cloud service executions, an integrated monitoring approach is proposed which is capable of measuring the availability and reliability of the provisioned services in different providers. To this end, a minimal metric monitoring service has been designed and used together with a service monitoring solution to measure cloud performance. The transparent and cost effective operation on commercial clouds and the capability to simultaneously monitor both private and public clouds were the major design goals of this integrated cloud monitoring approach. Finally, the evaluation of our proposed solution is presented on different private IaaS systems participating in federations.

Integrated Monitoring Approach for Seamless Service Provisioning in Federated Clouds

Cloud Computing offers simple and cost effective outsourcing in dynamic service environments, and allows the construction of service-based applications using virtualization. By aggregating the capabilities of various IaaS cloud providers, federated clouds can be built. Managing such a distributed, heterogeneous environment requires sophisticated interoperation of adaptive coordinating components. In this paper we introduce an integrated federated management and monitoring approach that enables autonomous service provisioning in federated clouds. In this architecture, cloud brokers manage the number and the location of the utilized virtual machines for the received service requests. In order to provide seamless service executions, a state of the art monitoring solution is proposed that supports cloud selection performed by the management layer of the architecture. Our solution is able to cope with highly dynamic service executions by federating heterogeneous cloud infrastructures in a transparent and autonomous manner.

SALMonADA: a platform for monitoring and explaining violations of WS-agreement-compliant documents

Quality assurance techniques have been developed to supervise the service quality (QoS) agreed between service-based systems (SBSs) consumers and providers. Such QoS is usually included in service level agreements (SLAs) and thus, SLA monitoring platforms have been developed supporting violation detection. However, just a few of them provide explanation of the violations caused by observed QoS at monitoring time, but not in an user-friendly format. Therefore, we propose a general monitoring and analysis conceptual reference model and we instantiated it with SALMonADA, a SBS that notifies the clients with violations and their causes in their own easy-to-understand specification terms. In addition, our platform performs an early analysis notification that avoids delays in the client notification time when a violation takes place. Moreover, we have implemented a web application as a SALMonADA client, to prove how it monitors, analyses and reports to their clients the service level fulfillment of real services subject to a SLA specified with WS-Agreement.

The Crowd in Requirements Engineering: The Landscape and Challenges

Crowd-based requirements engineering (CrowdRE) could significantly change RE. Performing RE activities such as elicitation with the crowd of stakeholders turns RE into a participatory effort, leads to more accurate requirements, and ultimately boosts software quality. Although any stakeholder in the crowd can contribute, CrowdRE emphasizes one stakeholder group whose role is often trivialized: users. CrowdRE empowers the management of requirements, such as their prioritization and segmentation, in a dynamic, evolved style through collecting and harnessing a continuous flow of user feedback and monitoring data on the usage context. To analyze the large amount of data obtained from the crowd, automated approaches are key. This article presents current research topics in CrowdRE; discusses the benefits, challenges, and lessons learned from projects and experiments; and assesses how to apply the methods and tools in industrial contexts. This article is part of a special issue on Crowdsourcing for Software Engineering.

Goal-Driven Adaptation of Service-Based Systems from Runtime Monitoring Data

Service-based systems need to provide flexibility to adapt both to evolving requirements from multiple, often conflicting, ephemeral and unknown stakeholders, as well as to changes in the runtime behavior of their component services. Goal-oriented models allow representing the requirements of the system whilst keeping information about alternatives. We present the MAESoS approach which uses i* diagrams to identify quality of service requirements over services. The alternatives are extracted and kept in a variability model. A monitoring infrastructure identifies changes in runtime behavior that can propagate up to the level of stakeholder goals and trigger the required adaptations. We illustrate the approach with a scenario of use.

How Can Quality Awareness Support Rapid Software Development? – A Research Preview

Context and Motivation: Rapid software development (RSD) refers to the organizational capability to develop, release, and learn from software in rapid cycles without compromising its quality. To achieve RSD, it is essential to understand and manage software quality along the software lifecycle. Question/Problem: Despite the numerous information sources related to product quality, there is a lack of mechanisms for supporting continuous quality management throughout the whole RSD process. Principal ideas/Results: We propose Q-Rapids, a data-driven, quality-aware RSD framework in which quality and functional requirements are managed together. Quality requirements are incrementally elicited and refined based on data gathered at both development time and runtime. Project, development, and runtime data is aggregated into quality-related indicators to support decision makers in steering future development cycles. Contributions: Q-Rapids aims to increase software quality through continuous data gathering and analysis, as well as continuous management of quality requirements.

Monitoring the service-based system lifecycle with SALMon

Current monitoring frameworks do not cover the whole service-based system lifecycle.We present SALMon, a versatile QoS monitoring framework that supports the service-based system lifecycle.We have executed and validated our approach by including SALMon in several frameworks.We have conducted a performance evaluation over real web services using suitable estimators for response time. Context and motivationService-Based Systems are highly dynamic software systems composed of several web services. In contrast to other types of systems, Service-Based Systems rely on service providers to ensure that their web services comply with the agreed Quality of Service. Delivering an adequate Quality of Service is a critical and significant challenge that requires monitoring along the different activities in the Service-Based Systems lifecycle. Question/problemCurrent monitoring systems are designed to support specific activities (e.g. service selection, adaptation, etc.), but do not fulfil the requirements of all the activities in the Service-Based Systems lifecycle. Principal ideas/resultsIn this paper, we present SALMon, a QoS monitoring framework able to support the whole Service-Based Systems lifecycle. SALMon is highly versatile, since it combines different strategies for its configuration (model-based and invocation-based) and for the way it gets the Quality of Service (passive monitoring and online testing). Furthermore, its architecture supports easy extensibility with new quality attributes, independence of the technology of the monitored services and interoperability with other tools. We conducted a performance evaluation over real web services using suitable estimators for response time and evaluated both its overhead and capacity. ContributionSALMon provides infrastructure that can be used in very different scenarios, as exemplified in this paper, both in terms of the lifecycles phase addressed and the type of system (pure Service-Oriented Architecture, cloud-based systems, etc.). This diversity of situations addressed makes SALMon a significant contribution both for practitioners that may be interested in integrating a working technology in their software solutions, and for researchers who can conduct their investigation on top of a reliable infrastructure.

The RISCOSS Platform for Risk Management in Open Source Software Adoption

Managing risks related to OSS adoption is a must for organizations that need to smoothly integrate OSS-related practices in their development processes. Adequate tool support may pave the road to effective risk management and ensure the sustainability of such activity. In this paper, we present the RISCOSS platform for managing risks in OSS adoption. RISCOSS builds upon a highly configurable data model that allows customization to several types of scopes. It implements two different working modes: exploration, where the impact of decisions may be assessed before making them; and continuous assessment, where risk variables (and their possible consequences on business goals) are continuously monitored and reported to decision-makers. The blackboard-oriented architecture of the platform defines several interfaces for the identified techniques, allowing new techniques to be plugged in.