End-to-End Quality Provision and SLA Conformance (WP-JRA-1.3)

Objectives

This workpackage aims to achieve the following long-term objectives:

1. Defining novel principles, techniques and methodologies for specifying, negotiating and assuring end-to-end quality and SLA conformance (Service Level Agreement). Those techniques consider quality characteristics (quality dimensions) across the functional layers for service infrastructure, service composition and coordination, and business process management, as well as across the chain of service providers and consumers. Key focus will be on techniques and methods for quality prediction, which support the proactive adaptation of service-based applications.
   
2. Specifying clearly defined interfaces and concerns with respect to end-to-end quality aspects:
3. • Between the functional layers service infrastructure, service composition and coordination, as well as business process management.
   • Between engineering principles and methods (i.e., the engineering framework) as well as monitoring and adaptation principles and methods (i.e., the monitoring and adaptation framework).
4. Shaping the S-Cube convergence knowledge model by providing an integrated set of principles, techniques and methodologies for end-to-end quality assurance and SLA conformance, specifically providing a comprehensive set of quality attributes.

The following short-term objectives are discerned, that collectively provide a basis for realizing the long-term objectives:

1. Defining a comprehensive quality reference model for service-based systems (including quality attributes relevant for service-based applications), SLA constituents with respect to quality as well as HCI and context knowledge relevant for quality and conformance aspects.
2. Explicitly documenting software engineering and SOC knowledge with respect to defining quality characteristics and negotiating SLAs, as well as on quality assurance and SLA conformance (e.g., dynamic testing techniques and formal analysis approaches).
3. Explicitly document software engineering and SOC knowledge on quality assurance and SLA conformance (for instance, dynamic testing techniques and formal analysis approaches).
4. Contributing a quality reference model and knowledge baseline to the S-Cube convergence knowledge model.

Coordination

This workpackage (WP-JRA-1.3) is coordinated by Paluno (The Ruhr Institute for Software Technology), University of Duisburg-Essen.

Results

A list of deliverables of this workpackage can be found here.

A list of S-Cube publications can be accessed here.