Run-time model evaluation for requirements model-driven self-adaptation

A self-adaptive system adjusts its configuration to tolerate changes in its operating environment. To date, requirements modeling methodologies for self-adaptive systems have necessitated analysis of all potential system configurations, and the circumstances under which each is to be adopted. We argue that, by explicitly capturing and modelling uncertainty in the operating environment, and by verifying and analysing this model at runtime, it is possible for a system to adapt to tolerate some conditions that were not fully considered at design time. We showcase in this paper our tools and research results

Tracing Requirements for Adaptive Systems using Claims *

ABSTRACT The complexity of environments faced by dynamically adaptive systems (DAS) means that the RE process will often be iterative with analysts revisiting the system specifications based on new environmental understanding product of experiences with experimental deployments, or even after final deployments. An ability to trace backwards to an identified environmental assumption, and to trace forwards to find the areas of a DAS's specification that are affected by changes in environmental understanding aids in supporting this necessarily iterative RE process. This paper demonstrates how claims can be used as markers for areas of uncertainty in a DAS specification. The paper demonstrates backward tracing using claims to identify faulty environmental understanding, and forward tracing to allow generation of new behaviour in the form of policy adaptations and models for transitioning the running system

Design and run-time requirements modelling for adaptive systems

This thesis explores the construction, enrichment and use of requirements models for adaptive systems. This thesis proposes the enrichment of adaptive systems' requirements models with additional tracing information, preserving the rationale behind configuration decisions. The preserved rationale can be utilised at design time, allowing decisions to be re-taken in the context of new or changed information and allowing for the identification of areas of uncertainty in understanding. The preserved rationale can also be used by a system itself, at run time, allowing it to adapt its behaviour to contexts not fully envisaged at design time. This thesis presents the ReAssuRE modelling process, which defines modelling perspectives from which some classes of adaptive system may be viewed. ReAssuRE models embed the described tracing information, and may be interpreted and reasoned with by a suitably constructed system at run time. This thesis presents tool support, allowing adaptive behaviour to be derived directly from ReAssuRE models. Finally, this thesis presents proof of concept components that allow a system to reason with ReAssuRE models, transforming them in response to monitored data, and derive new adaptive behaviour.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Managing Testing Complexity in Dynamically Adaptive Systems: A Model-Driven Approach

Autonomous systems are increasingly conceived as a means to allow operation in changeable or poorly understood environments. However, granting a system autonomy over its operation removes the ability of the developer to be completely sure of the system's behaviour under all operating contexts. This combination of environmental and behavioural uncertainty makes the achievement of assurance through testing very problematic. This paper focuses on a class of system, called an m-DAS, that uses run-time models to drive run-time adaptations in changing environmental conditions. We propose a testing approach which is itself model-driven, using model analysis to significantly reduce the set of test cases needed to test for emergent behaviour. Limited testing resources may therefore be prioritised for the most likely scenarios in which emergent behaviour may be observed

Managing testing complexity in dynamically adaptive systems: a model-driven approach

Abstract-Autonomous systems are increasingly conceived as a means to allow operation in changeable or poorly understood environments. However, granting a system autonomy over its operation removes the ability of the developer to be completely sure of the system's behaviour under all operating contexts. This combination of environmental and behavioural uncertainty makes the achievement of assurance through testing very problematic. This paper focuses on a class of system, called an m-DAS, that uses run-time models to drive run-time adaptations in changing environmental conditions. We propose a testing approach which is itself model-driven, using model analysis to significantly reduce the set of test cases needed to test for emergent behaviour. Limited testing resources may therefore be prioritised for the most likely scenarios in which emergent behaviour may be observed

Requirements tracing to support change in dynamically adaptive systems

[Context and motivation] All systems are susceptible to the need for change, with the desire to operate in changeable environments driving the need for software adaptation. A Dynamically Adaptive System (DAS) adjusts its behaviour autonomously at runtime in order to accommodate changes in its operating environment, which are anticipated in the system’s requirements specification. [Question/Problem] In this paper, we argue that Dynamic Adaptive Systems’ requirements specifications are more susceptible to change than those of traditional static systems. We propose an extension to i* strategic rationale models to aid in changing a DAS. [Principal Ideas/Results] By selecting some of the types of tracing proposed for the most complex systems and supporting them for DAS modelling, it becomes possible to handle change to a DAS’ requirements efficiently, whilst still allowing artefacts to be stored in a Requirements Management tool to mitigate additional complexity. [Contribution] The paper identifies different classes of change that a DAS’ requirements may be subjected to, and illustrates with a case study how additional tracing information can support the making of each class of change

When to Adapt? Identification of Problem Domains for Adaptive Systems

Dynamically adaptive systems (DASs) change behaviour at run-time to operate in volatile environments. As we learn how best to design and build systems with greater autonomy, we must also consider when to do so. Thus far, DASs have tended to showcase the benefits of adaptation infrastructures with little understanding of what characterizes the problem domains that require run-time adaptation. This position paper posits that context-dependent variation in the acceptable trade-offs between non-functional requirements is a key indicator of problems that require dynamically adaptive solutions

Towards requirements aware systems: Run-time resolution of design-time assumptions

In earlier work we proposed the idea of requirements-aware systems that could introspect about the extent to which their goals were being satisfied at runtime. When combined with requirements monitoring and self adaptive capabilities, requirements awareness should help optimize goal satisfaction even in the presence of changing run-time context. In this paper we describe initial progress towards the realization of requirements-aware systems with REAssuRE. REAssuRE focuses on explicit representation of assumptions made at design time. When such assumptions are shown not to hold, REAssuRE can trigger system adaptations to alternative goal realization strategies

Tracing Requirements for Adaptive Systems using Claims ∗

The complexity of environments faced by dynamically adaptive systems (DAS) means that the RE process will often be iterative with analysts revisiting the system specifications based on new environmental understanding product of experiences with experimental deployments, or even after final deployments. An ability to trace backwards to an identified environmental assumption, and to trace forwards to find the areas of a DAS’s specification that are affected by changes in environmental understanding aids in supporting this necessarily iterative RE process. This paper demonstrates how claims can be used as markers for areas of uncertainty in a DAS specification. The paper demonstrates backward tracing using claims to identify faulty environmental understanding, and forward tracing to allow generation of new behaviour in the form of policy adaptations and models for transitioning the running system. Categories and Subject Descriptors D.2.1 [Software Engineering]: Requirements/Specifications