That is what most of us believe most of the time. They do happen, of course, sometimes with alarming frequency, sometimes with calamitous results. We explain these unnatural events as the consequences of lack of foresight, poor design, poor engineering andlor errors by some person or persons. Improve the design and production, admonish or train the persons to be more careful (less careless?) and they won't happen. It is easy to think of examples in the home, the laboratory, the office ... and in the public domain -for example, Chernobyl, Challenger, Bhopal, The Herald of Free Enterprise, King's Cross. The premise leads to an explanation of the cause, which in turn leads to the public inquiry recommending some action to prevent a similar accident occumng again. Chernobyl, for example, was blamed on a combination of unsatisfactory design and operator error. So also was the Zeebrugge disaster. So also ... and it is easy to make a long list including Flixborough, Torrey Canyon, Three Mile Island (TMI), to which King's Cross will probably soon be added. In each case the inquiry has prescribed corrective action based on this 'accidents are unnatural' (AAU) model: a technological fix plus wrist-slapping. In well-established technologies, in which we have many thousands or even millions of operating hours of experience. the repeated application of this process should by now have reduced the accident rate to zero -or, at the very least, to very nearly zero. Not a bit of it; there are no signs of this happening, and in some technologies the rate is rising. Could it be that we have got something wrong in our explanation?

Normal accidents. Living with high-risk technologies

The MAPE-K (Monitor-Analyze-Plan-Execute over a shared Knowledge) feedback loop is the most influential reference control model for autonomic and self-adaptive systems. This paper presents a conceptual and methodological framework for formal modeling, validating, and verifying distributed self-adaptive systems. We show how MAPE-K loops for self adaptation can be naturally specified in an abstract stateful language like Abstract State Machines. In particular, we exploit the concept of multi-agent Abstract State Machines to specify decentralized adaptation control by using MAPE computations. We support techniques for validating and verifying adaptation scenarios, and getting feedback of the correctness of the adaptation logic as implemented by the MAPE-K loops. In particular, a verification technique based on meta-properties is proposed to allow discovering unwanted interferences between MAPE-K loops at the early stages of the system design. As a proof-of concepts, we model and analyze a traffic monitoring system.

/pdf/modeling-and-analyzing-mape-k-feedback-loops-for-self-4dkcv6cm51.pdf

Modeling and analyzing MAPE-K feedback loops for self-adaptation

One increasingly important technique for improving system dependability is to provide mechanisms for a system to adapt at run time in order to accommodate varying resources, system errors, and changing requirements For such "self-repairing" systems one of the hard problems is determining when a change is needed, and knowing what kind of adaptation is required In this paper we describe a partial solution in which stylized architectural design models are maintained at run time as a vehicle for automatically monitoring system behavior, for detecting when that behavior falls outside of acceptable ranges, and for deciding on a high-level repair strategy The main innovative feature of the approach is the ability to specialize a generic run time adaptation framework to support particular architectural styles and properties of interest Specifically, a formal description of an architectural style defines for a family of related systems the conditions under which adaptation should be considered, provides an analytic basis for detecting anomalies, and serves as a basis for developing sound repair strategies

Increasing System Dependability through Architecture-Based Self-Repair.

Adaptive systems are characterized by the ability to monitor changes in their volatile world and react to monitored changes when needed. The ultimate goal of adaptation is that users’ requirements are always met correctly and efficiently. Adaptation is traditionally driven by the changing state of the system internal and its surrounding environment. Such state should be monitored and analyzed to decide upon a suitable alternative behaviour to adopt. In this paper, we introduce another driver for adaptation which is the users’ collective judgement on the alternative behaviors of a system. This judgmenet should be infered from the individual users’ feedback given iteratviely during the lifetime of a system. Users’ feedback reflects their main interest which is the validity and the quality of a system behaviour as a means to meet their requirements. We propose social adaptation which is a specific kind of adaptation that treats users’ feedback, obtained during the software lifetime, as a primary driver in planning and guiding adaptation. We propose a novel requirements engineering modelling and analysis approach meant for systems adopting social adaptation. We evaluate our approach by applying it in practice and report on the results.

/pdf/social-adaptation-when-software-gives-users-a-voice-wm53hzj0rx.pdf

Social Adaptation When Software Gives Users a Voice

Many techniques have been developed to enhance learning experience with computer technology. A particularly great influence of technology on learning came with the emergence of the web and adaptive educational hypermedia systems. While the web enables users to interact and collaborate with each other to create, organize, and share knowledge via user-generated content, majority of e-learning systems do not utilize the power of their users to create high quality educational content and provide data for adaptive algorithms. In this paper, we introduce a novel social learning framework that allows anybody to author educational content in a form of mini-lessons, learn lessons by following adaptive learning pathways as well as interact with their peers as in any social network. The proposed approach combines concepts of crowdsourcing, online social networks, and complex adaptive systems to engage users in efficient learning through teaching process. We first describe the main idea behind the framework and how users interact with it, and then we describe SALT system that implements the framework. We also performed evaluation of the SALT system via several classroom studies. Our results show that collective learning experiences can be efficiently utilized in adaptive social learning. We found that students tend to form stable clusters that survive very high similarity threshold. Meanwhile, our learning pathway analysis showed that almost all students have their own unique best pathway. Experiments with various recommendation algorithms showed that most algorithms obtain very small penalty in all classes.

Adaptive Social Learning Based on Crowdsourcing

Software’s ability to adapt at run-time to changing user needs, system intrusions or faults, changing operational environment, and resource variability has been proposed as a means to cope with the complexity of today’s softwareintensive systems. Such self-adaptive systems can conflgure and reconflgure themselves, augment their functionality, continually optimize themselves, protect themselves, and recover themselves, while keeping most of their complexity hidden from the user and administrator. In this paper, we present research road map for software engineering of selfadaptive systems focusing on four views, which we identify as essential: requirements, modelling, engineering, and assurances.

/pdf/software-engineering-for-self-adaptive-systems-a-research-kv7gn3ecka.pdf

Software Engineering for Self-Adaptive Systems: A Research Road Map (Draft Version) ⁄

The CONNECT Integrated Project aims at enabling continuous composition of networked systems to respond to the evolution of functionalities provided to and required from the networked environment. CONNECT aims at dropping the interoperability barrier by adopting a revolutionary approach to the seamless networking of digital systems, that is, synthesizing on-the-fly the connectors via which networked systems communicate. The resulting emergent connectors are effectively synthesized according to the behavioral semantics of application- down to middleware-layer protocols run by the interacting parties. The role of work package WP3 is to devise automated and compositional approaches to connector synthesis, which can be performed at run-time. Given the respective interaction behavior of networked systems, we want to synthesize the behavior of the connector(s) needed for them to interact. These connectors serve as mediators of the networked systems' interaction at both application and middleware layers. During the project's first year, the work of WP3 led us to achieve the following preliminary results: the formalization of matching and mapping relationships for application-layer interaction protocols; the definition of the corresponding mediator generation algorithm; the analysis of the interoperability problems, and related solutions, that can occur at middleware-layer; and a model-driven approach to the automated elicitation of application-layer protocols from software implementations. All these achievements have been reported in Deliverable D3.1: "Modeling of application- and middleware-layer interaction protocols". In this deliverable, we go a step forward with respect to some of the previous achievements by delivering a unified process, and related artefacts, for the automated synthesis of mediators at both application and middleware layers, code-generation techniques to generate the actual code that implements a synthesized mediator, and a preliminary integration of QoS management in the synthesis process. During year 2, all the work has been validated through its application to several scenarios, in particular as part of WP1 and WP6. By selecting one of them as common scenario, in this deliverable, we also show the different methods/techniques at work on the scenario. All the steps of the devised synthesis process are described in detail and applied to the selected common scenario.

https://hal.inria.fr/inria-00584917/document

Reasoning about and Harmonizing the Interaction Behavior of Networked Systems at Application- and Middleware- Layer

The CONNECT Integrated Project aims at enabling continuous composition of networked systems to respond to the evolution of functionalities provided to and required from the networked environment. CONNECT aims at dropping the interoperability barrier by adopting a revolutionary approach to the seamless networking of digital systems, that is, synthesizing on-the-fly the connectors via which networked systems communicate. The resulting emergent connectors are effectively synthesized according to the behavioral semantics of application- down to middleware-layer protocols run by the interacting parties. The role of work package WP3 is to devise automated and compositional approaches to connector synthesis, which can be performed at run-time. Given the respective interaction behavior of networked systems, we want to synthesize the behavior of the connector(s) needed for them to interact. These connectors serve as mediators of the networked systems' interaction at both application and middleware layers. In this deliverable, we set the scene for a formal theory of the automated synthesis of application- and middleware-layer protocol mediators. We formally characterize mediating connectors between mismatching application-layer protocols by rigorously defining the necessary conditions that must hold for protocols to be mediated. The outcome of this formalization is the definition of two relationships between heterogenous protocols: matching and mapping. The former is concerned with checking whether a mediator letting two protocols interoperate exists or not. The latter concerns the algorithm that should be executed to synthesize the required mediator. Furthermore, we analyze the different dimensions of interoperability at the middleware layer and exploit this analysis to formalize existing solutions to middleware-layer interoperability. Since the work on application-layer mediator synthesis is based on the assumption that a model of the interaction protocol for a networked system is dynamically discovered, we finally present an approach, based on data-flow analysis and testing, for the automated elicitation of application-layer protocols from software implementations. This approach presents similarities, but also several differences, with the work of work package WP4 (protocol learning). Furthermore, it allowed us to proceed in parallel with the work of WP4 and to state the requirements that the learning approaches have to satisfy to enable mediator synthesis. For this reason, we keep this work separate from the work on protocol learning and discuss it in this deliverable. All the approaches mentioned above are applied to several examples and scenarios.

https://hal.inria.fr/inria-00464661/document

Modeling of application- and middleware-layer interaction protocols

The D1.1 deliverable clarifies baseline, progress, and state of the art that CHOReOS will address. For each of the first four CHOReOS work packages, WP1 to WP4, this deliverable gives a precise definition of the state of the art, an indication of the envisaged progress beyond the state of the art by CHOReOS and the baseline for its research.

https://hal.inria.fr/hal-00662510/document

CHOReOS State of the Art, Baseline, and Beyond (D1.1)

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Software Engineering for Self-Adaptive Systems: A Research Road Map (Draft Version) ⁄

Reasoning about and Harmonizing the Interaction Behavior of Networked Systems at Application- and Middleware- Layer

Modeling of application- and middleware-layer interaction protocols

CHOReOS State of the Art, Baseline, and Beyond (D1.1)