The 8th edition of the workshop Models@run.time was held at the 16th International Conference MODELS. The workshop took place in the city of Miami, USA, on the 29th of September 2013. The workshop was organised by Nelly Bencomo, Sebastian Götz, Robert France and Bernhard Rumpe. Here, we present a summary of the workshop and a synopsis of the papers discussed during the workshop

Bencomo, Nelly

France, Robert

Götz, Sebastian

Rumpe, Bernhard

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Summary of the 8th International Workshop onModels@run.timeNelly Bencomo1, Robert France2, Sebastian Götz3, and Bernhard Rumpe41 Aston University, UK2 Colorado State University, USA3 Technische Universität Dresden, Germany4 RWTH Aachen, Germanynelly@acm.org,sebastian.goetz@acm.org,france@cs.colostate.edu,rumpe@se-rwth.deAbstract. The 8th edition of the workshop Models@run.time was heldat the 16th International Conference MODELS. The workshop took placein the city of Miami, USA, on the 29th of September 2013. The workshopwas organised by Nelly Bencomo, Sebastian Götz, Robert France andBernhard Rumpe. Here, we present a summary of the workshop and asynopsis of the papers discussed during the workshop.Keywords: runtime adaptation, MDE, reﬂection, run-time abstractions1 IntroductionThe Models@run.time workshop series provides a forum for exchange of ideas onthe use of run-time models. The main goal is to further promote cross-fertilizationbetween researchers from diﬀerent communities, including model-driven softwareengineering, software architectures, computational reﬂection, adaptive systems,autonomic and self-healing systems, and requirements engineering. This editionof the workshop successfully brought together at least twenty ﬁve researchersfrom diﬀerent communities.This edition had nine (9) papers presented. Improved versions of these papersare published in this post-workshop proceedings.2 Workshop Format and Session SummariesThe workshop was held as a one-day workshop in MODELS. The activities werestructured into presentations followed by an afternoon discussion session.Nine (9) papers were presented. In total, seven (7) long presentations andtwo (2) short presentations were given. Authors of the papers with long pre-sentations discussed their papers in a twenty-minute-time slot, and ﬁve minuteswere allowed for questions and discussion. Shorter presentations, in turn, hadﬁfteen (15) minutes.2In the second part of the afternoon, the workshop participants dedicatedtheir time for discussions where a useful classiﬁcation of presented and discussedapproaches was deﬁned. In the following we summarize the nine (9) paper pre-sentations given in three sessions:Session 1: Safety and Cyber Physical SystemsEnhancing Root Cause Analysis with Runtime Models and Interactive Visual-izations by Michael Szvetits and Uwe Zdun. In this paper the authors proposethe use of runtime models in combination with interactive visualizations to easetracing between log ﬁle entries and corresponding software artefacts. The con-tribution of this paper is a repository-based approach to augment root causeanalysis (of unwanted behaviour for example) with interactive tracing viewswhile maximizing reusability of models created during the software developmentprocess.Building heterogeneous models at runtime to detect faults in ambient-intelligentenvironments by Christophe Jacquet, Ahmed Mohamed, Frédéric Boulanger, Ce-cile Hardebolle and Yacine Bellik. This paper introduces an approach for faultdetection in ambient-intelligent environments. It proposes to compute predic-tions for sensor values, to be compared with actual values. As ambient envi-ronments are highly dynamic, one cannot pre-determine a prediction method.Therefore, our approach relies on (a) the modeling of sensors, actuators andphysical eﬀects that link them, and (b) the automatic construction at run-timeof a heterogeneous prediction model. The prediction model can then be executedon a heterogeneous modeling platform such as ModHel'X, which yields predictedsensor values.A Model-driven Approach to Develop and Manage Cyber-Physical Systems byAdalberto Sampaio Jr., Fabio Costa and Peter Clarke. Cyber-Physical Systems(CPS) integrate computing, networking, and physical processes to digitally exe-cute tasks on or using the physical elements of a system. Power microgrids are aparticular kind of CPS that enables management and autonomic control of localsmart grids, aiming at reliability, fault tolerance and energy eﬃciency, amongother goals. Thw paper explores a new approach based on MDE that uses modelsat runtime techniques to manage and control microgrids. The approach employsa model execution engine that manages a causally connected runtime model ofthe microgrid and interprets user-deﬁned models in order to generate controls forthe microgrid elements. The authors demonstrate the approach by building thelower layer of the model execution engine. Furthermore, they explored a model-driven technique to build the execution engine and use the resulting experienceto argue that the approach can be extended to other kinds of cyber-physicalsystems.3Session 2: Enterprise and CloudA Tool for Collaborative Evolution of Enterprise Architecture Models at Runtimeby Sascha Roth, Matheus Hauder and Florian Matthes. In this paper, the au-thors propose a solution that empowers stakeholders to reveal their informationdemand collaboratively to facilitate Enterprise Architecture (EA) models thatevolve with changing information demands at runtime. They present core con-cepts of our approach and insights of an implementation thereof as foundationto achieve our long-term goal of evolving EA models. In their implementationwe extend a collaboration platform with capabilities to monitor the actual in-formation demand and to maintain the EA model referring to this demand atruntime.Towards Business Process Models at Runtime by Thomas Johanndeiter, AnatGoldstein and Ulrich Frank. Business Process Management (BPM) suﬀers frominadequate con-cepts and tools for monitoring and evaluation of process execu-tions at runtime. Conversely, models at runtime promise to give insights into thestate of a soft-ware system using the abstract and concrete appearance of de-sign time process models. Therefore, the authors at ﬁrst advocate to use modelsat runtime in business process (BP) modeling. Then, we outline the implemen-tation of a prototypical modeling framework for BP runtime models based onmetaprogramming. This framework supports the integration of BP type mod-els - models that are en-hanced with statistics of runtime data - and instancemodels - visual representa-tions of executed BPs - resulting in versatile processmonitoring dashboards. The approach is superior to object-oriented program-ming, as it provides a common representation for models and code at variouslevels of classiﬁcation, and represents an attractive alternative to object-orientedlanguages for the im-plementation of runtime models in general.Models@Runtime to Support the Iterative and Continuous Design of AutonomicReasoners by Franck Chauvel, Nicolas Ferry and Brice Morin. Modern soft-ware systems evolve in a highly dynamic and open environment, where theirsupporting platforms and infrastructures can change on demand. Designing andoperating holistic controllers able to leverage the adaptation capabilities of thecomplete software stack is a complex task, as it is no longer possible to foresee allpossible environment states and system conﬁgurations that would properly com-pensate for them. The paper presents our experience in using models@runtimeto foster the systematic design and evaluation of self-adaptive systems, by en-abling the coevolution of the reasoning engine and its environment. The researchwas carried out in the context of the Diversify project, which explores how bio-diversity can be used to enhanced the design of self-adaptive mechanisms.Session 3: Model Extraction and ConﬁgurationExploring the use of metaheuristic search to infer models of dynamic systembehaviour by James Williams, Simon Poulding, Richard Paige and Fiona Po-lack. As software systems become more pervasive and increase in both size and4complexity, the requirement for systems to be able to self- adapt to changingenvironments becomes more important. The paper describes a model-based ap-proach for adapting to dynamic runtime environments using metaheuristic op-timisation techniques. The metaheuristics exploit metamodels that capture theimportant components in the adaptation process. Firstly, a model of the envi-ronment's behaviour is extracted using a combination of inference and search.The model of the environment is then used in the discovery of a model of op-timal system behaviour i.e. how the system should best behave in response tothe environment. The system is then updated based on this model. The paperfocuses on investigating the extraction of a behaviour model of the environmentand describes how our previous work can be utilised for the adaptation stage.The authors contextualise the approach using an example and analyse diﬀerentways of applying the metaheuristic algorithms for discovering an optimal modelof the case study's environment.Simon Spinner, Samuel Kounev, Xiaoyun Zhu and Mustafa Uysal. Towards On-line Performance Model Extraction in Virtualized Environments. Virtualizationincreases the complexity and dynamics of modern software architectures mak-ing it a major challenge to manage the end-to-end performance of applications.Architecture-level performance models can help here as they provide the model-ing power and analysis exibility to predict the performance behavior of applica-tions under varying workloads and conﬁgurations. However, the construction ofsuch models is a complex and time-consuming task. In this position paper, theauthors discuss how the existing concept of virtual appliances can be extended toautomate the extraction of architecture-level performance models during systemoperation.Yihan Wu, Ying Zhang, Yingfei Xiong, Xiaodong Zhang and Gang Huang. To-wards RSA-based HA conﬁguration in Cloud. High availability (HA) is a crucialconcern in cloud systems. However, guaranteeing HA is challenging because ofthe complex runtime cloud environment, large number of HA mechanisms avail-able, error-prone HA conﬁguration, and ever-needed dynamic adjustment. Inthis study, the authors leverage runtime system architecture (RSA) for auto-matic conﬁguration of HA in a cloud. With a causal connection between RSAand its corresponding cloud system, our approach has the following advantages.1) The runtime changes of the system are abstracted, collected, and reﬂected onthe RSA continuously, simplifying HA information collection. 2) With a model-based HA analyzer working on the collected HA-related information, an ap-propriate HA style (HAS) can be automatically selected for application to thecurrent system. 3) Changing a HAS on RSA at runtime changes the system HAmechanism, which is suitable for the complex and ever-changing cloud environ-ment. They implemented a prototype of our approach and evaluated it using ourmodel-driven Yan-cloud platform.The presentations and slides associated with discussions are in the web pagesof the workshop.53 Discussion and Classiﬁcation of Presented andDiscussed ApproachesAt the end of the third session discussion topics were identiﬁed. All participantsagreed on aiming for a classiﬁcation of the approaches presented at the workshopusing the following ﬁve dimensions:1. Runtime Model: What is the runtime model in the approach ?2. Purpose: What is its purpose?3. User: Who is using it?4. Properties: What are its properties?5. Reﬂection: Is the runtime model used for reﬂection?Eight (8) approaches were classiﬁed according to these dimensions. The ap-proaches discussed were approaches developed by people who were in the dis-cussions and were not necessarily related to the papers presented earlier duringthis workshop but certainly use runtime models.In order to do the classiﬁcation, the eight approaches were explained to therest of the audience by at least one person. Then, the approaches were assignedto two (2) types based on this classiﬁcation: (1) model-code synchronization and(2) self-adaptive systems / system conﬁguration, where the second type can befurther split by the applied domain into (2a) general purpose and (2b) cloud. Ofcourse, further domains exist, e.g., mobile devices and cyber-physical systems,but approaches of these domains were not been discussed at the workshop. Theresults of the discussions can be summarized as follows:(1) Approaches on Model-Code SynchronizationMichael Szvetits (University of Applied Sciences Wiener Neustadt) Interactive VisualizationRuntime Model: Class and sequence diagrams (design time).Purpose: Extraction of information from the running system.User: Developers use models to understand the design andthe running system.Properties: Descriptive; there are trace links between model ele-ments and runtime elements.Reﬂection: Is used to determine relevant information.Mohammed Al-Refai (Colorado State University, USA)  Fine-grained Adaptation Framework (FiGA) [1] (not discussed as a paper inthis workshop)Runtime Model: Class, sequence and activity diagrams.Purpose: Enables developers to change the system at runtimeby applying changes to the runtime models.User: Developers.Properties: Visual (representation of source code), abstract, notexecutable, descriptive.Reﬂection: Yes. Causal connection between models and code.6(2a) General Purpose Self-adaptive SystemsSimon Spinner (KIT, Germany)  Descartes Meta-ModelRuntime Model: Architectural performance models, behavior mod-els describing how the system utilizes resources andadaptation models describing the adaptation processand what can be adapted.Purpose: Optimization of ressource allocation to meet perfor-mance objectives.User: Autonomous systems, i.e., the system is the user.Properties: Self-reﬂective, self-predictive, course-grained (i.e., ar-chitectural), interpretative.Reﬂection: Yes. Causal connection between model and system.Sebastian Götz (Technische Universität Dresden)  Multi-QualityAuto-Tuning [2] (not discussed as a paper in this workshop)Runtime Model: Architecture of soft- and hardware, behavioral mod-els to predict non- functional properties, Quality-of-Service contracts covering non- functional behaviorof implementations and a model reﬂecting the cur-rent state of the overall system.Purpose: Optimal conﬁguration meeting multiple objectivesconcurrently.User: End-user or system are the user.Properties: descriptive, self-reﬂective, self-predictive, interpreta-tive, heterogeneous.Reﬂection: Yes. Causal connection between model and runningsystem.Nelly Bencomo (Aston University, UK)  Runtime Goal-based mod-els for requirements-aware systems [3] (not discussed as a paper in thisworkshop)Runtime Model: Requirement and goal models.Purpose: Self-adaptive system, thus, conﬁguration.User: End-user or system itseldcan be user.Properties: DescriptiveReﬂection: Top-down, but not bottom-up.(2b) Self-adaptive Systems in Cloud EnvironmentsNicolas Ferry (SINTEF, Norway)  CloudMLRuntime Model: Model describing the distribution of components ina cloud environment.Purpose: Service Provisioning, Optimal Deployment meetingobjectives.User: End-user or system can be the user (also simultane-ously).Properties: Descriptive, can be simulated, i.e., interpretable.Reﬂection: Yes. Causal connection between model and system.7Xiadong Zhang (Peking University)  SM@RTRuntime Model: Architecture model of a cloud environment.Purpose: Optimal conﬁguration meeting cost minimization ob-jective.User: Enterprises (i.e., management staﬀ) and administra-tors.Properties: heterogeneous, descriptive.Reﬂection: Yes. Causal connection between model and system.Interestingly, all participants could immediately classify their approach byanswering the ﬁve questions. Thus, for future work, we plan to do a broaderdiscussion to collect more approaches based on models at runtime and, in con-sequence, identify more types of approaches.The classiﬁcation shown above for the presented approaches can certainly beapplied to other approaches. The classiﬁcation shows that "models@runtime"has evolved as a paradigm covering new types of dynamic systems (like theCPSs described above) and enables a structured investigation of domains likesafety (by separation of concerns due to models). Note that during the editionof the workshop last year, models@runtime has been discussed much more fun-damentally (e.g., executable models vs. runtime models). This year we saw theapplication of the paradigm to various domains. A more extensive application ofthis classiﬁcation can certainly be useful as a way to evaluate and compare theapproaches developed based on the use of runtime models so far.4 Final RemarksA general wrap-up discussion was held at the very end of the afternoon. Theworkshop was closed with a friendly thank you from the organizers to all par-ticipants for a fruitful workshop. After the workshop, the organizers used thefeedback from attendees and PC members to conclude that there is still need forthe discussions in this workshop for next yeareven after eight years. However,we are planning a new approach for next year while doing the call for papers. Itwas concluded that the research topic of the workshop has got a certain level ofmaturity. Several approaches exist and have been applied along all these yearsand certainly the workshop should take those facts into account.AcknowledgementsWe would also like to thank the members of the program committee who acted asanonymous reviewers and provided valuable feedback to the authors: ChristophBockisch, Walter Cazzola, Lars Grunske, Martin Gogolla, Bradley Schmerl, HuiSong, Matthias Tichy, Franck Chauvel, Peter J. Clarke, Fabio Costa, HolgerGiese, Gang Huang, Jean-Marc Jezequel, Rui Silva Moreira, Brice Morin, HausiMüller, Arnor Solberg, Mario Trapp and Thaís Vasconcelos Batista.8References1. Cazzola, W., Rossini, N.A., Al-Refai, M., France, R.: Fine-grained software evolutionusing uml activity and class models. In: To be published in Proceedings of the 16thACM/IEEE International Conference on Model Driven Engineering Languages andSystems, Springer (2013)2. Götz, S., Wilke, C., Cech, S., Aßmann, U.: Architecture and Mechanisms for EnergyAuto Tuning. In: Sustainable ICTs and Management Systems for Green Computing.IGI Global (June 2012) 45733. Bencomo, N., Whittle, J., Sawyer, P., Finkelstein, A., Letier, E.: Requirements re-ﬂection: Requirements as runtime entities. In: Proceedings of the 32nd ACM/IEEEInternational Conference on Software Engineering, Cape Town, South Africa, ACM(May 2010) 199202

Summary of the 8th International workshop on Models@run.time

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Summary of the 8th International Workshop on Models@run.time

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