GESTÃO DO CONHECIMENTO: UM ESTUDO SOBRE A RELAÇÃO ENTRE A LIDERANÇA TRANSFORMACIONAL, A CONVERSÃO DO CONHECIMENTO E A EFICÁCIA ORGANIZACIONAL

Este estudo teve como objetivo principal analisar a relação entre a Liderança Transformacional, a Conversão do Conhecimento e a Eficácia Organizacional. Foram considerados como pressupostos teóricos conceitos consolidados sobre os temas desta relação, além de recentes pesquisas já realizadas em outros países e contextos organizacionais. Com base nisto identificou-se potencial estudo de um modelo que relacionasse estes três conceitos. Para tal considera-se que as organizações que buscam atingir Vantagem Competitiva e incorporam a Knowledge-Based View possam conquistar diferenciação frente a seus concorrentes. Nesse contexto o conhecimento ganha maior destaque e papel protagonista nestas organizações. Dessa forma criar conhecimento através de seus colaboradores, passa a ser um dos desafios dessas organizações ao passo que sugere melhoria de seus indicadores Econômicos, Sociais, Sistêmicos e Políticos, o que se define por Eficácia Organizacional. Portanto os modos de conversão do conhecimento nas organizações, demonstram relevância, uma vez que se cria e se converte conhecimentos através da interação entre o conhecimento existente de seus colaboradores. Essa conversão do conhecimento ou modelo SECI possui quatro modos que são a Socialização, Externalização, Combinação e Internalização. Nessa perspectiva a liderança nas organizações apresenta-se como um elemento capaz de influenciar seus colaboradores, propiciando maior dinâmica ao modelo SECI de conversão do conhecimento. Se identifica então na liderança do tipo Transformacional, características que possam influenciar colaboradores e entende-se que esta relação entre a Liderança Transformacional e a Conversão do Conhecimento possa ter influência positiva nos indicadores da Eficácia Organizacional. Dessa forma esta pesquisa buscou analisar um modelo que explorasse essa relação entre a liderança do tipo Transformacional, a Conversão do Conhecimento (SECI) e a Eficácia Organizacional. Esta pesquisa teve o caráter quantitativo com coleta de dados através do método survey, obtendo um total de 230 respondentes válidos de diferentes organizações. O instrumento de coleta de dados foi composto por afirmativas relativas ao modelo de relação pesquisado com um total de 44 itens. O perfil de respondentes concentrou-se entre 30 e 39 anos de idade, com a predominância de organizações privadas e de departamentos de TI/Telecom, Docência e Recursos Humanos respectivamente. O tratamento dos dados foi através da Análise Fatorial Exploratória e Modelagem de Equações Estruturais via Partial Least Square Path Modeling (PLS-PM). Como resultado da análise desta pesquisa, as hipóteses puderam ser confirmadas, concluindo que a Liderança Transformacional apresenta influência positiva nos modos de Conversão do Conhecimento e que; a Conversão do Conhecimento influencia positivamente na Eficácia Organizacional. Ainda, concluiu-se que a percepção entre os respondentes não apresenta resultado diferente sobre o modelo desta pesquisa entre quem possui ou não função de liderança.

Advanced data driven visualisation for geo-spatial data

Most current 3D landscape visualisation systems either use bespoke hardware solutions, or offer a limited amount of interaction and detail when used in realtime mode. We are developing a modular, data driven 3D visualisation system that can be readily customised to specific requirements. By utilising the latest software engineering methods and bringing a dynamic data driven approach to geo-spatial data visualisation we will deliver an unparalleled level of customisation in near-photo realistic, realtime 3D landscape visualisation. In this paper we show the system framework and describe how this employs data driven techniques. In particular we discuss how data driven approaches are applied to the spatiotemporal management aspect of the application framework, and describe the advantages these convey.

Using quantitative analysis to implement autonomic IT systems

The software underpinning today’s IT systems needs to adapt dynamically and predictably to rapid changes in system workload, environment and objectives. We describe a software framework that achieves such adaptiveness for IT systems whose components can be modelled as Markov chains. The framework comprises (i) an autonomic architecture that uses Markov-chain quantitative analysis to dynamically adjust the parameters of an IT system in line with its state, environment and objectives; and (ii) a method for developing instances of this architecture for real-world systems. Two case studies are presented that use the framework successfully for the dynamic power management of disk drives, and for the adaptive management of cluster availability within data centres, respectively.

CADS*: Computer-Aided Development of self-* systems

We present the prototype tool CADS* for the computer-aided development of an important class of self-* systems, namely systems whose components can be modelled as Markov chains. Given a Markov chain representation of the IT components to be included into a self-* system, CADS* automates or aids (a) the development of the artifacts necessary to build the self-* system; and (b) their integration into a fully-operational self-* solution. This is achieved through a combination of formal software development techniques including model transformation, model-driven code generation and dynamic software reconfiguration.

Towards a generic autonomic architecture for legacy resource management

Half a decade has passed since the objectives and benefits of autonomic computing were stated, yet even the latest system designs and deployments exhibit only limited and isolated elements of autonomic functionality. From an autonomic computing standpoint, all computing systems – old, new or under development – are legacy systems, and will continue to be so for some time to come. In this paper, we propose a generic architecture for developing fully-fledged autonomic systems out of legacy, non-autonomic components, and we investigate how existing technologies can be used to implement this architecture.

The transformational implementation of JSD process specifications via finite automata representation

Conventional structured methods of software engineering are often based on the use of functional decomposition coupled with the Waterfall development process model. This approach is argued to be inadequate for coping with the evolutionary nature of large software systems. Alternative development paradigms, including the operational paradigm and the transformational paradigm, have been proposed to address the inadequacies of this conventional view of software developement, and these are reviewed. JSD is presented as an example of an operational approach to software engineering, and is contrasted with other well documented examples. The thesis shows how aspects of JSD can be characterised with reference to formal language theory and automata theory. In particular, it is noted that Jackson structure diagrams are equivalent to regular expressions and can be thought of as specifying corresponding finite automata. The thesis discusses the automatic transformation of structure diagrams into finite automata using an algorithm adapted from compiler theory, and then extends the technique to deal with areas of JSD which are not strictly formalisable in terms of regular languages. In particular, an elegant and novel method for dealing with so called recognition (or parsing) difficulties is described,. Various applications of the extended technique are described. They include a new method of automatically implementing the dismemberment transformation; an efficient way of implementing inversion in languages lacking a goto-statement; and a new in-the-large implementation strategy.

Dynamic QoS management and optimisation in service-based systems

Service-based systems that are dynamically composed at run time to provide complex, adaptive functionality are currently one of the main development paradigms in software engineering. However, the Quality of Service (QoS) delivered by these systems remains an important concern, and needs to be managed in an equally adaptive and predictable way. To address this need, we introduce a novel, tool-supported framework for the development of adaptive service-based systems called QoSMOS (QoS Management and Optimisation of Service-based systems). QoSMOS can be used to develop service-based systems that achieve their QoS requirements through dynamically adapting to changes in the system state, environment and workload. QoSMOS service-based systems translate high-level QoS requirements specified by their administrators into probabilistic temporal logic formulae, which are then formally and automatically analysed to identify and enforce optimal system configurations. The QoSMOS self-adaptation mechanism can handle reliability- and performance-related QoS requirements, and can be integrated into newly developed solutions or legacy systems. The effectiveness and scalability of the approach are validated using simulations and a set of experiments based on an implementation of an adaptive service-based system for remote medical assistance.

A semantic web environment for component model

Component-based development (CBD) has become an important emerging topic in the software engineering field. It promises long-sought-after benefits such as increased software reuse, reduced development time to market and, hence, reduced software production cost. Despite the huge potential, the lack of reasoning support and development environment of component modeling and verification may hinder its development. Methods and tools that can support component model analysis are highly appreciated by industry. Such a tool support should be fully automated as well as efficient. At the same time, the reasoning tool should scale up well as it may need to handle hundreds or even thousands of components that a modern software system may have. Furthermore, a distributed environment that can effectively manage and compose components is also desirable. In this paper, we present an approach to the modeling and verification of a newly proposed component model using Semantic Web languages and their reasoning tools. We use the Web Ontology Language and the Semantic Web Rule Language to precisely capture the inter-relationships and constraints among the entities in a component model. Semantic Web reasoning tools are deployed to perform automated analysis support of the component models. Moreover, we also proposed a service-oriented architecture (SOA)-based semantic web environment for CBD. The adoption of Semantic Web services and SOA make our component environment more reusable, scalable, dynamic and adaptive.

Minimizing nasty surprises with better informed decision-making in self-adaptive systems

Designers of self-adaptive systems often formulate adaptive design decisions, making unrealistic or myopic assumptions about the system's requirements and environment. The decisions taken during this formulation are crucial for satisfying requirements. In environments which are characterized by uncertainty and dynamism, deviation from these assumptions is the norm and may trigger 'surprises'. Our method allows designers to make explicit links between the possible emergence of surprises, risks and design trade-offs. The method can be used to explore the design decisions for self-adaptive systems and choose among decisions that better fulfil (or rather partially fulfil) non-functional requirements and address their trade-offs. The analysis can also provide designers with valuable input for refining the adaptation decisions to balance, for example, resilience (i.e. Satisfiability of non-functional requirements and their trade-offs) and stability (i.e. Minimizing the frequency of adaptation). The objective is to provide designers of self adaptive systems with a basis for multi-dimensional what-if analysis to revise and improve the understanding of the environment and its effect on non-functional requirements and thereafter decision-making. We have applied the method to a wireless sensor network for flood prediction. The application shows that the method gives rise to questions that were not explicitly asked before at design-time and assists designers in the process of risk-aware, what-if and trade-off analysis.

Evolution of competing strategies in a threshold model for task allocation

A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task allocation in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. The problem is constrained so that agents are penalised for switching mail types. When an agent process a mail batch of different type to the previous one, it must undergo a change-over, with repeated change-overs rendering the agent inactive. The efficiency (average amount of mail retrieved), and the flexibility (ability of the agents to react to changes in the environment) are investigated both in static and dynamic environments and with respect to sudden changes. New rules for mail selection and specialisation are proposed and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a evolutionary algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation.

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.

Requirements reflection:requirements as runtime entities

Computational reflection is a well-established technique that gives a program the ability to dynamically observe and possibly modify its behaviour. To date, however, reflection is mainly applied either to the software architecture or its implementation. We know of no approach that fully supports requirements reflection- that is, making requirements available as runtime objects. Although there is a body of literature on requirements monitoring, such work typically generates runtime artefacts from requirements and so the requirements themselves are not directly accessible at runtime. In this paper, we define requirements reflection and a set of research challenges. Requirements reflection is important because software systems of the future will be self-managing and will need to adapt continuously to changing environmental conditions. We argue requirements reflection can support such self-adaptive systems by making requirements first-class runtime entities, thus endowing software systems with the ability to reason about, understand, explain and modify requirements at runtime. © 2010 ACM.

Summary of the 6th international workshop on models@run.time

The 6th edition of the workshop Models@run.time was held at the 14th International Conference MODELS. The workshop took place in the city of Wellington, New Zealand, on the 17th of October 2011. The workshop was organised by Nelly Bencomo, Gordon Blair, Robert France, Betty H.C. Cheng, and Cédric Jeanneret. We present a summary of the workshop and a synopsis of the papers presented during the workshop. © 2012 Springer-Verlag Berlin Heidelberg.

Second international workshop on models@run.time

The second edition of the workshop Models@run.time was co-located with the ACM/IEEE 10th International Conference on Model Driven Engineering Languages and Systems. The workshop took place in the lively city of Nashville, USA, on the 2nd of October, 2007. The workshop was organised by Nelly Bencomo, Robert France, and Gordon Blair and was attended by at least 25 people from 7 countries. This summary gives an overview of the presentations and lively discussions that took place during the workshop. © 2008 Springer-Verlag Berlin Heidelberg.

Summary of the 5th international workshop on models@run.time

The 5th edition of the workshop Models@run.time was held at the 13th International Conference MODELS. The workshop took place in the exciting city of Oslo, Norway, on the 5th of October 2010. The workshop was organised by Nelly Bencomo, Gordon Blair, Franck Fleurey, and Cédric Jeanneret. It was attended by at least 33 people from more than 11 countries. In this summary we present a synopsis of the presentations and discussions that took place during the workshop. © 2011 Springer-Verlag Berlin Heidelberg.