Reuse is not a new concept in software engineering. Ideas, abstractions, and processes have been reused by programmers since the very early days of software development. In the beginning, since storage media was very expensive, software reuse was basically to serve computers and their mechanical resources, as it substantially conserved memory. When the limitations on physical resources started to diminish, software engineers began to invent reuse approaches to save human resources as well. In addition, as the size and complexity of software systems constantly grow, organized and systematic reuse becomes essential in order to develop those systems in timely and cost-effective fashion. That is one main reason why new technologies and approaches for building software systems, such as object-oriented and component-based development, emerged in the last two or three decades. The focus of this thesis is on software components as building blocks of today's software systems. We consider components as software black boxes whose specification and external behavior are known. We assume that this information can somehow be extracted for each deployed software component. The first and basic assumption then would be the availability of a searchable repository of software components and their external behavioral specifications. Web services are a good example of such components. The most important advantage of software components is that they can be reused repeatedly in building different software systems. Reuse presents challenging problems, one of which is studied in this thesis. This problem, the composition problem, simply is creating a composite component from a collection of available components that, by interacting with each other, provide a requested functionality. When there are a large number of components available to be reused, finding a solution to the composition problem manually would require a considerable time and human effort. This could make the search practically impossible or unwieldy. However, performing the search automatically would save a significant amount of development time, cost and human effort. Solving this problem would be a huge step forward in the component-based software development. In this thesis, we concentrate on a subproblem of the composition problem, composition planning or synthesis, which is defined as finding a collection of useful components from the repository and the necessary communications among them to satisfy a requested functionality. For scalability purposes, we study automatic solutions to composition planning and propose two approaches in this regard. In one, we take advantage of graphs to model the repository, which is the collection of available components along with their behavioral specification. Graph search algorithms and a few composition-specific algorithms are used to find solutions for given component requests. In the other approach, we extend a logical reasoning algorithm and come up with algorithms for solving the composition planning problem. In both approaches we provide algorithms for finding the possibility of a composition, as well as finding the composition itself. We propose different types of composition and show how applying each would impact the behavior of a composite component. We provide the necessary formalism for capturing these types of composition through two different models: interface automata and composition algebra. Interface automata is an automaton-based model for representing the behavior of software components. The other model in this regard is composition algebra, which is an algebraic model based on CSP (Communicating Sequential Processes), CCS (Calculus of Communicating Systems), and interface automata. These formal models are used to validate the results returned by the composition approaches. We also compare the two composition approaches and show why each of them is suitable for specific types of the problem according to the repository attributes. We then evaluate the performance of the reasoning-based approach and provide some experimental results. In these experiments, we study how different attributes of the repository components could impact the performance of the reasoning-based approach in solving the composition planning problem.

This thesis addresses the issues of coherent distributed knowledge production and sharing in the Life-science area. In spite of the continuously increasing computing and storage capabilities of computing infrastructures, the management of massive scientific data through centralized approaches became inappropriate, for several reasons: (i) they do not guarantee the autonomy property of data providers, constrained, for either ethical or legal concerns, to keep the control over the data they host, (ii) they do not scale and adapt to the massive scientific data produced through e-Science platforms. In the context of the NeuroLOG and VIP Life-science collaborative platforms, we address on one hand, distribution and heterogeneity issues underlying, possibly sensitive, resource sharing ; and on the other hand, automated knowledge production through the usage of these e-Science platforms, to ease the exploitation of the massively produced scientific data. We rely on an ontological approach for knowledge modeling and propose, based on Semantic Web technologies, to (i) extend these platforms with efficient, static and dynamic, transparent federated semantic querying strategies, and (ii) to extend their data processing environment, from both provenance information captured at run-time and domain-specific inference rules, to automate the semantic annotation of ''in silico'' experiment results. The results of this thesis have been evaluated on the Grid'5000 distributed and controlled infrastructure. They contribute to addressing three of the main challenging issues faced in the area of computational science platforms through (i) a model for secured collaborations and a distributed access control strategy allowing for the setup of multi-centric studies while still considering competitive activities, (ii) semantic experiment summaries, meaningful from the end-user perspective, aimed at easing the navigation into massive scientific data resulting from large-scale experimental campaigns, and (iii) efficient distributed querying and reasoning strategies, relying on Semantic Web standards, aimed at sharing capitalized knowledge and providing connectivity towards the Web of Linked Data.

Reuse is not a new concept in software engineering. Ideas, abstractions, and processes have been reused by programmers since the very early days of software development. In the beginning, since storage media was very expensive, software reuse was basically to serve computers and their mechanical resources, as it substantially conserved memory. When the limitations on physical resources started to diminish, software engineers began to invent reuse approaches to save human resources as well. In addition, as the size and complexity of software systems constantly grow, organized and systematic reuse becomes essential in order to develop those systems in timely and cost-effective fashion. That is one main reason why new technologies and approaches for building software systems, such as object-oriented and component-based development, emerged in the last two or three decades. The focus of this thesis is on software components as building blocks of today's software systems. We consider components as software black boxes whose specification and external behavior are known. We assume that this information can somehow be extracted for each deployed software component. The first and basic assumption then would be the availability of a searchable repository of software components and their external behavioral specifications. Web services are a good example of such components. The most important advantage of software components is that they can be reused repeatedly in building different software systems. Reuse presents challenging problems, one of which is studied in this thesis. This problem, the composition problem, simply is creating a composite component from a collection of available components that, by interacting with each other, provide a requested functionality. When there are a large number of components available to be reused, finding a solution to the composition problem manually would require a considerable time and human effort. This could make the search practically impossible or unwieldy. However, performing the search automatically would save a significant amount of development time, cost and human effort. Solving this problem would be a huge step forward in the component-based software development. In this thesis, we concentrate on a subproblem of the composition problem, composition planning or synthesis, which is defined as finding a collection of useful components from the repository and the necessary communications among them to satisfy a requested functionality. For scalability purposes, we study automatic solutions to composition planning and propose two approaches in this regard. In one, we take advantage of graphs to model the repository, which is the collection of available components along with their behavioral specification. Graph search algorithms and a few composition-specific algorithms are used to find solutions for given component requests. In the other approach, we extend a logical reasoning algorithm and come up with algorithms for solving the composition planning problem. In both approaches we provide algorithms for finding the possibility of a composition, as well as finding the composition itself. We propose different types of composition and show how applying each would impact the behavior of a composite component. We provide the necessary formalism for capturing these types of composition through two different models: interface automata and composition algebra. Interface automata is an automaton-based model for representing the behavior of software components. The other model in this regard is composition algebra, which is an algebraic model based on CSP (Communicating Sequential Processes), CCS (Calculus of Communicating Systems), and interface automata. These formal models are used to validate the results returned by the composition approaches. We also compare the two composition approaches and show why each of them is suitable for specific types of the problem according to the repository attributes. We then evaluate the performance of the reasoning-based approach and provide some experimental results. In these experiments, we study how different attributes of the repository components could impact the performance of the reasoning-based approach in solving the composition planning problem.

The Web turns out to be a collection of services that interoperate through the Internet. As the number of services increase, it is getting more and more diffucult for users to find, filter and integrate these services depending on their requirements. Automatic techniques are being developed to fulfill these tasks. The first step toward automatic composition is the discovery of services needed. UDDI which is one of the accepted web standards, provides a registry of web services. However representation capabilities of UDDI are insufficient to search for services on the basis of what they provide. Semantic web initiatives like OWL and OWL-S are promising for locating exact services based on their capabilities. In this thesis, a new semantic service discovery mechanism is implemented based on OWL-S service profiles. The service profiles of an advertisement and a request are matched based on OWL ontologies describing them. In contrast to previous work on the subject, the ontologies of the advertisement and the request are not assumed to be same. In case they are different, schema matching algorithms are applied. Schema matching algorithms find the mappings between the given schema models. A hybrid combination of semantic, syntactic and structural schema matching algorithms are applied to match ontologies

Web service composition is an inevitable aspect of web services technology, which solves complex problems by combining available basic services and ordering them to best suit the problem requirements. Automatic composition gives us flexibility of selecting best candidate services at composition time, this would require the user to define the resource allocation constraints for selecting and composing candidate web services. Resource allocation constraints define restrictions on how to allocate resources, and scheduling under resource allocation constraints to provide proper resource allocation to tasks. In this work, web service composition system named as CWSF (Composite Web Service Framework) constructed for users to define a workflow system in which a rich set of constraints can be defined on web services. On the contrary many technologies and studies, CWSF provides a user-friendly environment for modeling web service composition system. The output of the framework is the scheduling of web service composition in which how and when web services are executed are defined. With this work, a language, CWSL is defined to describe workflow, resource allocation constraints, selection and discovery rules of web services and associated semantic information. An important property of CWSF system is converting web service composition problem into a constraint satisfaction problem to find the best solution that meet the all criteria defined by user. Furthermore, CWSF has ability to display other possible solutions to provides users flexibility. This study also includes semantic matching and mapping facilities for service discovery.

In Web service composition, service discovery and combining suitable services through determination of interoperability among different services are important operations. Utilizing semantics improves the quality and facilitates automation of these operations. There are several previous approaches for semantic service discovery and service matching. In this work, we exploit and extend these semantic approaches in order to make Web service composition process more facilitated, less error prone and more automated. This work includes a service discovery and service interoperability checking technique which extends the previous semantic matching approaches. In addition to this, as a guidance system for the user, a new semantic domain model is proposed that captures semantic relations between concepts in various ontologies.

In today&#039 / s world, composite web services are widely used in service oriented computing, web mashups and B2B Applications etc. Most of these services are composed manually. However, the complexity of manually composing web services increase exponentially with the increase in the number of available web services, the need for dynamically created/updated/discovered services and the necessity for higher amount of data bindings and type mappings in longer compositions. Therefore, current highly manual web service composition techniques are far from being the answer to web service composition problem. Automatic web service composition methods are recent research efforts to tackle the issues with manual techniques. Broadly, these methods fall into two groups: (i) workflow based methods and (ii) methods using AI planning. This thesis investigates the application of AI planning techniques to the web service composition problem and in particular, it proposes the use of the abductive event calculus in this domain. Web service compositions are defined as templates using OWL-S (&quot / OWL for Services&quot / ). These generic composition definitions are converted to Prolog language as axioms for the abductive event calculus planner and solutions found by the planner constitute the specific result plans for the generic composition plan. In this thesis it is shown that abductive planning capabilities of the event calculus can be used to generate the web service composition plans that realize the generic procedure.

In recent years, web services have become an emerging technology for communication and integration between applications in many areas such as business to business (B2B) or business to commerce (B2C). In this growing technology, it is hard to compose web services manually because of the increasing number and compexity of web services. Therefore, automation of this composition process has gained a considerable amount of popularity. Automated web service composition can be achieved either by generating the composition plan dynamically using given inputs and outputs, or by locating the correct services if an abstract process model is given. This thesis investigates the former method which is dynamicly generating the composition by using the abductive lanning capabilities of the Event Calculus. Event calculus axioms in Prolog language, are generated using the available OWL-S web service descriptions in the service repository, values given to selected inputs from ontologies used by those semantic web services and desired output types selected again from the ontologies. Abductive Theorem Prover which is the AI planner used in this thesis, generates composition plans and execution results according to the generated event calculus axioms. In this thesis, it is shown that abductive event calculus can be used for generating web services composition plans automatically, and returning the results of the generated plans by executing the necessary web services.

In this thesis, some novel ideas are presented for solving automated web service composition problem. Some possible real world problems such as partial observability of environment, nondeterministic effects of web services, service execution failures are solved through some mechanisms. In addition to automated web service composition, automated web service invocation task is handled in this thesis by using reflection mechanism. The proposed approach is based on AI planning. Web service composition problem is translated to AI planning problem and a novel AI planner namely &ldquo / Simplanner&rdquo / that is designed for working in highly dynamic environments under time constraints is adapted to the proposed system. World altering service calls are done by conforming to the WS-Coordination and WS-Business Activity web service transaction specifications in order to physically repair failure situations and prevent undesired side effects of aborted web service composition efforts.

In this thesis, some enhancements to an existing automatic web service composition and execution system are described which provide a practical significance to the existing framework with scalability, i.e. the ability to operate on large service sets in reasonable time. In addition, the service storage mechanism utilized in the enhanced system presents an effective method to maintain large service sets. The described enhanced system provides scalability by implementing a pre-processing phase that extracts service chains and problem initial and goal state dependencies from service descriptions. The service storage mechanism is used to store this extracted information and descriptions of available services. The extracted information is used in a forward chaining algorithm which selects the potentially useful services for a given composition problem and eliminates the irrelevant ones according to the given problem initial and goal states. Only the selected services are used during the AI planning and execution phases which generate the composition and execute the services respectively.