Claudia Szabo

Web services composition: A decade's overview

Service-oriented computing (SOC) represents a paradigm for building distributed computing applications over the Internet. In the past decade, Web services composition has been an active area of research and development endeavors for application integration and interoperation. Although Web services composition has been heavily investigated, several issues related to dependability, ubiquity, personalization, among others, still need to be addressed, especially giving the recent rise of several new computing paradigms such as Cloud computing, social computing, and Web of Things. This article overviews the life cycle of Web services composition and surveys the main standards, research prototypes, and platforms. These standards, research prototypes, and platforms are assessed using a set of assessment criteria identified in the article. The paper also outlines several research opportunities and challenges for Web services composition.

CODES: An Integrated Approach to Composable Modeling and Simulation

In component-based simulation, models developed in different locations and for specific purposes can be selected and assembled in various combinations to meet diverse user requirements. This paper proposes CODES (COmposable Discrete-Event scalable Simulation), an approach to component-based modeling and simulation that supports model reuse across multiple application domains. A simulation component is viewed by the modeller as a black box with an in- and/or out-channel. The attributes and behavior of the component abstracted as a meta-component are described using COML (COmponent Markup Language), a markup language we propose for representing simulation components. The integrated approach, supported by a proposed COSMO (COmponent-oriented Simulation and Modeling Ontology) ontology, consists of four main steps. Component discovery returns a set of syntactically valid model components. Syntactic composability is determined by our proposed EBNF syntactic composition rules. Validation of semantic composability is performed using our proposed data and behavior alignment algorithms. The semantically valid simulation component is subsequently stored in a model repository for reuse. As proof of concept, we discuss a prototype implementation of the CODES framework using queueing system as an application domain example.

On Syntactic Composability and Model Reuse

Composability, the capability to select and assemble off-the-shelf model components in various combinations to satisfy user requirements, is an appealing approach in reducing the time and costs of developing complex simulation. This paper discusses CODES, a hierarchical component framework to support component-based modeling and simulation. We propose the use of EBNF based grammars to specify syntactic composability rules with the aims of achieving syntax consistency for model components to operate together. EBNF production strings associated with each composed models are transformed into a unique identifier to support distributed DHT-based model discovery. The hierarchical design supports the sharing and reuse of models and model components across application domains, and facilitates the verification of composed models. We present a prototype of the framework implemented using the scalable simulation framework, and illustrate this approach by modeling a grid computing system

Evolving multi-objective strategies for task allocation of scientific workflows on public clouds

With the increase in deployment of scientific application on public and private clouds, the allocation of workflow tasks to specific cloud instances to reduce runtime and cost has emerged as an important challenge. The allocation of scientific workflows on public clouds can be described through a variety of perspectives and parameters and has been proved to be NP-complete. This paper presents an optimization framework for task allocation on public clouds. We present a solution that considers important parameters such as workflow runtime, communication overhead, and overall execution cost. Our multi-objective optimization framework builds on a simple and extensible cost model and uses a heuristic to determine the optimal number of cloud instances to be used. Using the Amazon Elastic Compute Cloud (EC2) and Amazon Simple Storage Service (S3) as an example, we show how our optimization heuristics lead to significantly better strategies than other state-of-the-art approaches. Specifically, our single-objective optimization is slightly better than a simple heuristic and a particle swarm optimization approach for small workflows, and achieves significant improvements for larger workflows. In a similar manner, our multi-objective optimization obtains similar results to our single-objective optimization for small-size workflows, and achieves up to 80% improvement for large-size workflows.

Behavior modeling and automated verification of Web services

Cloud computing has been rapidly adopted over the last few years. However, techniques on Web services, one of the most important enabling technologies for cloud computing, are still not mature yet. In this paper, we propose a novel approach that supports dependable development of Web services. Our approach includes a new Web service model that separates service behaviors into operational and control behaviors. The coordination of operational and control behaviors at runtime is facilitated by conversational messages. We also propose an automated service verification approach based on symbolic model checking. In particular, our approach extracts the checking properties, in the form of temporal logic formulas, from control behaviors, and automatically verifies the properties in operational behaviors using the NuSMV model checker. The approach presented in this paper has been implemented using a number of state-of-the-art technologies. We conducted a number of experiments to study the performance of our proposed approach in detecting design problems in services. The results show that our automated approach can successfully detect service design problems. Our system offers a set of tools assisting service developers in specifying, debugging, and monitoring service behaviors.

An Approach for Validation of Semantic Composability in Simulation Models

Semantic composability aims to ensure that the composition of simulation components is meaningful in terms of their expressed behavior, and achieves the desired objective of the new composed model. Validation of semantic composability is a non-trivial problem because reused simulation components are heterogeneous in nature and validation must consider various orthogonal aspects including logical, temporal, and formal. In this paper, we propose a layered approach to semantic composability validation with increasing accuracy and complexity. The first layer exploits model checking for logical properties of component coordination including deadlock, safety, and liveness. Next, we address temporal properties by validating composition safety and liveness through simulation time. The third layer provides a formal composition validation guarantee by determining the behavioral equivalence between the composed model and a perfect model. In contrast to state-of-the-art approaches, we propose time-based formalisms to describe simulation components and compare the composition behaviors through time using semantically related composition states.

A time-based formalism for the validation of semantic composability

Simulation components are semantically composable if the newly composed model is meaningful in terms of expressed behaviors, and achieves the desired objective. The validation of semantic composability is challenging because reused simulation components are heterogeneous in nature and validation must consider various aspects including logical, temporal, and formal. In this paper, we propose a new time-based formal approach for semantic composability validation. Our validation process provides a formal composition validation guarantee by establishing the behavioral equivalence between the composed model and a perfect model. Next, composition behaviors are compared through time using semantically related composition states. We evaluate our formal approach using time complexity and experimental analysis using the CADP analyzer.

Student projects are not throwaways: teaching practical software maintenance in a software engineering course

Teaching software engineering through group-based project work supported by theory lectures is effective, as recognized by both academia and industry. However, exposing students to practical software maintenance is often overlooked in favor of building software from scratch under the guidance of a lecturer or client. The developed software is usually delivered to the lecturer/client and no maintenance efforts are further required. In contrast, industry projects require fresh graduates to perform maintenance exercises and very rarely to build software from scratch. To address this issue, existing software maintenance assignments usually focus on small codebases of very good quality, in which artificial issues are introduced. In this paper, we propose to enhance a group-based project course with a software maintenance assignment that uses a medium-sized, student-produced codebase with real software bugs. Our analysis shows the effectiveness of our approach and highlights future avenues for improvement.

Formalization of emergence in multi-agent systems

Emergence is a distinguishing feature in systems, especially when complexity grows with the number of components, interactions, and connectivity. There is immense interest in emergence, and a plethora of definitions from philosophy to sciences. Despite this, there is a lack of consensus on the definition of emergence and this hinders the development of a formal approach to understand and predict emergent behavior in multi-agent systems. This paper proposes a grammar-based set-theoretic approach to formalize and verify the existence and extent of emergence without prior knowledge or definition of emergent properties. Our approach is based on weak (basic) emergence that is both generated and autonomous from the underlying agents. In contrast with current work, our approach has two main advantages. By focusing only on system interactions of interest and feasible combinations of individual agent behavior, state-space explosion is reduced. In formalizing emergence, our extended grammar is designed to model agents of diverse types, mobile agents, and open systems. Theoretical and experimental studies using the boids model demonstrate the complexity of our formal approach.

Post-mortem analysis of emergent behavior in complex simulation models

Analyzing and validating emergent behavior in component-based models is increasingly challenging as models grow in size and complexity. Despite increasing research interest, there is a lack of automated, formalized approaches to identify emergent behavior and its causes. As part of our integrated framework for understanding emergent behavior, we propose a post-mortem emergence analysis approach that identifies the causes of emergent behavior in terms of properties of the composed model and properties of the individual model components, and their interactions. In this paper, we detail the use of reconstructability analysis for post-mortem analysis of known emergent behavior. The two-step process first identifies model components that are most likely to have caused emergent behavior, and then analyzes their interaction. Our case study using small and large examples demonstrates the applicability of our approach.