George Kakarontzas

Agent-Based Resource Discovery and Selection for Dynamic Grids

The massive amount of resources on computational grids raises the question of efficient resource discovery and selection. In this paper we present an agent-based approach to these two phases of a grid scheduling process. The approach is based on client agents which act on behalf of grid users, and search for resources in a network of resource representatives that are registries of resource characteristics. After potentially suitable resources are discovered, client agents carry out negotiations directly with agents representing local resource management systems. This selection process first determines the willing resources with a contract-net protocol and then uses current load information and a more accurate post-discovery search to determine the optimum set of resources for the task in hand

An empirical investigation on the reusability of design patterns and software packages

Nowadays open-source software communities are thriving. Successful open-source projects are competitive and the amount of source code that is freely available offers great reuse opportunities to software developers. Thus, it is expected that several requirements can be implemented based on open source software reuse. Additionally, design patterns, i.e. well-known solution to common design problems, are introduced as elements of reuse. This study attempts to empirically investigate the reusability of design patterns, classes and software packages. Thus, the results can help developers to identify the most beneficial starting points for white box reuse, which is quite popular among open source communities. In order to achieve this goal we conducted a case study on one hundred (100) open source projects. More specifically, we identified 27,461 classes that participate in design patterns and compared the reusability of each of these classes with the reusability of the pattern and the package that this class belongs to. In more than 40% of the cases investigated, design pattern based class selection, offers the most reusable starting point for white-box reuse. However there are several cases when package based selection might be preferable. The results suggest that each pattern has different level of reusability.

Product Line Variability with Elastic Components and Test-Driven Development

In this work we present a systematic approach for the creation of new variant software components via customization of existing core assets of a software product line. We consider both functional and quality variants and address the issue of a controlled creation of variants which considers the reference architecture and its co-evolution with a number of other artifacts including components and functional and quality test suites. Furthermore we discuss the relationship between the popular agile practice of test-driven development (TDD) and how it can be used to assist the evolution of software components of a software product line.

Towards Open Source Software System Architecture Recovery Using Design Metrics

Over the past years, software development practices include open source code reuse. Since documentation gives little or no information about the system architecture, a prohibitive amount of effort is required to comprehend the source code and the overall system architecture. In this paper, we investigate how design metrics can reveal architectural information about a software system and more specifically, how architectural layers are correlated to design metrics. Finally, we present an empirical study on two large open source systems written in Java, attempting to identify metrics revealing information about the system architecture.

Layer assessment of object-oriented software

Highlights? We analyze using multiple linear regression nearly 22,000 classes of 29 Open Source Java systems. ? In our analysis Chidamber and Kemerer metrics were used as predictors of the layer of each class. ? Analysis resulted in a new metric, suitable for the white-box reuse of object-oriented software. ? The new metric is compared against three other proposed metrics and shows significant advantages. ? The metric is suitable for the white box reuse of classes, componentization and rearchitecting. Software reuse has the potential to shorten delivery times, improve quality and reduce development costs. However software reuse has been proven challenging for most organizations. The challenges involve both organizational and technical issues. In this work we concentrate on the technical issues and we propose a new metric facilitating the reuse of object-oriented software based on the popular Chidamber and Kemerer suite for object-oriented design. We derive this new metric using linear regression on a number of OSS java projects. We compare and contrast this new metric with three other metrics proposed in the literature. The purpose of the proposed metric is to assist a software developer during the development of a software system in achieving reusability of classes considered important for future reuse and also in providing assistance during re-architecting and componentization activities of existing systems.

Quantification of interacting runtime qualities in software architectures: Insights from transaction processing in client-server architectures

Context: Architecture is fundamental for fulfilling requirements related to the non-functional behavior of a software system such as the quality requirement that response time does not degrade to a point where it is noticeable. Approaches like the Architecture Tradeoff Analysis Method (ATAM) combine qualitative analysis heuristics (e.g. scenarios) for one or more quality metrics with quantitative analyses. A quantitative analysis evaluates a single metric such as response time. However, since quality metrics interact with each other, a change in the architecture can affect unpredictably multiple quality metrics. Objective: This paper introduces a quantitative method that determines the impact of a design change on multiple metrics, thus reducing the risks in architecture design. As a proof of concept, the method is applied on a simulation model of transaction processing in client server architecture. Method: Factor analysis is used to unveil latent (i.e. not directly measurable) quality features represented by new variables that reflect architecture-specific correlations between metrics. Separate Analyses of Variance (ANOVA) are then applied to these variables, for interpreting the tradeoffs detected by factor analysis in terms of the quantified metrics. Results: The results for the examined transaction processing architecture show three latent quality features, the corresponding groups of strongly correlated quality metrics and the impact of architecture characteristics on the latent quality features. Conclusion: The proposed method is a systematic way for relating the variability of quality metrics and the implied tradeoffs to specific architecture characteristics.

Elastic Components: Addressing Variance of Quality Properties in Components

The quality properties of a software component, although verified by the component developer and even certified by a trusted third-party, might very well be inappropriate for the requirements of a new system. This is what we call the quality mismatch problem: the mismatch between the quality requirements of a new system with the quality properties exhibited by the components that we want to use for its development. This work contributes to the understanding of the quality mismatch problem between component properties and component-based systems requirements. To solve this problem we introduce the concept of elastic components. An elastic component is an open-ended hierarchy of the same pure component with variants that differ between them to the quality properties that they exhibit. We present a quality-driven design approach that can be effectively applied for the design and implementation of elastic components.

Competence assessment as an expert system for human resource management: A mathematical approach

Abstract Efficient human resource management needs accurate assessment and representation of available competences as well as effective mapping of required competences for specific jobs and positions. In this regard, appropriate definition and identification of competence gaps express differences between acquired and required competences. Using a detailed quantification scheme together with a mathematical approach is a way to support accurate competence analytics, which can be applied in a wide variety of sectors and fields. This article describes the combined use of software technologies and mathematical and statistical methods for assessing and analyzing competences in human resource information systems. Based on a standard competence model, which is called a Professional, Innovative and Social competence tree, the proposed framework offers flexible tools to experts in real enterprise environments, either for evaluation of employees towards an optimal job assignment and vocational training or for recruitment processes. The system has been tested with real human resource data sets in the frame of the European project called ComProFITS.

ComProFITS: A web-based platform for human resources competence assessment

An efficient assessment of human resource competences, followed by the goal oriented analysis of the results, support the identification of the competence gaps in organizations and the allocation of resources towards identified gaps. This paper presents the basic idea as well as the scientific and implementation results of the ComProFITS project as an innovative web-based platform for the evaluation of existing employees and the recruitment of new employees in organizations. The platform integrates research on the statistical assessment of competences, an innovative competence pyramid and many alternative methods of employee evaluation and recruitment. The initial version of the platform is being applied and used in the IT sector in a large organization in Spain with the goal of extending it to the Spanish and European wide enterprises in different sectors.

An Adaptive Model for Competences Assessment of IT Professionals

Emerging technologies such as Big Data and Cloud Computing in the field of information technology imposes further needs (requests) for professional competences in organizations and IT companies. The ultimate goal is to comply with industrial changes characterizedby adaptive solutions for fostering human-machine interactions. Here competence and job knowledge play a great role in organizations. This paper discusses the concept ofan adaptive competence profiling platform in the context of EU funded project ComProFITS. The main goal is (i) reinforcing competence analytics, and (ii) improving the quality of personnel selection and job performance in the IT sector. This project reflects the results of the research and development activities based on needs analysis with a Spanish IT company.