Andreas S. Andreou

Key issues for the design and development of mobile commerce services and applications

This paper suggests a new approach for developing m-commerce services and applications based on a scheme that divides m-applications into directory- and transaction-oriented classes, identifies mobile user requirements, and takes into consideration the constraints of current technologies for mobile and wireless computing. The efficacy of the proposed approach in a real scenario is discussed.

Automatic, evolutionary test data generation for dynamic software testing

This paper proposes a dynamic test data generation framework based on genetic algorithms. The framework houses a Program Analyser and a Test Case Generator, which intercommunicate to automatically generate test cases. The Program Analyser extracts statements and variables, isolates code paths and creates control flow graphs. The Test Case Generator utilises two optimisation algorithms, the Batch-Optimistic (BO) and the Close-Up (CU), and produces a near to optimum set of test cases with respect to the edge/condition coverage criterion. The efficacy of the proposed approach is assessed on a number of programs and the empirical results indicate that its performance is significantly better compared to existing dynamic test data generation methods.

Nonlinear analysis and forecasting of a brackish Karstic spring

Nonlinear methods and artificial neural network techniques are applied to the study of the regime and the possibility of short-term forecasting of discharges of the spring of Almyros, Iraklion, Crete. Questions regarding the nonlinearity and chaotic characteristics of the system necessitate the examination of dynamical properties. Toward this objective the time series of daily average discharges is analyzed in detail. First, the dimensionality of the dynamics in the reconstructed phase space is found to be quite low, ∼3–4. Then several tests are applied to examine the nonlinearity and the presence of noise in the data. Using the surrogate time series test, a high degree of nonlinearity and a deterministic nature are revealed, while the differentiation test showed that the presence of high-frequency noise in the series of the discharge is not dynamically important. These suggest that an attempt to forecast the short-term future behavior of this time series may turn out to be quite successful. Nonlinear methods, such as Farmers algorithm and artificial neural networks, were employed and found to exhibit a very satisfactory predictive ability, with neural networks achieving a slightly better performance.

Exchange-Rates Forecasting: A Hybrid Algorithm Based onGenetically Optimized Adaptive Neural Networks

The use of neural networks trained by a new hybrid algorithm is employed on forecasting the Greek Foreign Exchange-Rate Market. Four major currencies, namely the U.S. Dollar (USD), the Deutsche Mark (DEM), the French Franc (FF) and the British Pound (GBP), versus the Greek Drachma, were used as experimental data. The proposed algorithm combines genetic algorithms and a training method based on the localized Extended Kalman Filter (EKF), in order to evolve the structure and train Multi-Layered Perceptron (MLP) neural networks. The goal of this effort is to predict, as accurately as possible, exchange-rates future behavior. Simulation results show that the method gives highly successful results, while the diversification of the structure between the four currencies has no effect on the performance.

A quality framework for developing and evaluating original software components

Component-based software development is being identified as the emerging method of developing complex applications consisting of heterogeneous systems. Although more research attention has been given to Commercial Off The Shelf (COTS) components, original software components are also widely used in the software industry. Original components are smaller in size, they have a narrower functional scope and they usually find more uses when it comes to specific and dedicated functions. Therefore, their need for interoperability is equal or greater, than that of COTS components. A quality framework for developing and evaluating original components is proposed in this paper, along with an application methodology that facilitates their evaluation. The framework is based on the ISO9126 quality model which is modified and refined so as to reflect better the notion of original components. The quality model introduced can be tailored according to the organization-reuser and the domain needs of the targeted component. The proposed framework is demonstrated and validated through real case examples, while its applicability is assessed and discussed.

Software Cost Estimation using Fuzzy Decision Trees

This paper addresses the issue of software cost estimation through fuzzy decision trees, aiming at acquiring accurate and reliable effort estimates for project resource allocation and control. Two algorithms, namely CHAID and CART, are applied on empirical software cost data recorded in the ISBSG repository. Approximately 1000 project data records are selected for analysis and experimentation, with fuzzy decision trees instances being generated and evaluated based on prediction accuracy. The set of association rules extracted is used for providing mean effort value ranges. The experimental results suggest that the proposed approach may provide accurate cost predictions in terms of effort. In addition, there is strong evidence that the fuzzy transformation of cost drivers contribute to enhancing the estimation process.

An Automatic Software Test-Data Generation Scheme Based on Data Flow Criteria and Genetic Algorithms

Software test-data generation research primarily focuses on using control flow graphs for producing an optimum set of test cases. This paper proposes the integration of a data flow graph module with an existing testing framework and the utilisation of a specially designed genetic algorithm for automatically generating test cases based on data flow coverage criteria. The enhanced framework aims to explore promising aspects of software testing that have not yet received adequate research attention, by exploiting the data information of a program and provide a different testing coverage approach compared to existing control flow-oriented ones. The performance of the proposed approach is assessed and validated on a number of sample programs of different levels of size and complexity. The associated experimental results indicate successful performance in terms of testing coverage, which is significantly better when compared to those of existing dynamic data flow-oriented test data generation methods.

Empirical evidence and state of practice of software agile teams

The paper provides an in depth analysis of empirical evidence on the state of practice within the agile domain obtained through a survey conducted in 2012. The context of focus is agile software processes and teams and the particular topics of interest revolve around three axes: (i) communication; (ii) project management; and (iii) quality assurance and validation. The aim of the survey is to deliver the current levels of agile adoption and practices as these are recorded in the responses of professionals in IT services and the software industry. The goal of the survey is to provide evidence‐based assessment of the level of agile adoption by software development organizations, in relation to the general profile of the respondents (country of origin, business sectors, roles, etc.) and compared with different types of practices followed, such as agile techniques adopted, team organization and communication techniques, and project management. Particular patterns and trends are identified in the survey connecting the use of the agile paradigm with the aforementioned practices and investigating its relation with the roles of the respondents and the business strategies of their organizations. Copyright

WAQE: a Web Application Quality Evaluation model

Developing and maintaining web applications that have high quality demands the provision of certain assessment and monitoring mechanisms to afford such a success. Continuous evaluation of the web applications to check if they meet functional and non-functional requirements, as well as the organisational goals, necessitates the use of quality evaluation models in a fast-changing environment. This paper proposes an efficient web application quality evaluation model that is based on two axons: internal (within the organisation) and external (the users). The model places emphasis on quality issues as defined by ISO 9126 and other web quality factors and utilises importance-based criteria for evaluating requirements. Finally, the applicability and efficiency of the model are demonstrated through the evaluation of two different types of web applications.

The cyprus puzzle and the greek - turkish arms race: forecasting developments using genetically evolved fuzzy cognitive maps

The scope of this paper is to forecast the extent to which a settlement of the Cyprus issue may be possible given the decisions taken during the Copenhagen EU summit. It aims, in addition, at investigating the possibilities of improvement in Greek-Turkish relations which may lead, in turn, to reducing the arms race between the two countries. The paper uses a Genetically Evolved Certainty Neuron Fuzzy Cognitive Map algorithm to consider a number of scenarios examining the possible reactions of all sides involved in the Cyprus issue, namely Greece, Turkey, Cyprus, the Turkish-Cypriot community and the international environment. All simulation exercises suggest that the Greek and the Cypriot side should not necessarily rely on the decisions taken during the Copenhagen summit conference. The forecasts point out, in addition, that the optimism of the Greek government concerning the outlook of its relations with Turkey, and a subsequent reduction of the arms race against it, is far from being justified.