Vol. 26 · No. 4

The quality of mobile services in the mobile and wireless world is ultimately judged in terms of customer satisfaction. This is particularly true for the third generation (3G) and beyond multimedia mobile services which should meet or exceed customer expectations. In this study Quality Function Deployment (QFD) is used for the first time as a quality improvement approach for building customers' requirements into mobile services. Traditionally QFD approach is adopted in product and manufacturing industries. In this paper QFD is extended to mobile service industry which is such a promising industry in today's information society. This paper proposes a generic framework based on QFD concepts and practices to improve mobile service design and development. An example is presented to illustrate the use of QFD for mobile e-learning services for university students and lecturers. The data transmission speed is found to be the most critical requirement in mobile e-learning services. By the use of QFD the developed mobile services can best meet customers' requirements or even exceed their expectations. At the end of this paper some benefits as well as further improvements regarding QFD approach are discussed and concluded.

Software testing takes a considerable amount of time and resources spent on producing software. Therefore, it would be useful to have ways to reduce the cost of software testing. The new concepts of spanning sets of entities suggested by Marre and Bertolino are useful for reducing the cost of testing. In fact, to reduce the testing effort, the generation of test data can be targeted to cover the entities in the spanning set, rather than all the entities in the tested program. Marre and Bertolino presented an algorithm based on the subsumption relation between entities to find spanning sets for a family of control flow and data flow-based test coverage criteria. This paper presents a new general technique for the automatic test data generation for spanning sets coverage. The proposed technique applies to the algorithm proposed recently by Marre and Bertolino to automatically generate the spanning sets of program entities that satisfy a wide range of control flow and data flow-based test coverage criteria. Then, it uses a genetic algorithm to automatically generate sets of test data to cover these spanning sets. The proposed technique employed the concepts of spanning sets to limit the number of test cases, guide the test case selection, overcome the problem of the redundant test cases and automate the test path generation.

This paper describes a hybrid method of typewritten Arabic character recognition by Toeplitz Matrices and Neural Networks (TMNN) applying a new technique for feature selecting and data mining. The suggested algorithm reduces the NN input data to only the most significant and essential-for-classification points. Four items are determined to resemble the distribution percentage of the essential feature points in each part of the extracted character image. Feature points are detected depending on a designed algorithm for this aim. This algorithm is of high performance and is intelligent enough to define the most significant points which satisfy the sufficient conditions to recognize almost all written fonts of Arabic characters. The number of essential feature points is reduced by at least 88

Formal methods have come into use for the construction of real systems, as they help increase software quality and reliability. However, they are usually accessible only to specialists, thus discouraging stakeholders' participation, crucial in first steps of software development. To address this problem, we present in this paper a strategy to derive an initial formal specification, written in the RAISE Specification Language, from requirements models based on natural language, such as the Language Extended Lexicon, the Scenario Model, and the Business Rules Model, which are closer to the stakeholders' language. We provide a set of heuristics which show how to derive types and functions, and how to structure them in a layered architecture, thus contributing to fruitfully use the large amount of information usually available after requirements modelling stage. In addition, we illustrate the strategy with a concrete case study.

Flooding in the major river basins of Central Europe is a recurrent event affecting many countries. Almost every year, it takes away lives and causes damage to infrastructure, agricultural and industrial production, and severely affects socio-economic development. Recurring floods of the magnitude and frequency observed in this region is a significant impediment, which requires rapid development of more flexible and effective flood-forecasting systems. In this paper we present design and development of the flood-forecasting system based on the Semantic Grid services citegoble. We will highlight the corresponding architecture, discovery and composition of services into workflows and semantic tools supporting the users in evaluating the results of the flood simulations citekwfgrid. We will describe in detail the challenges of the flood-forecasting application and corresponding design and development of the service-oriented model, which is based on the well known Web Service Resource Framework (WSRF). Semantic descriptions of the WSRF services will be presented as well as the architecture, which exploits semantics in the discovery and composition of services. Further, we will demonstrate how experience management solutions can help in the process of service discovery and user support. The system provides a unique bottom-up approach in the Semantic Grids by combining the advances of semantic web services and grid architectures.