Blockchain for Collaborative Businesses

Mobile Networks and Applications - Blockchain applications have continuously improved ever since its first debut on cryptocurrency. From then on, its uses have branched out from the financial...     

Intelligent security and access control framework for service-oriented architecture

One of the most significant difficulties with developing Service-Oriented Architecture (SOA) involves meeting its security challenges, since the responsibilities of SOA security are based on both the service providers and the consumers. In recent years, many solutions to these challenges have been implemented, such as the Web Services Security Standards, including WS-Security and WS-Policy. However, those standards are insufficient for the new generation of Web technologies, including Web 2.0 applications. In this research, we propose an intelligent SOA security framework by introducing its two most promising services: the Authentication and Security Service (NSS), and the Authorization Service (AS). The suggested autonomic and reusable services are constructed as an extension of WS-¹ security standards, with the addition of intelligent mining techniques, in order to improve performance and effectiveness. In this research, we apply three different mining techniques: the Association Rules, which helps to predict attacks, the Online Analytical Processing (OLAP) Cube, for authorization, and clustering mining algorithms, which facilitate access control rights representation and automation. Furthermore, a case study is explored to depict the behavior of the proposed services inside an SOA business environment. We believe that this work is a significant step towards achieving dynamic SOA security that automatically controls the access to new versions of Web applications, including analyzing and dropping suspicious SOAP messages and automatically managing authorization roles.     

A new calibration for Function Point complexity weights

Function Point (FP) is a useful software metric that was first proposed 25 years ago, since then, it has steadily evolved into a functional size metric consolidated in the well-accepted Standardized International Function Point Users Group (IFPUG) Counting Practices Manual – version 4.2. While software development industry has grown rapidly, the weight values assigned to count standard FP still remain same, which raise critical questions about the validity of the weight values. In this paper, we discuss the concepts of calibrating Function Point, whose aims are to estimate a more accurate software size that fits for specific software application, to reflect software industry trend, and to improve the cost estimation of software projects. A FP calibration model called Neuro-Fuzzy Function Point Calibration Model (NFFPCM) that integrates the learning ability from neural network and the ability to capture human knowledge from fuzzy logic is proposed. The empirical validation using International Software Benchmarking Standards Group (ISBSG) data repository release 8 shows a 22% accuracy improvement of mean magnitude relative error (MMRE) in software effort estimation after calibration.     

HCI International 2011

Announcement

HCI International 2011     

Neural network models for software development effort estimation: a comparative study

Software development effort estimation (SDEE) is one of the main tasks in software project management. It is crucial for a project manager to efficiently predict the effort or cost of a software project in a bidding process, since overestimation will lead to bidding loss and underestimation will cause the company to lose money. Several SDEE models exist; machine learning models, especially neural network models, are among the most prominent in the field. In this study, four different neural network models—multilayer perceptron, general regression neural network, radial basis function neural network, and cascade correlation neural network—are compared with each other based on: (1) predictive accuracy centred on the mean absolute error criterion, (2) whether such a model tends to overestimate or underestimate, and (3) how each model classifies the importance of its inputs. Industrial datasets from the International Software Benchmarking Standards Group (ISBSG) are used to train and validate the four models. The main ISBSG dataset was filtered and then divided into five datasets based on the productivity value of each project. Results show that the four models tend to overestimate in 80 % of the datasets, and the significance of the model inputs varies based on the selected model. Furthermore, the cascade correlation neural network outperforms the other three models in the majority of the datasets constructed on the mean absolute residual criterion.     

Fuzzy inference system for software product family process evaluation

When developing multiple products within a common application domain, systematic use of a software product family process can yield increased productivity in cost, quality, effort and schedule. Such a process provides the means for the reuse of software assets which can considerably reduce the development time and the cost of software products. A comprehensive strategy for the evaluating the maturity of a software product family process is needed due to growing popularity of this concept in the software industry. In this paper, we propose a five-level maturity scale for software product family process. We also present a fuzzy inference system for evaluating maturity of software product family process using the proposed maturity scale. This research is aimed at establishing a comprehensive and unified strategy for process evaluation of a software product family. Such a process evaluation strategy will enable an organization to discover and monitor the strengths and weaknesses of the various activities performed during development of multiple products within a common application domain.     

Making Sense of Software Development and Personality Types

It's common sense to state that the production of any software product involves a human element, at least to some extent. We all have different personality traits, and the way we perceive, plan, and execute any activity is influenced by these characteristics. Typically, software development is a product of teamwork, involving several people performing various tasks. The success and failure of software projects reveal the human factor as one of vital importance. Not everyone can excel at every task, thus better results are achieved if people with particular personality traits are assigned to different aspects of a project, especially the roles best suited to their ability. The authors mapped some opposing psychological traits, such as extroversion-introversion, sensing-intuition, thinking-feeling, and judging-perceiving, to the main stages of a software development life cycle. Consequently, they concluded that assigning a person with specific psychological characteristics to the stage of the software life cycle best suited for his or her traits increases the chances of a successful outcome for the project.     

An organizational maturity model of software product line engineering

Software product line engineering is an inter-disciplinary concept. It spans the dimensions of business, architecture, process, and the organization. Some of the potential benefits of this approach include cost reduction, improvements in product quality and a decrease in product development time. The increasing popularity of software product line engineering in the software industry necessitates a process maturity evaluation methodology. Accordingly, this paper presents an organizational maturity model of software product line engineering for evaluating the maturity of organizational dimension. The model assumes that organizational theories, behavior, and management play a critical role in the institutionalization of software product line engineering within an organization. Assessment questionnaires and a rating methodology comprise the framework of this model. The objective and design of the questionnaires are to collect information about the software product line engineering process from the dual perspectives of organizational behavior and management. Furthermore, we conducted two case studies and reported the assessment results using the organizational maturity model presented in this paper.     

Critical Success Factors to Improve the Game Development Process from a Developer’s Perspective

The growth of the software game development industry is enormous and is gaining importance day by day. This growth imposes severe pressure and a number of issues and challenges on the game development community. Game development is a complex process, and one important game development choice is to consider the developer’s perspective to produce good-quality software games by improving the game development process. The objective of this study is to provide a better understanding of the developer’s dimension as a factor in software game success. It focuses mainly on an empirical investigation of the effect of key developer’s factors on the software game development process and eventually on the quality of the resulting game. A quantitative survey was developed and conducted to identify key developer’s factors for an enhanced game development process. For this study, the developed survey was used to test the research model and hypotheses. The results provide evidence that game development organizations must deal with multiple key factors to remain competitive and to handle high pressure in the software game industry. The main contribution of this paper is to investigate empirically the influence of key developer’s factors on the game development process.