softwareengineering (SE) and human-computer interaction (HCI) are often regarded as two separate entities while the fact is the two share many similarities and should affect each other to produce a better product or ...
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softwareengineering (SE) and human-computer interaction (HCI) are often regarded as two separate entities while the fact is the two share many similarities and should affect each other to produce a better product or software. In this paper, we compare two component frameworks that integrate both HCI and SE together. Our aim is to understand how each framework considers usability in the software development, and, to identify the strengths and weaknesses of both frameworks. The two component frameworks are IKnowU and UBAF. Comparison of these two frameworks can be useful for researchers as we can the four important criteria - model, architecture, usability work and process, that make of a framework which has usability as its paramount objective.
The successful implementation of Service-Oriented development of Distributed Embedded Real-time systems (DERTS) in the recent years has proved the importance of Service-Orientation over previous paradigms. However, ef...
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The successful implementation of Service-Oriented development of Distributed Embedded Real-time systems (DERTS) in the recent years has proved the importance of Service-Orientation over previous paradigms. However, efforts are still needed on systematic Service-Oriented design of DERTS, especially on the modelling of DERTS. The UML standard profile MARTE can be used for modelling of embedded real-time system while UML standard profile SoaML can be used to represent Service-Oriented concepts. Therefore, a thorough investigation of both standard profiles is needed to determine which parts of these profiles are useful for Service-Oriented DERTS development. This paper investigates these profiles in order to highlight the portions of the two profiles and provides some suggestions that can be utilized for Service-Oriented modelling of DERTS. The results of this investigation would be useful in developing a Service-Oriented based meta-model for DERTS.
Component-Based System (CBS) is an approach to build applications from deployed components. It provides efficiency, reliability, maintainability. The challenge of interpreting the results of performance analysis and g...
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Component-Based System (CBS) is an approach to build applications from deployed components. It provides efficiency, reliability, maintainability. The challenge of interpreting the results of performance analysis and generate alternative design to build component system is quite critical in the software performance domain. Although, many approaches have been proposed and were successfully applied to predict software performance, still span of design space hinder the selection of the appropriate design alternative. Meta-heuristics such as Genetic Algorithms (GA) methods have proven its usefulness to solve the problem even with multi-degree of freedom. But, in recent investigations Particle Swarm Optimization (PSO), an alternative search technique, often outperformed GA when applied to various problems. In this paper we describe performance prediction approach based on PSO for component-Based system development. The proposed approach aids developers to effectively trades-off between architectural designs alternatives. Boundary search technique and PSO are used to provoke more efficient results. To the best of our knowledge we are the first who employ PSO in software performance prediction. Outlines of our approach are presented and a case study applied using GA is described to be used by our approach for validation. This paper has concluded that, PSO technique can be used to effectively generate alternatives in spanned design space and facilitate the design decision during the development process.
Sensitivity based linear learning method (SBLLM) has recently been used as predictive tool due to its unique characteristics and performance, particularly its high stability and consistency during predictions. However...
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Testing is a very important task to build error free software. As the resources and time to market is limited for a software product, it is impossible to perform exhaustive test i.e., to test all combinations of input...
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Testing is a very important task to build error free software. As the resources and time to market is limited for a software product, it is impossible to perform exhaustive test i.e., to test all combinations of input data. To reduce the number of test cases in an acceptable level, it is preferable to use higher interaction level (t way, where t ≥ 2). Pairwise (2-way or t = 2) interaction can find most of the software faults. This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. Java program has been used to test the performance of the algorithm. The algorithm is able to support both uniform and non-uniform values effectively with performance better than the existing algorithms/tools in terms of number of generated test cases and time consumption.
Testing is a very important task to build error free software. As the resources and time to market is limited for a software product, it is impossible to perform exhaustive test i.e., to test all combinations of input...
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Testing is a very important task to build error free software. As the resources and time to market is limited for a software product, it is impossible to perform exhaustive test i.e., to test all combinations of input data. To reduce the number of test cases in an acceptable level, it is preferable to use higher interaction level (t way, where t = 2). Pairwise (2- way or t = 2) interaction can find most of the software faults. This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. Java program has been used to test the performance of the algorithm. The performance is better than the existing algorithms/tools in terms of number of generated test cases and time consumption.
The availability of high quality and inexpensive video camera, as well as the increasing need for automated video analysis is leading towards a great deal of interest in numerous applications. However the video tracki...
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The availability of high quality and inexpensive video camera, as well as the increasing need for automated video analysis is leading towards a great deal of interest in numerous applications. However the video tracking systems is still having many open problems. Thus, some of research activities in a video tracking system are still being explored. Generally, most of the researchers are used a static camera in order to track an object motion. However, the use of a static camera system for detecting and tracking the motion of an object is only capable for capturing a limited view. Therefore, to overcome the above mentioned problem in a large view space, researcher may use several cameras to capture images. Thus, the cost will increases with the number of cameras. To overcome the cost increment a mobile camera is employed with the ability to track the wide field of view in an environment. Conversely, mobile camera technologies for tracking applications have faced several problems; simultaneous motion (when an object and camera are concurrently movable), distinguishing objects in occlusion, and dynamic changes in the background during data capture. In this study we propose a new method of Global best Local Neighborhood Oriented Particle Swarm Optimization (GbLN-PSO) to address these problems. The advantages of tracking using GbLN-PSO are demonstrated in experiments for intelligent human and vehicle tracking systems in comparison to a conventional method. The comparative study of the method is provided to evaluate its capabilities at the end of this paper.
Nowadays, the using of intelligent data mining approaches to predict intrusion in local area networks has been increasing rapidly. In this paper, an improved approach for Intrusion Detection System (IDS) based on comb...
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Nowadays, the using of intelligent data mining approaches to predict intrusion in local area networks has been increasing rapidly. In this paper, an improved approach for Intrusion Detection System (IDS) based on combining data mining and expert system is presented and implemented in WEKA. The taxonomy consists of a classification of the detection principle as well as certain WEKA aspects of the intrusion detection system such as open-source data mining. The combining methods may give better performance of IDS systems, and make the detection more effective. The result of the evaluation of the new design produced a better result in terms of detection efficiency and false alarm rate from the existing problems. This presents useful information in intrusion detection.
This paper presents a new way of online communications through mobile to web that helps students and lecturers to be always aware of appointments no matter where they are. It contributes to the teaching and learning p...
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This paper presents a new way of online communications through mobile to web that helps students and lecturers to be always aware of appointments no matter where they are. It contributes to the teaching and learning process, in which communication is made easy using short messaging system (SMS) technology which is called Web-based Student Appointment System with GSM Network (WASGN). It starts with examples of previous success stories of the implementation of SMS in many areas. The objectives of the paper are to discuss about the hardware and software requirement, and integrate them to be measured in terms of functionality. The research method is outlined next, and some discussions over current outcomes of the research are addressed. The prototype of WAS-GN is successfully implemented using SMS technology. Briefly, results show that WAS-GN is able to solve the appointment-making problem.
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