Earticle

A challenging part of software testing entails the generation of test cases. A good test case should have the quality to cover more features of test objective. The techniques for automatic generation of test cases try to efficiently find a small set of cases that allow an adequacy criterion to be fulfilled, thus reducing the cost of software testing and resulting in more efficient testing of software products. In this paper we introduce an all-around classification framework for automatic test case generation approaches in terms of test type and Algorithm, and represent some test case evaluation approaches. Finally we illustrate a comparison between different existing techniques.

We propose a regression test selection technique that is based on analysis of both the source code of an object-oriented program as well as the UML state machine models of the affected classes. We first construct a dependency graph model of the original program from the source code. When the program is suitably modified, the constructed model is updated to reflect the changes. Our model in addition to capturing control and data dependencies represents the dependencies arising from object-relations. To find the model elements affected due to a program change, we construct a forward slice of the constructed graph model, where each changed model element is used as a slicing criterion. Subsequently, we determine the affected methods from an analysis of the state machine models based on the changed statements. The test cases that exercise the affected model elements in the program model as well as the transitions caused by the affected methods in state machine models are selected for regression testing. Empirical studies carried out by us show that our technique selects on an average of 27.89 % more fault-revealing test cases compared to a purely dependence graph model-based technique while incurring about 38.21% increase in regression test suite size.

Various models for software reliability prediction were proposed by many researchers. In this work we present a hybrid approach based on the Neural Networks and Simulated Annealing. An adaptive simulated Annealing algorithm is used to optimize the mean square of the error produced by training the Neural Network, predicting software cumulative failure. To evaluate the predictive capability of the proposed approach various projects were used. A comparison between this approach and others is presented. Numerical results show that both the goodness-of-fit and the next-step-predictability of our proposed approach have greater accuracy in predicting software cumulative failure compared with other approaches.

Developing a system architecture that satisfies the functional requirements and keeping the quality attributes high is still an open challenge.The task of selecting the optimal combination and redundancy levels of components (which is known as RAP problem) that meet system-level constraints is hard since each one of these alternatives must be modeled in order to obtain the global optimal solution. This problem is classified as NP-complete and many researches have suggested use of metaheuristic to encode this challenge as an optimization problem for improving architectures. The search for optimal solution in metaheuristics techniques is guided by objective function/functions. Majority of studies in RAP area were focused on reliability and mostly simple cost functions were used. An adopted cost-with-discount function is proposed in this paper to increase the efficiency of the approach within especial conditions. Single Objective - Particle Swarm Optimization (SO-PSO) to automatically generate and to evaluate architecture is implemented in order to support design decision. The Anti-lock Breaking System (ABS) has been used as a case study to motivate, demonstrate the applicability, and to validate the study. And statistical t-test is performed to evaluate the approach. The evaluation of the approach has proven that; it is significantly impact on providing an efficient solution and it can be used to assist architectures to easily achieve their objectives since they can decide on the automatically provided design options according to technical and financial inclinations.

This paper discussed the past works on fraud detection system and highlights their deficiencies. A probabilistic based model was proposed to serve as a basis for mathematical derivation for adaptive threshold algorithm for detecting anomaly transactions. The model was optimized with Baum-Welsh and hybrid posterior-Viterbi algorithms. A credit card transactional data was simulated, trained and predicted for fraud. And finally, the proposed model was evaluated with different metric. The results showed that with the optimization of parameters, posterior-Viterbi cum new detection model performed better than Viterbi cum old detection model.

In this paper, we have studied the notion of atomicity in message-passing distributed programs. The difference between the notion of atomicity in shared memory programs and messagepassing programs has been discussed in detail. Due to the nature of communication in messagepassing programs, the atomicity requirement in shared memory programs (serializability) does not guarantee the same level of atomicity in message-passing programs. We have referred to the atomicity level guaranteed by the serializability requirement in message-passing programs as the weak atomicity. We have defined the requirements that guarantee a level of atomicity in message-passing programs similar to that in shared memory programs. We have referred to it as the strong atomicity requirement. Both of weak and strong atomicity have been formally defined. The notion of atomicity can be employed to significantly reduce the state space to be considered in verification. Moreover, atomicity violations in a run typically indicate the presence of program bugs. Consequently, the concepts presented in this paper can be exploited to reduce the cost of the verification of message-passing distributed programs.

Service Oriented Architecture (SOA) is generally defined as a business-centric IT architectural approach that supports integrating businesses as linked, repeatable business tasks, or services. The successful deployment of SOA implementation in any enterprise is ensured by testing of applications. An inspection of recent research achievements related to SOA testing is present in this paper. Testing challenges from the viewpoint of different stakeholders along with different levels of testing, including unit, integration, end to end and regression testing are analyzed. Further the ways to improve functional testing of SOA applications created using Web Services is explored.

The chauffeur service system in a city is one of the most popular services, especially at night. This system provides a substitutive driver for people who can’t drive their car when they drink generally. But traditional chauffeur service system did not provide any driver’s information for service requester(user) whether the driver committed traffic accident, crimes or have car insurance. Thus the traditional system may not be user-centric one but service provider. The proposed system provides this information including drivers position on users mobile device such as smart phones and tablet PCs. Then, user can select a driver of some drivers who are displaying including this information and their position on mobile device. Thus the proposed system is what we call user-centric one. This paper implements a new chauffeur service system with the Google map API.

In order to avoid the risk caused by continuously changing option value, option issuers generally utilize the traditional Dynamic Delta Hedging (DDH) method. DDH tries to maintain risk-neutral position by adjusting hedge position according to the delta by Black-Scholes (BS) model. DDH, however, is not able to guarantee optimal hedging performance due to some impractical assumptions inherent in BS model. Therefore, this study presents a methodology for dynamic option hedging strategy using artificial neural network (ANN) to enhance hedging performance and shows the superiority of the proposed method through computational experiments.

The Software product line engineering is an inter-disciplinary concept. It spans the dimensions of business, architecture, process, and the organization. Similarly, Educational System engineering is also an inter-disciplinary concept, which spans the dimensions of academic, infrastructure, facilities, administration etc. Some of the potential requirements and benefits of this engineering approach includes continuous improvements in educational quality and adhering to global standards. The increasing competency in IT and Educational Sectors necessitates a process maturity evaluation methodology for educational organization. Accordingly, this paper presents a new quality educational capability maturity model for evaluating the maturity of multi - dimension factors and attributes of an Educational System. Assessment questionnaires and a rating methodology comprise the framework of this Capability maturity model for quality Education (CMM-QE). The objective and design of the questionnaires are to collect information about the Education system engineering process from the multi perspectives of academic, infrastructure, administration, facilities etc. This model is validated using PLS-Graph tool, and the organizational maturity is validated by classifying the educational institutions into different levels by applying k-means Cluster analysis using SPSS and finally it is ranked for its maturity level accordingly.

In this paper, the structural information between tree nodes of XML documents is represented without any structural changes of the tree by converting that number information added to the tree into bit streams. It is also shown that other structural information can be retrieved and added to index schema in the process. In this process, we confirm that the response time can be minimized by conducting a bit operation between the bit streams with index schema in use, and accurate results can be reached by searching only with information of record sets by nodes in index files.

This paper proposes a method for effectively implementing the pyramid strategy. The pyramid strategy is based on the short strangle strategy and adopts the multiple-entry approach. Risk management is an essential element of derivatives trading, and the pyramid strategy is very efficient because it combines mutual and dynamic hedging. However, in operating the pyramid strategy, choosing a specific exercise price results in significant differences in terms of profitability and stability. This paper analyzes theta—measurement of decreasing time-value of an option—to propose a method for achieving profitability and stability simultaneously. The proposed approach involves adding stability by selecting deep out-of-the-money (OTM) options in early monthly contracts, and moving to near OTM options with high theta values in late monthly contracts to pursue profitability. To verify the validity of the proposed method, automatic strangle trades was simulated based on real data of Korean option information system. The simulation was performed using the multi-chart automatic trading analysis tool. The results of simulation using April 2012 contracts confirmed that the proposed method produces higher returns and offers greater stability than conventional methods.

The redundant components' nodes are widely used as design tactic to improve the reliability of complex embedded systems. The challenge is that; the obtained solution might not be sufficient because it demands high cost, and the system might be failed if the predicted cost does not estimated reasonably. Many publications have addressed this area to compose the systems by assembling COTS components only. However, combination of outsourced components and in-house developed components is essential to produce cost effective systems. This paper proposes an architecture optimization approach based on Metaheuristic Swarm Intelligent algorithm in order to answer the question: What type of components to be selected and how many components are appropriate for each subsystem in order to obtain optimal software architecture. The objective is to minimize cost under reliability constraints by combining components from different sources in order to compose system that satisfies the requirements. Sensitivity analysis applied on a numerical simple case study showed the potentiality of the approach.

Transmission Control Protocol (TCP) is widely used for the transport layer protocol in most Internet and Intranet applications. The link characteristics of a specific link environment such as satellite has been limited and degraded by its link characteristics. To address such limitations Performance Enhancing Proxies (PEPs) have been designed and introduced to improve the operation of internet and intranet protocols in certain environments where a link or subnet suffers performance degradation with high error rates and with low bandwidths. This paper discuss the overview of PEPs together with the problems and drawbacks of such technologies to improve the degraded performance of TCPs. Based on the identified limitations of the currently developed and designed PEPs, we have integrated some mechanism for the improvement of the handover latency, thus enhancing its performance. Some steps with the handover procedure have been modified applying the benefits splitting and spoofing techniques resulting with a better performance and shorter handover latency. An enhanced packet buffering transmission module was introduced to boost the packet transmission performance in terms of efficiency.

Computer Assisted Language Learning (CALL) has not been so successful up to date. A potential reason for this is that the gap between theoretical assumptions and reality was larger than researchers and practitioners thought. For the development of usable and realistic systems, it is crucial to be aware of practices in reality rather than theoretical and technical judgements. This paper presents a questionnaire study to help understand practices with computers in terms of learning English among Korean university students. Concerning IT usage of studying English, the results show that about a half of the participants have utilized IT, and VOD lectures are a major method at present, and vocabulary learning tools are also popular including electronic dictionaries. While learners began to use smart phone application, learning English with social network services is not common yet. Though technological aids are crucial, however, participants also pointed out that learners’ willingness or interest in learning English is the most important factor affecting English study. Emphasizing that both human/social and technological aspects should be understood simultaneously to build better systems, we hope that the results shed some light on the development of more realistic and practical CALL in English as a foreign language (EFL).

For a library to be able provide information services and fulfill its function as a knowledge convergence center capable of responding to various information demands, the development of next-generation information systems based on the latest information and communication technology is needed. The development of mobile information services using portable devices such smart phones and tablet PCs and information systems which incorporate the concepts of cloud computing, SaaS (Software as a Service), annotation and Library2.0 is also required. This paper describes a library information system that utilizes collective intelligence and cloud computing. The information system developed for this study adopts the SaaS-based cloud computing service concept to cope with the shift in the mobile service paradigm in libraries and the explosion of electronic data. The strengths of such a conceptual model include the sharing of resources, support of multi-tenants, and the configuration and support of metadata. The user services are provided in the form of software on-demand. To test the performance of the developed system, the efficiency analysis and TTA certification test were conducted. The results of performance tests, It is encouraging that, at least up to 100MB, the job time is approximately linear and with only a moderate overhead of less than one second. The system also passed the level-3 or higher criteria in the certification test, which includes the SaaS maturity, performance and application program functions.

Random forests are known to be robust for missing and erroneous data as well as irrelevant features. Moreover, even though the forests have many trees, they can utilize the fast building property of decision trees, so they do not require much computing time. In this paper an efficient procedure that utilizes random forests to predict the cylinder bands in rotogravure printing is shown. Even though several research results have been published already to find better prediction accuracy based on other methods, a new and very good result has been found with the suggested method having appropriate parameters of random forests.

Recently, according to increasing the network traffic in the IMS, the role of Network Management System (NMS) is very important because of limited network resource. It can perform two kinds of routing ways with the capability of static or dynamic routing. A dynamic routing way is more efficient than static routing one because it can make the flow of traffic changeful among nodes in the IMS. Therefore, in this paper, we suggest a management function of NMS, applying a dynamic routing algorithm for managing the CSCFs in the IMS. And then we analyze the algorithm by measuring the performance of PoC and presence service one of the prominent application services to be deployed in the IMS.

To overcome the poor communication environment between the underwater acoustic signal transmitter and receiver, previous research applied underwater acoustic OFDM communication system which had efficient bandwidth capacity and could mitigate multi-path delay spread effect via guard interval. Concurrently with this OFDM signal, additional data could be transmitted through spread spreading technique, which was called water-line technique. However, this decreased the performance of the OFDM modulation because the water-line signal degraded OFDM signal. In this paper, we studied the efficient method to minimize signal interference by water-line signal so that we applied convolution error correction code on water-line to minimize signal level.

This paper proposes a problem-based digital textbook (DT) by defining an instructional model of problem-based learning (PBL) for DTs. The objective was to develop a DT that stimulates self-directed learning through the support of a wide range of student-centered learning activities to enhance the overall learning experience and effectiveness. As an application, a problem-based DT that performs PBL according to the proposed instructional model was developed for the subject of general computing used by high schools in South Korea. For the experiment, the DT was applied to practical classes for one semester at a commercial high school and there were generally very positive responses and enhanced problem-solving achievement.

Most library systems use the client/server and ASP services for their software. However, such systems are difficult to manage and incur high operating costs because of the problems related to high HW and SW purchasing costs, installation and distribution, customization, upgrade, fault and problem management, and costly license royalties. To solve such problems, this study developed the key elements that can be deployed in the SaaS-based digital library system supporting the multi-tenant environment (SaaS maturity level 3 or higher). The system was deployed with the SaaS-based software on-demand type service model, which requires little initial investment, is simple and easy to use, and delivers the IT service at a low cost. The system proposed in this paper features multi-tenant-oriented application resource sharing and optimization, multi-tenant-oriented data space sharing and isolation, multitenant- oriented back-end data management, and isolated multi-tenant-oriented hosting in order to solve many problems of the existing problems.

Grid computing is a promising technology for future computing platforms and is expected to provide easier access to remote computational resources that are usually locally limited. Scheduling is one of the core steps to efficiently exploit the capabilities of grid computing (GC) systems. The problem of optimally mapping (defined as matching and scheduling) tasks onto the machines of a grid computing environment has been shown, in general, to be NPcomplete, requiring the development of heuristic techniques. The efficient scheduling of independent tasks in a heterogeneous computing environment is an important problem in domains such as grid computing. Different criteria can be used for evaluating the efficiency of scheduling algorithms, the most important of which are makespan, resource utilization and matching proximity. In this paper we will compare 7 popular heuristics for statically mapping independent tasks onto grid computing systems.

With the development of cloud computing and virtualization technologies, application virtualization becomes an innovative software usage model. However, the existing solutions show a very limited performance on 3D graphics applications. To solve the problems, we propose a new application virtualization mechanism using separated software execution system. The proposed system does not execute 3D rendering commands or graphic commands of the 3D graphics application at the hosted server but delivers them to client via the Internet and executes them using the client’s graphic device. This mechanism enhances the hosted server’s performance for desktop virtualization service of 3D rendering applications. In performance experiment, the proposed method showed good scalability and obtained a more stable frame rate than the existing desktop virtualization solutions.

Although there are various kinds of mobile application technologies, users spend time with their smartphone mostly surfing the Internet, playing games, and communicating with their friends because the computing power of smartphone still lags behind other devices in terms of resources such as CPU, memory, etc. Furthermore, in many cases, users can’t easily find suitable mobile applications without implementing them by themselves, because it’s very difficult and takes much effort to implement a mobile application. So in this paper, we propose MCSC, a mobile collaborative service cloud for Android and iOS which requires less computing power while providing rich functionalities. While implementing an application using native language takes significant time and requires a specialized skill set, using our proposed service cloud, users can implement new mobile applications easily and quickly using instant adaptive orchestration and Mashup. MCSC facilitates the use of other devices’ resource and context information such as contact lists, location, etc. We evaluated MCSC in several scenarios, and confirmed that it performs as fast as native mobile applications and works well in heterogeneous environments incorporating both Android and iOS devices. In the future, MCSC will create new opportunities for mobile cloud computing and service oriented architecture.

Information-Centric Network (ICN) is a new paradigm, which solve the limitations of the IP network architecture. The one of the advantage in ICN is that it reduces network traffic by using in-network caching. The caching is an important element of the ICN, because the factor that leads to efficient usage of network resources is the high hit ratio of a cache in a router. In this paper, we consider social influence in cache replacement policy over ICN. The social influence makes a decision based on the Social Network Service (SNS) application. This paper proposes a new cache replacement policy by social influence of user in SNS over ICN. The proposed algorithm is able to reduce network resource than existing ICN.