• Journal of KIISE
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• v.45 no.2
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• pp.150-156
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• 2018

Software visualization can assist developers to understand a software system and change its code. The recent development of bottom-up visualization tools demonstrates the advantages by revealing the code that is directly related to a software evolution task. However, the information provided by these tools is limited to the code already investigated by the developers in that task session. To broaden the scope and provide the code information that developers should explore, we propose to present the latest revision of a software system via a class diagram. When a developer clicks on a button, the proposed tool reveals the code changes committed to a configuration management system, and facilitates the understanding of code changes. We also conduct case studies illustrating the advantages of the proposed tool.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.615-621
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• 1999

On the aspect of on-time and development resource use, it is very important to predict the software release time during the software development process. In this paper, we present the optimal release problem based on the evaluation indicator and cost evaluation. And also we show the optimal release point considered with both of them. We applied the Exponential Software Reliability Growth Model(E-SRGM) and Testing-effort dependent Software Reliability Growth Model(Te-SRGM) and decided the software release time according to software reliability indicator. As a result of two models comparison, we verify the Te-SRGM is more adopted in our switching system software.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3110-3125
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• 2014

Network coding improves TCP's performance in lossy wireless networks. However, the complex congestion window evolution of network coded TCP (TCP-NC) makes the analysis of end-to-end throughput challenging. This paper analyzes the evolutionary process of TCP-NC against lossy links. An analytic model is established by applying a two-dimensional Markov chain. With maximum window size, end-to-end erasure rate and redundancy parameter as input parameters, the analytic model can reflect window evolution and calculate end-to-end throughput of TCP-NC precisely. The key point of our model is that by the novel definition of the states of Markov chain, both the number of related states and the computation complexity are substantially reduced. Our work helps to understand the factors that affect TCP-NC's performance and lay the foundation of its optimization. Extensive simulations on NS2 show that the analytic model features fairly high accuracy.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.2
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• pp.99-113
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• 2010

Beyond the rapid normalization process of patents in software industry, complex legal evolution and rigorous economic arguments underlie the crucial environmental transformation of the industry. In this article, we trace the evolutionary history for the theory and practice of patents in software industry from both legal and economic perspectives. First, we study the legal disputes and cases in light with the underpinnings of patent policy transformation, and then delve into the economic backrounds of the pros and cons for software patents, with special focus on the generic economic peculiarities of software industry. The fact that historical and practical policy and law in Korea have been largely affected from those of USA, and relative deficiency in the law, economics and management literature are the main motivation of the study, and we hope this study to contribute to the decision making of policymakers as well as law and business practitioners.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.495-504
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• 2008

Aspect Oriented Programming(AOP) is a relatively new programming paradigm and has properties that other programming paradigms don't have. This new programming paradigm provides new modularization of software systems by cross-cutting concerns. In this paper, we propose a regression test method for program evolution by AOP. By using JoinPoint, we can catch a pointcut-name which makes it possible to test the incorrect pointcut strength fault and the incorrect aspect precedence fault. Through extending proof rules to aspect, we can recognize failures to establish expected postconditions faults. We can also trace variables using set() and get() pointcut and test failures to preserve state invariant fault. Using control flow graph, we can test incorrect changes in control dependencies faults. In order to show the correctness of our proposed method, channel management system is implemented and tested by using proposed methods.

• Journal of Ecology and Environment
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• v.31 no.2
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• pp.89-95
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• 2008

Sensing the approach of a predator is critical to the survival of prey, especially when the prey has no choice but to escape at a precisely timed moment. Escape behavior has been approached from both proximate and ultimate perspectives. On the proximate level, empirical research about electrophysiological mechanisms for detecting predators has focused on vision, an important modality that helps prey to sense approaching danger. Studies of looming-sensitive neurons in locusts are a good example of how the selective sensitivity of nervous systems towards specific targets, especially approaching objects, has been understood and realistically modeled in software and robotic systems. On the ultimate level, general optimality models have provided an evolutionary framework by considering costs and benefits of visually elicited escape responses. A recent paper showed how neural network models can be used to understand the evolution of visually mediated antipredatory behaviors. We discuss this new trend towards integration of these relatively disparate approaches, the proximate and the ultimate perspectives, for understanding of the evolution of behavior of predators and prey. Focusing on one of the best-studied escape pathway models, the Orthopteran LGMD/DCMD pathway, we discuss how ultimate-level optimality modeling can be integrated with proximate-level studies of escape behaviors in animals.

• Geomechanics and Engineering
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• v.20 no.1
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• pp.29-41
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• 2020

It is extremely important to obtain rock strength parameters for geological engineering. In this paper, the evolution of sandstone cohesion and internal friction angle with plastic shear strain was obtained by simulating the cyclic loading and unloading tests under different confining pressures using Particle Flow Code software. By which and combined with the micro-crack propagation process, the mesoscopic mechanism of parameter evolution was studied. The results show that with the increase of plastic shear strain, the sandstone cohesion decreases first and then tends to be stable, while the internal friction angle increases first, then decreases, and finally maintains unchanged. The evolution of sandstone shear strength parameters is closely related to the whole process of crack formation, propagation and coalescence. When the internal micro-cracks are less and distributed randomly and dispersedly, and the rock shear strength parameters (cohesion, internal friction angle) are considered to have not been fully mobilized. As the directional development of the internal micro-fractures as well as the gradual formation of macroscopic shear plane, the rock cohesion reduces continuously and the internal friction angle is in the rise stage. As the formation of the macroscopic shear plane, both the rock cohesion and internal friction angle continuously decrease to a certain residual level.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.1
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• pp.29-38
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• 1998

We summarize, in this paper, that we have learned from the slftwar reliability analysis of a large switching software composed of functional blocks which form slotware units. To determine the time of management activity related to sopftware reliability growth, we review the process of detection and correction of software failures. Also we apply the two softwre reliability frowth model, Goel-Okumoto and S-shaped model, to estimate the global software reliability growth to a set of failure found during period of the system test. The analysis methods and results can be applied to other large software development projects.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.164-173
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• 2009

Automotive systems have tended to be equipped with many electronic contents to satisfy safety, comport, convenience, and entertainment services over the past years. As a result, the amount of vehicle embedded software in electrical/electronic(E/E) systems is steadily increasing to manage these requirements. This leads to the traditional, document-based software development in the vehicle embedded systems being increasingly displaced by a model-based development in order to reduce software development time and cost. Due to the application of model-based development, a great evolution is being realized in the aspect of efficiency, but the development is being made without sufficient testing. So, erroneous automotive embedded software may cause serious problems such as car accidents which relate to human safety. Therefore, efficient methods for model-based test and validation are needed to improve software reliability in the stage of embedded software development. This paper presents the model-based development and test method for AUTOSAR embedded software to improve its reliability and safety, and it is demonstrated based on the case study.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.232-240
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• 2022

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.