• Journal of Software Assessment and Valuation
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• v.15 no.1
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• pp.79-86
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• 2019

Software dimension reduction identifies the commonality of elements and extracts important feature elements. So it reduces complexity by simplify and solves multi-collinearity problems. And it reduces redundancy by performing redundancy and noise detection. In this study, we proposed defect severity-based dimension reduction model. Proposed model is applied defect severity-based NASA dataset. And it is verified the number of dimensions in the column that affect the severity of the defect. Then it is compares and analyzes the dimensions of the data before and after reduction. In this study experiment result, the number of dimensions of PC4's dataset is 2 to 3. It was possible to reduce the dimension.

• Journal of Software Assessment and Valuation
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• v.15 no.1
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• pp.1-9
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• 2019

We intend to collect and analyze traffic efficiently in order to detect copyright infringement that illegally share contents on Tor network. We have designed and implemented a Tor traffic collection system using multiple virtual machines. We use a number of virtual machines and Mini PCs as clients to connect to Tor network, and automate both the collection and refinement processes in the traffic collection server through script-based test client software. Through this system, only the necessary field data on Tor network can be stored in the database, and only 95% or more of recognition of Tor traffic is achieved.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.11
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• pp.1169-1174
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• 2015

Risk-Risk-based inspection (RBI) has been developed in order to identify risky equipments that can cause major accidents or damages in large-scale plants. This assessment evaluates the equipment's risk, categorizes their priorities based on risk level, and then determines the urgency of their maintenance or allocates maintenance resources. An earlier version of the risk-based assessment software is already installed within the equipment management system; however, the assessment is based on examination by an inspector, and the results can be influenced by his subjective judgment, rather than assessment being based on failure probability. Moreover, the system is housed within a server, which limits the inspector's work space and time, and such a system can be used only on site. In this paper, the development of independent risk-based assessment software is introduced; this software calculates the failure probability by an analytical method, and analyzes the field inspection results, as well as inspection effectiveness. It can also operate on site, since it can be installed on an independent platform, and has the ability to generate an I/O function for the field inspection results regarding the period for an optimum maintenance cycle. This program will provide useful information not only to the field users who are participating in maintenance, but also to the engineers who need to decide whether to extend the lifecycle of the power machinery or replace only specific components.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.486-490
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• 2003

Software qualify models can predict the risk of faults in the software early enough for cost-effective prevention of problems. This paper introduces a least squares support vector machine (LS-SVM) as a fuzzy regression method for predicting fault ranges in the software under development. This LS-SVM deals with the fuzzy data with crisp inputs and fuzzy output. Predicting the exact number of bugs in software is often not necessary. This LS-SVM can predict the interval that the number of faults of the program at each session falls into with a certain possibility. A case study on software reliability problem is used to illustrate the usefulness of this LS -SVM.

• Journal of Korean Society for Quality Management
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• v.34 no.3
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• pp.73-78
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• 2006

In this paper, we propose a software reliability growth model based on the testing domain in the software system, which is isolated by the executed test cases in software testing. In particular, our model assumes an imperfect debugging environment in which new faults are introduced in the fault-correction process, and is formulated as a nonhomogeneous Poisson process(NHPP). Further, it is applied to fault-detection data, the results of software reliability assessment are shown, and comparison of goodness-of-fit with the existing software reliability growth model is performed.

• Journal of Information Processing Systems
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• v.8 no.2
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• pp.241-262
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• 2012

An understanding of quality attributes is relevant for the software organization to deliver high software reliability. An empirical assessment of metrics to predict the quality attributes is essential in order to gain insight about the quality of software in the early phases of software development and to ensure corrective actions. In this paper, we predict a model to estimate fault proneness using Object Oriented CK metrics and QMOOD metrics. We apply one statistical method and six machine learning methods to predict the models. The proposed models are validated using dataset collected from Open Source software. The results are analyzed using Area Under the Curve (AUC) obtained from Receiver Operating Characteristics (ROC) analysis. The results show that the model predicted using the random forest and bagging methods outperformed all the other models. Hence, based on these results it is reasonable to claim that quality models have a significant relevance with Object Oriented metrics and that machine learning methods have a comparable performance with statistical methods.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.278-283
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• 2024

When implementing software, there can be side effects that pose a threat to human life. Therefore, it is necessary to measure the impact of software on safety and create alternatives to mitigate and prevent threats. To conduct a software safety assessment to measure the impact of threat factors, the following components are necessary. This paper aims to classify the threat factors of software into internal and external factors and quantitatively demonstrate the impact of these threat factors.

• Journal of Software Engineering Society
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• v.29 no.1
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• pp.7-12
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• 2020

As interest in functional safety has recently increased, application of functional safety standards has been required in various industrial fields. A functional safety standard is a document that defines functional safety-related activities required to prevent system malfunctions. All activities defined in this standard are required differentially according to the classification results calculated through the risk analysis and assessment of the system. In the field of domestic weapon systems, there is a manual for the development and management of weapon system software issued by the Defense Acquisition Program Administration (DAPA ). This manual requires static and dynamic analysis of software for functional safety related activities. However, the manual does not specifically address the classification activity through risk analysis and assessment as required for the preceding activities. Therefore, in this study, we analyze the problems of the manual based on the representative functional safety standards, and propose improvement plans.

• Journal of Software Assessment and Valuation
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• v.16 no.1
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• pp.27-36
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• 2020

The software development cost appraisal is treated as a part of the program completion appraisal, and the software engineering methodology is applied. In particular, software cost estimation techniques have been actively applied. For more information about the software development costs calculation, we can refer to the "SW cost estimation guide". Although successful appraisal of a number of development costs based on the guide has been processed, but a number of cases requiring discussion of appraisal results have been discovered. In this study, we propose a use case-based size estimation method to maintain the accuracy and consistency of size estimation. As a result of performing performance evaluation of the proposed method in an environment similar to the development cost appraisal case, it was proved that the accuracy was improved over the existing function points method.

• Journal of Power System Engineering
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• v.20 no.4
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• pp.44-51
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• 2016

An investigation on reliability of reanalysis wind data was conducted using the met mast wind data at four coastal regions, Jeju Island. Shinchang, Handong, Udo and Gangjeong sites were chosen for the met mast sites, and ERA-Interim and MERRA reanalysis data at two points on the sea around Jeju Island were analyzed for creating Wind Statistics of WindPRO software. Reliability of reanalysis wind data was assessed by comparing the statistics from the met mast wind data with those from Wind Statistics of WindPRO software. The relative error was calculated for annual average wind speed, wind power density and annual energy production. In addition, Weibull wind speed distribution and monthly energy production were analyzed in detail. As a result, ERA-Interim reanalysis data was more suitable for wind resource assessment than MERRA reanalysis data.