• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.12
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• pp.21-26
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• 2011

This is a study to establish regulations against light pollution for lighting on roads. Many kinds of light pollution by luminaire on roads was calculated and analyzed by applying the classification method of luminaires(Cut-off classification of IDA-IESNA, BUG Rating Classification) and the calculation method of Upward Lighting Ratio of CIE among measures to prevent light pollution that international lighting organizations suggest. As a result of the analysis, it was found that the regulation by Cutoff of IESNA and ULR classification of CIE could be one for scattered light of light pollution compared to BUG classification but is not sufficient for the regulation of light tresspass or glare. BUG classification by each lighting zone was suggested as threshold value of the light pollution regulation considering domestic conditions.

• Journal of KIISE
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• v.42 no.6
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• pp.755-763
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• 2015

As fixing bugs is a large part of software development and maintenance, estimating the time to fix bugs -bug fixing time- is extremely useful when planning software projects. Therefore, in this study, we propose a way to estimate bug fixing time using bug reports. First, we classify previous bug reports with meta fields by applying a k-NN method. Next, we compute the similarity of the new bug and previous bugs by using data from bug reports. Finally, we estimate how long it will take to fix the new bug using the time it took to repair similar bugs. In this study, we perform experiments with open source software. The results of these experiments show that our approach effectively estimates the bug fixing time.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.866-869
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• 2020

소프트웨어 개발 환경이 빠르게 변화함에 따라 시스템의 복잡성이 증가하고 있다. 이에 따라 크고 작은 소프트웨어의 버그를 피할 수 없게 되며 이를 효율적으로 처리하기 위해 Bug report 를 사용한다. 하지만, Bug report 에서 개발자가 해당 Bug report 의 우선순위를 결정하는 과정은 노력과 비용 그리고 시간을 많이 소모하게 만든다. 따라서, 본 논문에서는 Bug report 내의 Stack trace 를 기반으로 Bug 의 우선순위를 자동적으로 추천하는 기법을 제안한다. 이를 위해 본 연구에서는 첫 번째로 Bug report 로부터 Stack trace 를 추출하였으며 Stack trace 의 3 가지 요소(Exception, Reason 그리고 Stack frame)에 TF-IDF, Word2Vec 그리고 Stack overflow 를 사용하여 특징 벡터를 정의하였다. 그리고 Bug 의 우선순위 추천 모델을 생성하기 위해 4 가지의 Classification 알고리즘을(Random Forest, Decision Tree, XGBoost, SVM)을 적용하였다. 평가에서는 266,292 개의 JDK library 의 Bug report 데이터를 수집하였고 그중 Stack trace 를 가진 Bug report 로부터 68%의 정확도를 산출하였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.235-241
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• 2015

Nowadays, research and industry on the internet of things is rapidly developing. Bug fixed field of the Software development related internet of things is a very important things. In this study, we analyze the properties that can affect what the bug fix-time by analyzing the time required to fix a bug associated with the Internet of Things. Using the k-NN classification method based on the attribute information to be classified as bug reports. Extracts a bug report based on the results of a similar property. Bug fixed by calculating the time of a similar bug report predicts the fix-time for new bugs. Depending on the prediction of the properties that affect the bug correction time, the properties of os, component, reporter, and assignee showed the best prediction accuracy.

• Soft Computing and Machine Intelligence
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• v.1 no.1
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• pp.1-10
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• 2021

Analysis and Tracking of bug reports is a challenging field in software repositories mining. It is one of the fundamental ways to explores a large amount of data acquired from defect tracking systems to discover patterns and valuable knowledge about the process of bug triaging. Furthermore, bug data is publically accessible and available of the following systems, such as Bugzilla and JIRA. Moreover, with robust machine learning (ML) techniques, it is quite possible to process and analyze a massive amount of data for extracting underlying patterns, knowledge, and insights. Therefore, it is an interesting area to propose innovative and robust solutions to analyze and track bug reports originating from different open source projects, including Mozilla and Eclipse. This research study presents an ML-based classification model to analyze and track bug defects for enhancing software engineering management (SEM) processes. In this work, Artificial Neural Network (ANN) and Naive Bayesian (NB) classifiers are implemented using open-source bug datasets, such as Mozilla and Eclipse. Furthermore, different evaluation measures are employed to analyze and evaluate the experimental results. Moreover, a comparative analysis is given to compare the experimental results of ANN with NB. The experimental results indicate that the ANN achieved high accuracy compared to the NB. The proposed research study will enhance SEM processes and contribute to the body of knowledge of the data mining field.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.511-522
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• 2014

During the development of the software, a variety of bugs are reported. Several bug tracking systems, such as, Bugzilla, MantisBT, Trac, JIRA, are used to deal with reported bug information in many open source development projects. Bug reports in bug tracking system would be triaged to manage bugs and determine developer who is responsible for resolving the bug report. As the size of the software is increasingly growing and bug reports tend to be duplicated, bug triage becomes more and more complex and difficult. In this paper, we present an approach to assign bug reports to appropriate developers, which is a main part of bug triage task. At first, words which have been included the resolved bug reports are classified according to each developer. Second, words in newly bug reports are selected. After first and second steps, vectors whose items are the selected words are generated. At the third step, TF-IDF(Term frequency - Inverse document frequency) of the each selected words are computed, which is the weight value of each vector item. Finally, the developers are recommended based on the similarity between the developer's word vector and the vector of new bug report. We conducted an experiment on Eclipse JDT and CDT project to show the applicability of the proposed approach. We also compared the proposed approach with an existing study which is based on machine learning. The experimental results show that the proposed approach is superior to existing method.

• Journal of Korean Medical classics
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• v.23 no.5
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• pp.55-66
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• 2010

The medicinal part of Treasured Mirror of Eastern Medicine("東醫寶鑑" "湯液編") is based on Classified Emergency Materia Medica("證類本草"), Compendium of Prescriptions from the Countryside("鄕藥集成方"). But it distinguished materia medica of countryside(鄕藥) from materia medica of China(唐藥) and properly selected the sentences of them by actual medical circumstances in Korean peninsula. Especially upon assortment of medical herbs, the medicinal part of Treasured Mirror of Eastern Medicine added the part of Water, Earth, Metal, and divided the part of Fish & Bug, Jade & Stone into Fish, Bug, Jade, Stone part. Moreover, it abolished the three grade classification adopted in Classified Emergency Materia Medica, Compendium of Prescriptions from the Countryside and attempted a new approach on itemization; 'representative herb' and 'secondary herb'. Hence, medicinal part of Treasured Mirror of Eastern Medicine should be evaluated as the 'settling in of Chinese medicine with autonomous interpretation, other than 'the fusion of prescriptions from countryside and Chinese medicine.

• Korean Journal of Soil Science and Fertilizer
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• v.15 no.2
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• pp.128-140
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• 1982

The distribution and practical classification of sandy paddy soils, which have the most extensive acreage among low productive paddy soils in Korea and have distinctive improvement effects, were studied to propose a tentative new classification system of sandy textured paddy soils as a means of improving the "Paddy Soil Type Classification" scheme used. The results are summarized as follows; 1. The potential productivity of sandy textured paddy soils was about 86% of normal paddy and the coefficient of variation was relatively high indicating that the properties of soils included were not sufficiently homogeneous. 2. As the poorly drained and halomorphic (> 16 mmhos/cm of E.C. at $25^{\circ}C$) sandy soils are not included in the "Sandy Soil" type according to the criteria of "Soil Type Classification", the recommendation of "adding clay earth" become complicated, and the soil type have to change when the salts washed away or due to ground water table fluctuations. 3. Coarse textured soils were entirely included in the "Sandy Soils" in the tentative criteria of sandy soil classification proposed, and the sandy soils were subdivided into 4 subtypes that is "Oxidized leaching sandy paddy", Red-ox. intergrading sandy paddy", "Reduced accumulating sandy paddy" and "Reduced halomorphic sandy paddy". The system of sandy soil classification proposed were consisted of following categories; Type (Sandy paddy)-Sub-type (4)-Texture family (5)-Soil series (48). 4. The variation of productivities according to the proposed scheme was more homogenized than that of the present device. 5. The total extent of sandy paddy soils was 409, 902 ha (32.3% of total paddy) according to the present classification system, but the extent reached 492,983 ha (38.9%) by the proposed system. The provinces of Gyeong-gi (88.923ha), Jeon-bug (69.717 ha), Gyeong-bug (55.390 ha) have extensive acreage of sandy paddy soils, and the provinces that had high ratio of sandy paddy soils were Gang-weon (58.9%), Gyeong-gi (50.5%), Chung-bug (48.5%), Jeon-bug (41.0%) etc. The ratio was increased by the proposed scheme, e.g. 71.4% in the case of Gang-weon prov. 6. According to the suitability group of paddy soils, the sandy soils mostly belong to 3 class (69.1%) and 4 class (29.2%). Coarse loamy textural family (59.2%) and coarse silty (16.1 %) soils were dominantly distributed. 7. The "Red-ox. intergrading subtype" of sandy paddy pertinent to 49.6% (245,012 ha) while the "Oxidized leaching sub-type" reaches to 33.5% (64,890 ha) and the remained 16.9% (83,081ha) belong to "Reduced accumulating sub-type (14.0%) and "Reduced halomorphic sub-type (2.9%)" according to the proposed scheme.

• Journal of Software Engineering Society
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• v.28 no.1
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• pp.23-28
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• 2019

Recently, in order to effectively test deep neural network model for image processing application, researches have actively conducted to automatically generate data in corner-case that is not correctly predicted by the model. This paper proposes test data generation method that selects arbitrary words from input of system and transforms them into synonyms in order to test the bug reporter automatic assignment system based on sentence classification deep neural network model. In addition, we compare and evaluate the case of using proposed test data generation and the case of using existing difference-inducing test data generations based on various neuron coverages.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.19 no.4
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• pp.347-362
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• 2009

The United Nation agreed to adopt the Globally Harmonized System of Classification and Labelling of Chemicals (GHS) until 2008 to solve the significant differences enough to result in different labels or MSDS for the same chemical in different jurisdictions. Though the GHS is an ideal solution in the respect of pursuing only one format of a MSDS throughout the world, it may cause confusion at the beginning due to lack of information. So the Korean Ministry of Labor (MOL) revised the Industrial Safety and Health Act (ISHA) and related public notice on the classification & labelling of chemicals according to the GHS in 2006. The transition period for the implementation of the GHS for substances was set until Jun 30, 2010, and for mixtures until Jun 30, 2013. To promote the implementation of the GHS in Korea, we developed an application program for constructing MSDS database and a management program for providing MSDS contents on the web in accordance with the GHS. We analyzed the sixteen sections of MSDS by the GHS guideline, and the result showed the necessity to construct logically connected DB for chemical identifier, hazard classification, label, standard phrases and regulatory information. Each section of a MSDS was divided into sub-databases to update the database efficiently. According to Relational Database Management System (RDBMS), the sub-databases were automatically assembled and subsequently a full MSDS is produced. At present, MSDS database for 6,314 substances has been built and provided through internet as the MSDS Editing program. During the service period from January 1 to March 31, 13,666 users have searched MSDSs for 33,401 substances. During program review, some comments about the classification results and other MSDS element sources were reported but no technical bug reported. We expect that the MSDS DB management system in accordance with GHS will accelerate the implementation of the GHS in Korea.