• Journal of Information Processing Systems
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• v.15 no.4
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• pp.967-985
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• 2019

Bug report processing is a key element of bug fixing in modern software maintenance. Bug reports are not processed immediately after submission and involve several processes such as bug report deduplication and bug report triage before bug fixing is initiated; however, this method of bug fixing is very inefficient because all these processes are performed manually. Software engineers have persistently highlighted the need to automate these processes, and as a result, many automation techniques have been proposed for bug report processing; however, the accuracy of the existing methods is not satisfactory. Therefore, this study focuses on surveying to improve the accuracy of existing techniques for bug report processing. Reviews of each method proposed in this study consist of a description, used techniques, experiments, and comparison results. The results of this study indicate that research in the field of bug deduplication still lacks and therefore requires numerous studies that integrate clustering and natural language processing. This study further indicates that although all studies in the field of triage are based on machine learning, results of studies on deep learning are still insufficient.

• 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.

• Proceedings of the Korean Society for Quality Management Conference
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• 2010.04a
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• pp.283-290
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• 2010

This paper suggest that the derivation of good and practical ideas is important for the successful use of Kano model. Wish List, Bug List and Forced Connection Method as well as Brainstorming were applied to PMP(Portable Multimedia Player) in order to derive customer attributes. Wish List and Bug List are variants of Brainstorming, which are contrary to each other. Forced Connection Method is designed to bring about bisociation which is a typical characteristic of creative thinking.

• 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.

• Information Systems Review
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• v.1 no.1
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• pp.63-73
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• 1999

• International journal of advanced smart convergence
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• v.8 no.4
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• pp.207-213
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• 2019

Assistance for the quality assurance management and developers to provide high quality software products. Using a bug record keeping system is exceptionally important in software progress, and it is followed vastly by majority of software producing companies in modern era. Regular application of a bug record keeping system is very helpful in developing software systems. We developed this system which helps the software testing team to keep a complete record of their testing activities during the software testing, also increases your confidence in the software quality, class and worth. Our proposed system offers trouble-free and effortless approaches to acquire desired information about bug, also produces different kinds of reports like summary reports, detailed reports etc. It gives facility to create, delete and update any project. Our developed application system is designed by using visual c# at front end and sql server 2008 management studio express at back end.

• Korean Journal of Organic Agriculture
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• v.21 no.4
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• pp.685-699
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• 2013

This study was evaluated the effect of attractant or repellent plants for establishing push-pull strategy for insect pest management of organic Chinese cabbage cultivation. The attractant or repellent effect of Ten plants, marigold, rye, Chinese chive, lettuce, chicory, Nongwoo-chicory, crown daisy, Treviso, green leaf mustard, and red leaf mustard were evaluated against diamondback moth, striped flea beetle, aphids, brown-winged stink bug and cabbage stink bug in organic Chinese cabbage field in Seosan in 2012. Of the ten repellent or attractant plants, rye and chicory attracted significantly brown-winged stink bug and cabbage stink bug, respectively. Aphids ate attracted significantly to the rye rather than the other plants. Leaf mustard was attracted cabbage stink bug and brown-winged stink bug in order. Cabbage stink bug was attracted by only a combination of lettuce and Chinese chive. Diamondback moth, striped flea beetle, aphid, brown-winged stink bug and cabbage stink bug were significantly repelled by single or combined cultivation of crown daisies, Treviso, and leaf mustard in organic Chinese cabbage cultivation. The results above-mentioned indicate that selected insect-attractant and -repellent plants can be used as tools for integrated pest managements of Chinese cabbage.

• Proceedings of the Korean Society of Crop Science Conference
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• 2003.10a
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• pp.52-53
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• 2003

• Journal of Korean Society for Quality Management
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• v.39 no.2
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• pp.305-312
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• 2011

Kano model has been widely used to identify and classify customer attributes of a product or a service. The first step of Kano model application is the derivation of customer attributes, and brainstorming has been used conventionally for the purpose. A typical advantage of brainstorming is to get many ideas in a relatively short period, but the practicability of the derived ideas are known to be not so good. The derivation of good and practical ideas is important for the successful use of Kano model. Wish list, bug list and forced connection method as well as brainstorming were applied to PMP(Portable Multimedia Player) in order to derive customer attributes. To compare the idea generation methods, the derived attributes are classified and compared using Kano model.

• Journal of the Korea Safety Management & Science
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• v.2 no.1
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• pp.77-87
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• 2000

BOM has been widely used to manufacturing, product design and scheduling. There are several bug differences between Manufacturing BOM and Engineering BOM, which cause a lot of problems. A study to integrate both manufacturing BOM and Engineering BOM is researching to solve those problems. Therefore, this research presents a extended Engineering BOM concepts considering assembly sequence model.