• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.741-750
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• 2011

In this paper, we derive an software mixed debugging model based on a Markov process, assuming that the length of time to perform the debugging is random and its distribution may depend on the fault type causing the failure. We assume that the debugging process starts as soon as a software failure occurs, and either a perfect debugging or an imperfect debugging is performed upon each fault type. One type is caused by a fault that is easily corrected and in this case, the perfect debugging process is performed. An Imperfect debugging process is performed to fix the failure caused by a fault that is difficult to correct. Distribution of the first passage time and working probability of the software system are obtained; in addition, an availability function of a software system which is the probability that the software is in working at a given time, is derived. Numerical examples are provided for illustrative purposes.

• Communications for Statistical Applications and Methods
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• v.19 no.4
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• pp.571-577
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• 2012

Modules that consist of software are respectively coded in the early development phase and the modules are unified as a software. After unification, the software is repeatedly tested with a given taskset (the set of module tasks that are tested simultaneously) until a required performance level is satisfied. In this paper, we expand the one-module software debugging model of Jang and Lee (2011) to a multi-module debugging model and derive the taskset completion probability and the mean of the completed tasksets under the assumption that the processing times of module tasks given in a taskset are mutually dependent.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.219-226
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• 2016

In this paper, we propose an efficient repository model for online software education. The software education of app development consists of 7 stages: coding & debugging, submit, collaboration, review, validate, deployment, certification. Proposed repository model supports all 7 stages efficiently. In the coding & debugging stage, the students repeat coding and debugging of source. In the submit stage, the output of previous process such as source codes, project, and videos, are uploaded to repository server. In the collaboration stage, other students or experts can optimize or upgrade version of source code, project, and videos stored in the repository. In the review stage, mentors can review and send feedbacks to students. In the validate stage, the specialists validate the source code, project, and the videos. In the deployment stage, the verified source code, project, and videos are deployed. In the certification stage, the source code, project, and the videos are evaluated to issue the certificate.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.576-580
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• 2010

Generally, due to the strong coherence between embedded software and hardware or peripheral software, embedded software is tested by using black-box test based on user scenario for the whole system. This paper suggests the method to coordinate between testing and debugging under consideration for difficulties on solving out the defects detected from black-box test. First of all, from test result analysis, it builds up the debugging strategies enable to trace the locations of the defect's causes. And along with the strategies, it implements the generator of test scripts to be performed on the emulator environment. Through these steps, it can coordinate embedded software testing and debugging activities.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.57-64
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• 2000

In this paper we consider a Markovian perfect debugging model for which the software failure is caused by two types of faults, one which is easily detected and the other which is difficult to detect. When a failure occurs, a perfect debugging is immediately performed and consequently one fault is reduced from fault contents. We also treat the debugging time as a variable to develop a new debugging model. Several measures, including the distribution of first passage time to the specified number of removed faults, are also obtained using the proposed debugging model, Numerical examples are provided for illustrative purposes.

• The KIPS Transactions:PartD
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• v.9D no.4
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• pp.659-666
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• 2002

Park, Seo and Kim (12) developed the input domain-based SRGM, which was able to quantitatively assess the reliability of a software system during the testing and operational phases. They assumed perfect debugging during testing and debugging phase. To make this input domain-based SRGM more realistic, this assumption should be relaxed. In this paper we generalize the input domain-based SRGM under imperfect debugging. Then its statistical characteristics are investigated.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6A
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• pp.589-599
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• 2004

Most models assume the complete debugging environments by requiring a complete software correction in quantitative evaluation of software reliability. But, in many case, new faults are involved in debugging works, for complete software correction is impossible. In this paper, software growth model is proposed about incomplete debugging environments by considering the possibility of new faults involvements, and software faults occurrence status are also mentioned about NHPP by considering software faults under software operation environments and native faults owing to the randomly involved faults in operation before test. While, effective quantitative measurements are derived in software reliability evaluation, applied results are suggested by using actual data, and fitnesswith existing models are also compared and analyzed.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.891-898
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• 2010

In real software development fields, software is unified by several modules that are developed before the software testing period. For the evaluation of software task processing performance, this paper considers the software imperfect debugging model that is proposed by Lee and Park (2003) and presents the measures of a unified software, such as the completion probability of a task which is completed in a time interval and the expected number of the completed tasks. In addition, we suggest a software release policy that satisfies the required level of the expected perfect debugging, completion probability, and availability.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.396-402
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• 2005

The software reliability growth model(SRGM) has been developed in order to evaluate such measures as remaining fault number, fault rate, and reliability for the developing stage software. Most of the study literatures assumed that this detecting efficiency was perfect. However the actual fault detecting is generally imperfect, and widely known to many persons. It is not easy to develop and remove the fault existing in the software because the fault finding is difficult, and the exact solving method also not easy, and new fault may be introduced depending on the tester's capability. There, the fault removing efficiency influences the software reliability growth or developing cost of software. It is a very useful measure throughout the developing stage, much helpful for the developer to evaluate the debugging efficiency, and evaluate additional workload. Hence, the study for the imperfect debugging is important in point of software reliability and cost. This paper proposes that the fault debugging is imperfect and new fault may be introduced for the developing software during the developing stage.

• Journal of Korean Society for Quality Management
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• v.23 no.3
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• pp.57-68
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• 1995

In this paper, we consider possibility that the multiple errors occur in each testing stage. At present, software reliability modeling is considered as a part of software reliability quality assurance in software engineering. However they dealt with the software growth model for the single error debugging at each testing stage until now. Hence it is necessary to study software reliability with multiple errors debugging. Therefore we propose software reliability growth modeling and estimate the parameters in the proposed software reliability growth model for the multiple errors debugging at each testing stage.