Sungwon Kang

Prof. Dr. Sungwon Kang

School of Computing, Korea Advanced Institute of Science & Technology, 291 Daehak-ro, Eoeun-dong, Yuseong-gu, Daejeon, Korea
orcid

Research Focus & Metrics

Academic Career Length

15Years (2012-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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25 February 2019 in IEEE Transactions on Software Engineering
Verified
Journal Article
Closed access
Seonah LeeSeonah Lee
Seonah Lee
RWRongxin Wu
Rongxin Wu
SCShing-Chi Cheung
Shing-Chi Cheung
SKSungwon Kang
Sungwon Kang
Application programming interfaces (APIs) continually evolve to meet ever-changing user needs, and documentation provides an authoritative reference for their usage. However, API documentation is commonly outdated because nearly all of the associated updates are performed manually. Such outdated documentation, especially with regard to API names, causes major software development issues. In this paper, we propose a method for automatically updating outdated API names in API documentation. Our insight is that API updates in documentation can be derived from API implementation changes between code revisions. To evaluate the proposed method, we applied it to four open source projects. Our evaluation results show that our method, FreshDoc, detects outdated API names in API documentation with 48% higher accuracy than the existing state-of-the-art methods do. Moreover, when we checked the updates suggested by FreshDoc against the developers? manual updates in the revised documentation, FreshDoc addressed 82% of the outdated names. When we reported 40 outdated API names found by FreshDoc via issue tracking systems, developers accepted 75% of the suggestions. These evaluation results indicate that FreshDoc can be used as a practical method for the detection and updating of API names in the associated documentation.

1 June 2020 in Information and Software Technology
Verified
Journal Article
Closed access
JLJihyun Lee
Jihyun Lee
SKSungwon Kang
Sungwon Kang
PJPilsu Jung
Pilsu Jung

1 December 2019 in Journal of Systems and Software
Verified
Journal Article
Closed access
PJPilsu Jung
Pilsu Jung
SKSungwon Kang
Sungwon Kang
JLJihyun Lee
Jihyun Lee

1 December 2014 in Journal of Systems and Software
Verified
Journal Article
Closed access
HAHamad I. Alsawalqah
Hamad I. Alsawalqah
SKSungwon Kang
Sungwon Kang
JLJihyun Lee
Jihyun Lee

4 December 2020 in Applied Sciences
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Journal Article
Open access
PDF file
PJPilsu Jung
Pilsu Jung
SKSungwon Kang
Sungwon Kang
JLJihyun Lee
Jihyun Lee
Regression testing for software product lines (SPLs) is challenging because it must ensure that all the products of a product family work correctly whenever changes are made. One approach to reducing the cost of regression testing is the regression test selection (RTS), which selects a subset of regression test cases. However, even when RTS is applied, SPL regression testing can still be expensive because, in the product line context, each test case can be executed on more than one product that reuses the test case, which would typically result in a large number of test executions. A promising direction is to eliminate redundant test executions of test cases. We propose a method that, given a test case, identifies a set of products, on which the test case will cover the same sequence of source code statements and produce the same testing results, and then excludes these products from products to apply the test case to. The evaluation results showed that when the full selection approach and the approach of repetitively applying an RTS method for a single software system are used for test selection, our method reduced, respectively, 59.3% and 40.0% of the numbers of test executions of the approaches.

11 December 2019 in Applied Sciences
Verified
Journal Article
Open access
PDF file
BKBeomJun Kim
BeomJun Kim
SKSungwon Kang
Sungwon Kang
Seonah LeeSeonah Lee
Seonah Lee
For software maintenance, bug reports provide useful information to developers because they can be used for various tasks such as debugging and understanding previous changes. However, as they are typically written in the form of conversations among developers, bug reports tend to be unnecessarily long and verbose, with the consequence that developers often have difficulties reading or understanding bug reports. To mitigate this problem, methods that automatically generate a summary of bug reports have been proposed, and various related studies have been conducted. However, existing bug report summarization methods have not fully exploited the inherent characteristics of bug reports. In this paper, we propose a bug report summarization method that uses the weighted-PageRank algorithm and exploits the 'duplicates’, ‘blocks’, and ‘depends-on’ relationships between bug reports. The experimental results show that our method outperforms the state-of-the-art method in terms of both the quality of the summary and the number of applicable bug reports.