A Quantitative Comparison of Coverage-Based Greybox FuzzersNorihiro Yoshida
?
slides for the paper "A Quantitative Comparison of Coverage-Based Greybox Fuzzers", Proceedings of the 1st IEEE/ACM International Conference on Automation of Software Test (AST 2020), pp.89-92, Seoul, South Korea, July 2020.
Proactive Clone Recommendation System for Extract Method RefactoringNorihiro Yoshida
?
“Extract Method” refactoring is commonly used for
merging code clones into a single new method. In this position
paper, we propose a proactive clone recommendation system for
“Extract Method” refactoring. The proposed system that has
been implemented as Eclipse plug-in monitors code modifications
on the fly. Once the proposed system detects an “Extract Method”
refactoring instance based on the analysis of code modifications,
it recommends code clones of the refactored code as refactoring
candidates. The preliminary user study shows that the users are
able to refactor a greater number of clones in less time compared
to a code clone analysis environment GemX.
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A Quantitative Comparison of Coverage-Based Greybox FuzzersNorihiro Yoshida
?
slides for the paper "A Quantitative Comparison of Coverage-Based Greybox Fuzzers", Proceedings of the 1st IEEE/ACM International Conference on Automation of Software Test (AST 2020), pp.89-92, Seoul, South Korea, July 2020.
Proactive Clone Recommendation System for Extract Method RefactoringNorihiro Yoshida
?
“Extract Method” refactoring is commonly used for
merging code clones into a single new method. In this position
paper, we propose a proactive clone recommendation system for
“Extract Method” refactoring. The proposed system that has
been implemented as Eclipse plug-in monitors code modifications
on the fly. Once the proposed system detects an “Extract Method”
refactoring instance based on the analysis of code modifications,
it recommends code clones of the refactored code as refactoring
candidates. The preliminary user study shows that the users are
able to refactor a greater number of clones in less time compared
to a code clone analysis environment GemX.
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狠狠撸s for the paper "Code Search Based on Deep Neural Network and Code Mutation" in the Proceeding of the 13th International Workshop on Software Clones (IWSC 2019), in conjunction with the 26th edition of the IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2019), Hangzhou, China, February 2019.
When, why and for whom do practitioners detect technical debts?: An experienc...Norihiro Yoshida
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狠狠撸s for the paper "Revisiting the Relationship Between Code Smells and Refactoring" in the Proceedings of the 24th IEEE International Conference on Program Comprehension (ICPC 2016), Austin, TX, USA, May 2016
Mining the Modern Code Review Repositories: A Dataset of People, Process and ...Norihiro Yoshida
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狠狠撸s for the data paper "Mining the Modern Code Review Repositories: A Dataset of People, Process and Product" in the proceedings of the 13th International Conference on Mining Software Repositories (MSR 2016), Austin, TX, May 2016.
1) The document proposes a technique to support on-demand code reuse without interrupting coding tasks. It builds a source code corpus from open source projects and allows users to search for and complete code snippets without specifying search keywords.
2) An evaluation found the system can build large corpora from millions of lines of code within hours and return search results within 500ms. Precision is high for short inputs and highly similar code, but lower for less similar code.
3) Future work includes improving partitioning of code into keys and values, matching rules, and ranking search results to better support reuse of less similar code.
This document describes two datasets for analyzing open source software code review processes. The datasets contain information about who submits and reviews code patches, the types of roles reviewers perform, review activity metrics, and reviewer statistics. Example applications include social network analysis of collaboration between reviewers and analyzing how reviewers' roles relate to privileges like testing code. The datasets are available online and are aimed to provide more detailed information about reviewers compared to downloading full review repository JSON files.
11. 理解度確認テストの結果
設問1 設問2 設問3
受講生1 D C D
受講生2 A A C
受講生3 A A A
? ファジングとデバッグに関して,3つの設問を用意
? 設問1については,5段階で評価
? 設問2と3については,4段階で評価
? 第一著者と第二著者の採点が完全に一致
設問と採点基準は
予稿集P39に掲載
受講者間で
バラツキがあった
11