研究者詳細 - 門田　暁人

論文 - 門田　暁人

分割表示 230 件中 81 - 100 件目／全件表示 >>

Assessing the Effect of Varying Word Classes on Behavioral Variables in Technology Mediated Vocabulary Learning 査読

Parisa Supitayakul, Zeynep Yucel, Akito Monden, Pattara Leelaprute

2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI) 226 - 229 2019年7月

On Preventing Symbolic Execution Attacks by Low Cost Obfuscation 査読

Toshiki Seto, Akito Monden, Zeynep Yücel, Yuichiro Kanzaki

Proc. 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2019) 495 - 500 2019年7月

Data Smoothing for Software Effort Estimation 査読

Kent Korenaga, Akito Monden, Zeynep Yucel

2019 20TH IEEE/ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING (SNPD) 501 - 506 2019年7月

Prediction of Software Defects Using Automated Machine Learning 査読

Kazuya Tanaka, Akito Monden, Zeynep Yucel

2019 20TH IEEE/ACIS INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, ARTIFICIAL INTELLIGENCE, NETWORKING AND PARALLEL/DISTRIBUTED COMPUTING (SNPD) 490 - 494 2019年

Proposal of Association Rule with Correlation Functions and Its Application to Software Development Data.

Hidekazu Saito, Akito Monden, Zeynep Yücel, Shuji Morisaki

Computer Software 36 ( 3 ) 47 - 53 2019年

掲載種別：研究論文（学術雑誌）

In this paper, we propose an association rule A ) Correl(X, Y ) that handles a correlation function, where A is the prerequisite and Correl(X, Y ) is the correlation between variables X and Y . With this extension, we can find conditions whose correlation of arbitrary two variables is high (or low) from a given data set. Furthermore, in order to distinguish statistically significant correlation, we define the rule A ) TestCorrel(X, Y ) which holds the result of the correlation significance test in the conclusion section, where TestCorrel(X, Y ) is a p-value of no-correlation test between X and Y . In order to confirm the feasibility of the proposed method, a case study using software development data was conducted. We found that it is possible to distinguish projects that are suitable for predicting development effort and those that are not.

DOI： 10.11309/jssst.36.3_47

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Effectiveness of auto-sklearn in Software Bug Prediction

Kazuya Tanaka, Akito Monden, Yucel Zeynep

Computer Software 36 ( 4 ) 46 - 52 2019年

掲載種別：研究論文（学術雑誌）

Auto-sklearn is a recent attention-gathering software library for automated machine learning that can au-tomatically select appropriate prediction models and hyper parameters for a given data set. In this paper we empirically evaluate the effectiveness of auto-sklearn in software bug prediction. In the experiment, we used software metrics of 20 OSS projects for inter-version bug prediction and compared auto-sklearn with random forrest, decision tree and linear descriminat analysis by using AUC of ROC curve as a performance measure. As a result, auto-sklearn showed similar prediction performance as random forrest. We conclude that, although auto-sklearn is useful for bug prediction, we cannot expect better prediction performance than conventional modeling techniques.

DOI： 10.11309/jssst.36.4_46

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Report on the 25th foundation of software engineering workshop (FOSE2018)

Kei Ito, Toshihiro Kamiya, Akito Monden

Computer Software 36 ( 4 ) 60 - 67 2019年

Introduction to the special issue on foundations of software engineering

Monden, A., Ito, K., Kamiya, T., Aman, H., Hanakawa, N., Sawada, A., Sugiyama, Y., Washizaki, H.

Computer Software 36 ( 4 ) 2 - 2 2019年

シンボリック実行攻撃を妨げるソフトウェア難読化方法の検討

瀬戸俊輝, 門田暁人, 神崎雄一郎

ソフトウェア工学の基礎XXV，ソフトウェア工学の基礎ワークショップFOSE2018 145 - 146 2018年11月

難読化されたJavaバイトコードに対するシンボリック実行攻撃の困難さ評価の検討

西陽太, 神崎雄一郎, 門田暁人, 玉田春昭

ソフトウェア工学の基礎XXV，ソフトウェア工学の基礎ワークショップFOSE2018 151 - 152 2018年11月

Cross-validation-based association rule prioritization metric for software defect characterization 査読

Watanabe, T., Monden, A., Y{\"u}cel, Z., Kamei, Y., Morisaki, S.

IEICE Transactions on Information and Systems E101D ( 9 ) 2269 - 2278 2018年9月

難読化されたプログラムの自動解析への耐性に関する考察

西陽太, 神崎雄一郎, 門田暁人

情報処理学会第80回全国大会講演論文集 (講演番号2J-04) 2018年3月

分岐命令のカムフラージュに基づくプログラムの制御フローの隠ぺい

村上隼之助, 神崎雄一郎, 門田暁人

情報処理学会九州支部火の国情報シンポジウム2018 C3-3 2018年3月

A feasibility study of two-step software effort estimation 査読

Naoki Kinoshita, Akito Monden

Computer Software 35 ( 1 ) 194 - 200 2018年2月

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：Japan Society for Software Science and Technology

In this paper, focusing on the problem that estimation accuracy of software development effort greatly varies among software projects, we propose a two-step effort estimation method, and conduct a feasibility study of the method. In the proposed method, given a project to be estimated, we evaluate the dependability of effort estimation for the project, that is, we evaluate whether the effort can be accurately estimated or not for the project. In case that the dependability is high, we conduct the estimation. Otherwise, estimation is avoided. As a result of an experiment to assess the feasibility of the proposed method, the residual square mean turned out to be a suitable measure of dependability
and, by avoiding the estimation when a project belongs to the high residual square mean group, the estimation error was reduced, which indicates the effectiveness of the two-step estimation. Also, by relaxing the conditions to avoid the estimation, we found that it is possible to increase the number of project to be estimated, while decreasing the estimation error.

DOI： 10.11309/jssst.35.1_194

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移動窓によるソフトウェアバグの行レベル予測の試み

福谷圭吾, 門田暁人, ユジャイゼイネップ, 畑秀明

コンピュータソフトウェア 35 ( 4 ) 122 - 128 2018年1月

記述言語：日本語掲載種別：研究論文（学術雑誌）出版者・発行元：日本ソフトウェア科学会

<p>本論文では，ソフトウェアに含まれるバグを，行の粒度で予測することを試みる．提案方法では，ソースコードを探索するためのある大きさを持った窓を用意し，バグを含むソースコードの先頭から最後へ向けて窓をずらして走査を行うことで，バグを含む窓の集合と，含まない窓の集合を作成する．次に，各窓に含まれるソースコードのトークン列を入力として，各窓に対するバグを含む確率を出力とするスパムフィルタベースのバグ予測モデルを構築する．最後に，各窓に対する予測結果を統合し，各行に対するバグ混入確率を算出する．バグを 1 つだけ含むことが予め判明している 593 件のソースコード群を用いた実験の結果，窓の大きさを 3 行とした場合に，バグを含む確率が高いと予測された上位 10 行に全バグの 67.1% が含まれることが分かり，バグを行レベルで予測するという本試みの実現可能性を確認できた．</p>

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Kurtosis and Skewness Adjustment for Software Effort Estimation. 査読

Seiji Fukui, Akito Monden, Zeynep Yücel

25th Asia-Pacific Software Engineering Conference, APSEC 2018, Nara, Japan, December 4-7, 2018 504 - 511 2018年

Generation of Mimic Software Project Data Sets for Software Engineering Research. 査読

Maohua Gan, Kentaro Sasaki, Akito Monden, Zeynep Yücel

Proceedings of the 6th International Workshop on Quantitative Approaches to Software Quality co-located with 25th Asia-Pacific Software Engineering Conference (APSEC 2018), Nara, Japan, December 4, 2018. 2273 38 - 43 2018年

Scaling up software birthmarks using fuzzy hashing

Takehiro Tsuzaki, Teruaki Yamamoto, Haruaki Tamada, Akito Monden

International Journal of Software Innovation 5 ( 3 ) 89 - 102 2017年7月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：Taru Publications

To detect the software theft, software birthmarks have been proposed. Software birthmark systems extract software birthmarks, which are native characteristics of software, from binary programs, and compare them by computing the similarity between birthmarks. This paper proposes a new procedure for scaling up the birthmark systems. While conventional birthmark systems are composed of the birthmark extraction phase and the birthmark comparison phase, the proposed method adds two new phases between extraction and comparison, namely, compression phase, which employs fuzzy hashing, and pre-comparison phase, which aims to increase distinction property of birthmarks. The proposed method enables us to reduce the required time in the comparison phase, so that it can be applied to detect software theft among many larger scale software products. From an experimental evaluation, the authors found that the proposed method significantly reduces the comparison time, and keeps the distinction performance, which is one of the important properties of the birthmark. Also, the preservation performance is acceptable when the threshold value is properly set.

DOI： 10.4018/IJSI.2017070107

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Examining Software Engineering Beliefs about System Testing Defects

Akito Monden, Masateru Tsunoda, Mike Barker, Kenichi Matsumoto

IT PROFESSIONAL 19 ( 2 ) 58 - 64 2017年3月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：IEEE COMPUTER SOC

Software engineering beliefs-short, attention-getting, practically useful statements-can help to justify process improvements. The authors empirically validate four selected beliefs in relation to the increase or decrease of defects in system testing.

DOI： 10.1109/MITP.2017.31

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Industry Application of Software Development Task Measurement System: TaskPit

Pawin Suthipornopas, Pattara Leelaprute, Akito Monden, Hidetake Uwano, Yasutaka Kamei, Naoyasu Ubayashi, Kenji Araki, Kingo Yamada, Ken-ichi Matsumoto

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS E100D ( 3 ) 462 - 472 2017年3月

記述言語：英語掲載種別：研究論文（学術雑誌）出版者・発行元：IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG

To identify problems in a software development process, we have been developing an automated measurement tool called TaskPit, which monitors software development tasks such as programming, testing and documentation based on the execution history of software applications. This paper introduces the system requirements, design and implementation of TaskPit; then, presents two real-world case studies applying TaskPit to actual software development. In the first case study, we applied TaskPit to 12 software developers in a certain software development division. As a result, several concerns (to be improved) have been revealed such as (a) a project leader spent too much time on development tasks while he was supposed to be a manager rather than a developer, (b) several developers rarely used e-mails despite the company's instruction to use e-mail as much as possible to leave communication records during development, and (c) several developers wrote too long e-mails to their customers. In the second case study, we have recorded the planned, actual, and self reported time of development tasks. As a result, we found that (d) there were unplanned tasks in more than half of days, and (e) the declared time became closer day by day to the actual time measured by TaskPit. These findings suggest that TaskPit is useful not only for a project manager who is responsible for process monitoring and improvement but also for a developer who wants to improve by him/herself.

DOI： 10.1587/transinf.2016EDP7222

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