Faculty Profiles - MONDEN Akito

Papers - MONDEN Akito

Division display 181 - 200 of about 230 ／ All the affair displays >>

A Hybrid Faulty Module Prediction Using Association Rule Mining and Logistic Regression Analysis Reviewed

Yasutaka Kamei, Akito Monden, Shuji Morisaki, Ken-ichi Matsumoto

ESEM'08: PROCEEDINGS OF THE 2008 ACM-IEEE INTERNATIONAL SYMPOSIUM ON EMPIRICAL SOFTWARE ENGINEERING AND MEASUREMENT 279 - 281 2008

Language：English Publishing type：Research paper (international conference proceedings) Publisher：ASSOC COMPUTING MACHINERY

This paper proposes a fault-prone module prediction method that combines association rule mining with logistic regression analysis. In the proposed method, we focus on three key measures of interestingness of an association rule (support, confidence and lift) to select useful rules for the prediction. If a module satisfies the premise (i.e. the condition in the antecedent part) of one of the selected rules, the module is classified by the rule as either fault-prone or not. Otherwise, the module is classified by the logistic model. We experimentally evaluated the prediction performance of the proposed method with different thresholds of each rule interestingness measure (support, confidence and lift) using a module set in the Eclipse project, and compared it with three well-known fault-proneness models (logistic regression model, linear discriminant model and classification tree). The result showed that the improvement of the F1-value of the proposed method was 0.163 at maximum compared to conventional models.

Web of Science

researchmap

An Over-sampling Method for Analogy-based Software Effort Estimation Reviewed

Yasutaka Kamei, Jacky Keung, Akito Monden, Ken-ichi Matsumoto

ESEM'08: PROCEEDINGS OF THE 2008 ACM-IEEE INTERNATIONAL SYMPOSIUM ON EMPIRICAL SOFTWARE ENGINEERING AND MEASUREMENT 312 - + 2008

Language：English Publishing type：Research paper (international conference proceedings) Publisher：ASSOC COMPUTING MACHINERY

This paper proposes a novel method to generate synthetic project cases and add them to a fit dataset for the purpose of improving the performance of analogy-based software effort estimation. The proposed method extends conventional over-sampling method, which is a preprocessing procedure for n-group classification problems, which makes it suitable for any imbalanced dataset to be used in analogy-based system. We experimentally evaluated the effect of the over-sampling method to improve the performance of the analogy-based software effort estimation by using the Desharnais dataset. Results show significant improvement to the estimation accuracy by using our approach.

Web of Science

researchmap

Are Good Code Reviewers Also Good at Design Review? Reviewed

Hidetake Uwano, Akito Monden, Ken-ichi Matsumoto

ESEM'08: PROCEEDINGS OF THE 2008 ACM-IEEE INTERNATIONAL SYMPOSIUM ON EMPIRICAL SOFTWARE ENGINEERING AND MEASUREMENT 351 - 353 2008

Dresrem 2: An Analysis System for Multi-Document Software Review Using Reviewers' Eye Movements Reviewed

Hidetake Uwano, Akito Monden, Ken-ichi Matsumoto

Proceedings - The 3rd International Conference on Software Engineering Advances, ICSEA 2008, Includes ENTISY 2008: International Workshop on Enterprise Information Systems 177 - 183 2008

Analyzing factors of defect correction effort in a multi-vendor information system development Reviewed

Tomoko Matsumura, Shuji Morisaki, Akito Monden, Ken-Ichi Matsumoto

Journal of Computer Information Systems 49 ( 1 ) 73 - 80 2008

Language：English Publishing type：Research paper (scientific journal) Publisher：International Association for Computer Information Systems

This paper describes an empirical study to reveal factors influencing defect correction effort in software development. In the study we collected various attributes (metrics) of defects found in a typical medium-scale, multi-vendor information system development project in Japan over a six-month period. We then statistically analyzed the relationship between the defects' attributes and the correction effort. The analysis confirmed the well-known principle "defects are the more expensive the later they are detected" by revealing that defects detected in the "system test" were 4.88 times more expensive than those detected in the "coding/unit test". Another principle "defects are more expensive the longer they survive in software" was also confirmed by revealing that defects, which survived two or more development phases, were 4.44 times more expensive than those detected immediately. We also identified other factors, such as defect reproducibility, severity, and the cause of detection delay, that had a significant influence on the correction effort.

DOI： 10.1080/08874417.2008.11645308

Scopus

researchmap

異なるプロジェクト間におけるFault-Proneモジュール判別の精度評価 Reviewed

木浦幹雄, ?本真佑, 亀井靖高, 門田暁人, 松本健一

ソフトウェア工学の基礎XIV 日本ソフトウェア科学会 FOSE2007 131 - 136 2007.11

APIライブラリ名隠ぺいのための動的名前解決を用いた名前難読化 Reviewed

Haruaki Tamada, Masahide Nakamura, Akito Monden, Ken-ichi Matsumoto

電子情報通信学会論文誌D J90-D ( 10 ) 2723 - 2735 2007.10

Exploiting Eye Movements for Evaluating Reviewer's Performance in Software Review Reviewed

Hidetake Uwano, Masahide Nakamura, Akito Monden, Ken-ichi Matsumoto

IEICE Transactions on Fundamentals E90-A ( 10 ) 317 - 328 2007.10

Language：English Publishing type：Research paper (scientific journal) Publisher：The Institute of Electronics, Information and Communication Engineers

This paper proposes to use eye movements to characterize the performance of individuals in reviewing software documents. We design and implement a system called DRESREM, which measures and records eye movements of document reviewers. Based on the eye movements captured by eye tracking device, the system computes the line number of the document that the reviewer is currently looking at. The system can also record and play back how the eyes moved during the review process. To evaluate the effectiveness of the system we conducted an experiment to analyze 30 processes of source code review (6 programs, 5 subjects) using the system. As a result, we have identified a particular pattern, called scan, in the subject's eye movements. Quantitative analysis showed that reviewers who did not spend enough time on the scan took more time to find defects on average.

DOI： 10.1093/ietfec/e90-a.10.2290

CiNii Article

CiNii Books

researchmap

ソフトウェア開発工数積算のための生産性分析 Reviewed

角田雅照, 門田暁人, 松本健一

経済調査研究レビュー ( 1 ) 114 - 119 2007.9

Comparison of Outlier Detection Methods in Fault-Proneness Models Reviewed

Shinsuke Matsumoto, Yasutaka Kamei, Akito Monden, Ken-ichi Matsumoto

Proceedings of the 1st International Symposium on Empirical Software Engineering and Measurement (ESEM2007) 461 - 463 2007.9

Applying Sampling Methods to Fault-prone Module Detection(Evaluation and Management,<Special Issue>Software Engineering Theory and Practice) Reviewed

KAMEI YASUTAKA, MATSUMOTO SHINSUKE, KAKIMOTO TAKESHI, MONDEN AKITO, MATSUMOTO KEN-ICHI

IPSJ Journal 48 ( 8 ) 2651 - 2662 2007.8

Language：Japanese Publishing type：Research paper (scientific journal) Publisher：一般社団法人情報処理学会

To improve the prediction performance of fault-proneness models, this paper experimentally evaluates the effect of over and under sampling methods, which are preprocessing procedures for a fit dataset. The sampling methods are expected to improve the prediction performance when the fit dataset is imbalanced, i.e. there exists a large bias between the number of faultprone modules and the number of non-fault-prone modules. There is, however, no research that reports the effects of applying sampling methods to fault-proneness models. In the experiment, we evaluated the effects of four sampling...

CiNii Article

researchmap

他プロジェクトの実績データに基づくFault-Proneモジュール判別の試み

木浦幹雄, ?本真佑, 亀井靖高, 門田暁人, 松本健一

ソフトウェア信頼性研究会第4回ワークショップ 45 - 53 2007.7

Fault-Proneモジュール判別モデルに対する外れ値除去法の適用効果

?本真佑, 亀井靖高, 門田暁人, 松本健一

情報処理学会研究報告 2007-SE-155 ( 33 ) 49 - 56 2007.3

Language：Japanese Publishing type：Research paper (conference, symposium, etc.) Publisher：Information Processing Society of Japan (IPSJ)

In this paper, we experimentally evaluate outlier detection methods, which detect data points that are far away from others in a data set, in terms of improving the prediction performance of fault-prone module detection models. In the experiment, we compared two outlier detection methods (MOA, LOFM) each applied to three well-known fault-prone module detection models (LDA, LRA, CT). The result showed that MOA improved Fl-values of all fault-proneness models (0.04 at minimum, 0.17 at maximum and 0.10 at mean) while improvements by LOFM were relatively small (-0.01 at minimum, 0.04 at maximum and 0.01 at mean).

CiNii Article

CiNii Books

researchmap

Other Link： http://id.nii.ac.jp/1001/00021154/

Defect data analysis based on extended association rule mining Reviewed

Shuji Morisaki, Akito Monden, Tomoko Matsumura, Haruaki Tamada, Ken-Ichi Matsumoto

Proceedings - ICSE 2007 Workshops: Fourth International Workshop on Mining Software Repositories, MSR 2007 2007

Language：English Publishing type：Research paper (international conference proceedings)

This paper describes an empirical study to reveal rules associated with defect correction effort. We defined defect correction effort as a quantitative (ratio scale) variable, and extended conventional (nominal scale based) association rule mining to directly handle such quantitative variables. An extended rule describes the statistical characteristic of a ratio or interval scale variable in the consequent part of the rule by its mean value and standard deviation so that conditions producing distinctive statistics can be discovered. As an analysis target, we collected various attributes of about 1,200 defects found in a typical medium-scale, multi-vendor (distance development) information system development project in Japan. Our findings based on extracted rules include: (1)Defects detected in coding/unit testing were easily corrected (less than 7% of mean effort) when they are related to data output or validation of input data. (2)Nevertheless, they sometimes required much more effort (lift of standard deviation was 5.845) in case of low reproducibility, (3)Defects introduced in coding/unit testing often required large correction effort (mean was 12.596 staff-hours and standard deviation was 25.716) when they were related to data handing. From these findings, we confirmed that we need to pay attention to types of defects having large mean effort as well as those having large standard deviation of effort since such defects sometimes cause excess effort. © 2007 IEEE.

DOI： 10.1109/MSR.2007.5

Scopus

researchmap

ソースコードの圧縮性とコードクローンの関係の分析 Reviewed

左藤裕紀, 亀井靖高, 上野秀剛, 川口真司, 門田暁人, 松本健一

日本ソフトウェア科学会第24回大会 2007

Mining Quantitative Rules in a Software Project Data Set

Morisaki Shuji, Monden Akito, Tamada Haruaki, Matsumura Tomoko, Matsumoto Ken-ichi

ipsjdc 3 518 - 527 2007

Language：English Publisher：Information Processing Society of Japan

This paper proposes a method to mine rules from a software project data set that contains a number of quantitative attributes such as staff months and SLOC. The proposed method extends conventional association analysis methods to treat quantitative variables in two ways: (1) the distribution of a given quantitative variable is described in the consequent part of a rule by its mean value and standard deviation so that conditions producing the distinctive distributions can be discovered. To discover optimized conditions, (2) quantitative values appearing in the antecedent part of a rule are divided into contiguous fine-grained partitions in preprocessing, then rules are merged after mining so that adjacent partitions are combined. The paper also describes a case study using the proposed method on a software project data set collected by Nihon Unisys Ltd. In this case, the method mined rules that can be used for better planning and estimation of the integration and system testing phases, along with criteria or standards that help with planning of outsourcing resources.

DOI： 10.2197/ipsjdc.3.518

CiNii Article

researchmap

Mining Quantitative Rules in a Software Project Data Set

Morisaki Shuji, Monden Akito, Tamada Haruaki, Matsumura Tomoko, Matsumoto Ken-ichi

Information and Media Technologies 2 ( 4 ) 999 - 1008 2007

Language：English Publisher：Information and Media Technologies Editorial Board

DOI： 10.11185/imt.2.999

CiNii Article

researchmap

Evaluating the Robustness of Collaborative Filtering Based Effort Estimation Method against Data Missing Reviewed

KAKIMOTO Takeshi, TSUNODA Masateru, OHSUGI Naoki, MONDEN Akito, MATSUMOTO Ken-ichi

The IEICE transactions on information and systems (Japanese edetion) 89 ( 12 ) 2602 - 2611 2006.12

プログラマの視線を用いたコードレビュー性能の要因分析 Reviewed

Hidetake Uwano, Masahide Nakamura, Akito Monden, Ken-ichi Matsumoto

ソフトウェア工学の基礎XIII 日本ソフトウェア科学会FOSE 2006 103 - 112 2006.11

Java クラスファイル難読化ツール DonQuixote Reviewed

Haruaki Tamada, Masahide Nakamura, Akito Monden, Ken-ichi Matsumoto

ソフトウェア工学の基礎XIII, 日本ソフトウェア科学会 FOSE2006 113 - 118 2006.11

　 PREV - NEXT 　

< MONDEN Akito >

Papers - MONDEN Akito