KINDAI UNIVERSITY


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TSUNODA Masateru

Profile

FacultyDepartment of Informatics / Graduate School of Science and Engineering Research
PositionAssociate Professor
Degree
Commentator Guidehttps://www.kindai.ac.jp/meikan/469-tsunoda-masateru.html
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Last Updated :2020/09/30

Research Activities

Research Areas

  • Informatics, Software

Published Papers

  • Probing Software Engineering Beliefs about System Testing Defects: Analyzing Data for Future Directions, Akito Monden, Masateru Tsunoda, Mike Barker, Kenichi Matsumoto, IEEE IT Professional, IEEE IT Professional, 19(2), 58 - 64, Apr. 2017 , Refereed
  • Software Development Productivity of Japanese Enterprise Applications, Masateru Tsunoda, Akito Monden, Hiroshi Yadohisa, Nahomi Kikuchi, Ken-ichi Matsumoto, Information Technology and Management, Vol.10, No.4, pp.193-205, December 2009. [FILE], Information Technology and Management, Vol.10, No.4, pp.193-205, December 2009. [FILE], 10(4), 193 - 205, Jan. 2009 , Refereed
  • Benchmarking IT operations cost based on working time and unit cost, Masateru Tsunoda, Akito Monden, Kenichi Matsumoto, Sawako Ohiwa, Tomoki Oshino, SCIENCE OF COMPUTER PROGRAMMING, SCIENCE OF COMPUTER PROGRAMMING, 135, 75 - 87, Feb. 2017 , Refereed
    Summary:Recently, size of information system gets large, and the information system operation (IT operations) is often outsourced. When IT operations of the large system is outsourced, high cost is needed, and troubles in IT operations may affect the activity of the company. Therefore, the information system operation is important for the companies. Cost is one of the important factors when the system operation is outsourced. However, it is not easy for the customers (system users) to judge whether the operation cost is valid or not. To support the judgment, we focus on information which the customers can know (e.g., size of software), to estimate the working time. In the analysis, we clarified the factors which affect the working time. Then, data was stratified based on the factors, to show the benchmark of working time. Using the benchmark, customers estimate the working time roughly. Also, we clarified the factors which affect the unit cost, and showed the benchmark. Operation cost can be estimated, by estimated working time multiplied by the estimated unit cost. The analysis results showed that the process standardization relates to the working time of operators. Also, the network range and the contract type have a relationship to the unit cost of operators. Work efficiency and unit cost do not affect operation quality. (C) 2016 Elsevier B.V. All rights reserved.

Conference Activities & Talks

  • Analyzing the Decision Criteria of Software Developers Based on Prospect Theory, Kanako Kina, Masateru Tsunoda, Hideaki Hata, Haruaki Tamada, Hiroshi Igaki, International Conference on Software Analysis, Evolution, and Reengineering (SANER 2016),   2016 03
  • Revisiting Software Development Effort Estimation Based on Early Phase Development Activities, Masateru Tsunoda, Koji Toda, Kyohei Fushida, Yasutaka Kamei, Meiyappan Nagappan, Naoyasu Ubayashi, Working Conference on Mining Software Repositories (MSR 2013),   2013 05
  • How to Treat Timing Information for Software Effort Estimation?, Masateru Tsunoda, Sousuke Amasaki, Chris Lokan, International Conference on Software and Systems Process (ICSSP 2013),,   2013 05

Misc

  • ソフトウェア開発者の年齢がプログラム理解速度に及ぼす影響の分析, Yukasa Murakami, Masateru Tsunoda, Masahide Nakamura, 情報処理学会研究報告, ソフトウェア工学研究会, 2016-SE-191, 1, 1, 6,   2016 03 , http://www27.cs.kobe-u.ac.jp/achieve/data/pdf/
  • 時空間情報と動作を組み合わせた認証方法, Masateru Tsunoda, Kyohei Fushida, Kohei Mitsui, Yasutaka Kamei, Masahide Nakamura, Keita Gotoh, Kenichi Matsumoto, 情報処理学会研究報告, 数理モデル化と問題解決研究会, 2010-MPS-77, 27, 1, 6,   2010 03 , http://www27.cs.kobe-u.ac.jp/achieve/data/pdf/1091.pdf
  • 位置と速度を利用した移動体向け認証方式の提案, Masateru TSUNODA, Kyohei FUSHIDA, Kohei MITSUI, Yasutaka KAMEI, Keita GOTO, Masahide NAKAMURA, Ken-ichi MATSUMOTO, 電子情報通信学会技術報告, モバイルマルチメディア通信研究専門委員会, MoMuC2006-55, 11, 16,   2006 11 , http://www27.cs.kobe-u.ac.jp/achieve/data/pdf/178.pdf
  • A Recommendation Method of Useful Software Components for Ongoing Project, KAMEI Yasutaka, TSUNODA Masateru, KAKIMOTO Takeshi, OHSUGI Naoki, MONDEN Akito, MATSUMOTO Ken-ichi, Technical report of IEICE. SS, 106, 16, 25, 30,   2006 04 , http://ci.nii.ac.jp/naid/110004718949
    Summary:Many software components have been provided by development platform vendors, for achieving efficient development of high quality software; however, some practitioners cannot find useful components because number of the provided components is too large. For solving this problem, we propose a method based on collaborative filtering for recommending useful components to each ongoing project. In the proposed method, at first, some past projects similar to given ongoing project are retrieved by calculating similarity with number of common components used in the ongoing project and each past proj...
  • Characterizing Software Projects Unpredictable by Effort Estimation Models, TODA Koji, TSUNODA Masateru, MONDEN Akito, MATSUMOTO Ken-ichi, IEICE technical report, 105, 491, 67, 72,   2005 12 20 , http://ci.nii.ac.jp/naid/110003488407
    Summary:Effort prediction is necessary for project manegers to make software development plan. To predict development effort, various estimation moedels such as multivariate regression models or neural network model have been proposed. However, there is much difference in effort prediction accuracy among predicted projects. In this study, we experimentally analyzed the project charactaristics whose prediction accuracy tend to become worse. As a result, we identified some characteristics.
  • Software Technology Recommendation Based on Collaborative Filtering, AKINAGA Tomohiro, OHSUGI Naoki, KAKIMOTO Takeshi, TSUNODA Masateru, MONDEN Akito, MATSUMOTO Kenichi, Technical report of IEICE. SS, 105, 128, 7, 13,   2005 06 16 , http://ci.nii.ac.jp/naid/10016575649
    Summary:In recent years, much software development technology is proposed. It is difficult for the software engineer to be master of all these technologies. So it is necessary to select the technology that should acquire it beforehand. Then, we propose a system recommending the software exploitation technology that seems to be useful for engineer by using Collaborative Filtering. In the proposal method, first of all, the interest to each development technology is first investigated to each engineer. And, the engineer to whom the tendency to the interest is similar is discovered based on cooperated ...
  • A Java Class File Recommender System Based on Collaborative Filtering, KAKIMOTO Takeshi, TSUNODA Masateru, OHSUGI Naoki, MONDEN Akito, MATSUMOTO Ken'ichi, IEICE technical report. Dependable computing, 104, 346, 29, 34,   2004 10 , http://ci.nii.ac.jp/naid/110003204298
    Summary:Today, most software development platforms provide various software components. However, some software developers are not aware of useful components because extremely large amount of components are provided. This paper propose a system recommending the developers some Java class files by using Collaborative Filtering. Once a developer venters a Java class file which has been developed in ongoing project, the proposed system investigates used Java classes in the entered class file. Next, the system finds some similar class files from already completed class files which made in the past proje...
  • Benchmarking Software Maintenance Based on Working Time, Masateru Tsunoda, Akito Monden, Kenichi Matsumoto, Sawako Ohiwa, Tomoki Oshino, 3RD INTERNATIONAL CONFERENCE ON APPLIED COMPUTING AND INFORMATION TECHNOLOGY (ACIT 2015) 2ND INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND INTELLIGENCE (CSI 2015), 20, 27,   2015 , 10.1109/ACIT-CSI.2015.13
    Summary:Software maintenance is an important activity on the software lifecycle. Software maintenance does not mean only removing faults found after software release. Software needs extensions or modifications of its functions due to changes in a business environment, and software maintenance also indicates them. In this research, we try to establish a benchmark of work efficiency for software maintenance. To establish the benchmark, factors affecting work efficiency should be clarified, using a dataset collected from various organizations (cross-company dataset). We used dataset includes 134 data points collected by Economic Research Association in 2012, and analyzed factors affected work efficiency of software maintenance. We defined the work efficiency as number of modified modules divided by working time. The main contribution of our research is illustrating factors affecting work efficiency, based on the analysis using cross-company dataset and working time. Also, we showed work efficiency, classified the factor. It can be used to benchmark an organization. We empirically illustrated that using Java and restriction of development tool affect to work efficiency.
  • Predicting faults after unit testing using design phase metrics in embedded software development, Masateru Tsunoda, Akito Monden, Kenichi Matsumoto, 11, 2, 16, 23,   2015
  • Incorporating Expert Judgment into Regression Models of Software Effort Estimation, Masateru Tsunoda, Akito Monden, Jacky Keung, Kenichi Matsumoto, 2012 19TH ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE (APSEC), VOL 1, 374, 379,   2012 , 10.1109/APSEC.2012.58
    Summary:One of the common problems in building an effort estimation model is that not all the effort factors are suitable as predictor variables. As a supplement of missing information in estimation models, this paper explores the project manager's knowledge about the target project. We assume that the experts can judge the target project's productivity level based on his/her own expert knowledge about the project. We also assume that this judgment can be further improved, because using the expert's judgment solely could incur subjective perception. This paper proposes a regression model building/selection method to address this challenge. In the proposed method, a fit dataset for model building is divided into two or three subsets by project productivity, and an estimation model is built on each data subset. The expert judges the productivity level of the target project and selects one of the models to be used. In the experiment, we used three datasets to evaluate the produced effort estimation models. In the experiment, we adjusted the error rate of the judgment and analyzed the relationship between the error rate and the estimation accuracy. As a result, the judgment-incorporating models produced significantly higher estimation accuracy than the conventional linear regression model, where the expert's error rate is less than 37%.
  • Recommendation of software technologies based on collaborative filtering, T Akinaga, N Ohsugi, M Tsunoda, T Kakimoto, A Monden, K Matsumoto, 12TH ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE, PROCEEDINGS, 209, 214,   2005 , Refereed, 10.1109/APSEC.2005.94
    Summary:Software engineers have to select some appropriate development technologies to use in the work; however, engineers sometimes cannot find the appropriate technologies because there are vast amount of options today. To solve this problem, we propose a software technology recommendation method based on Collaborative Filtering (CF). In the proposed method, at first, questionnaires are collected from concerned engineers about their technical interest. Next, similarities between an active engineer who gets recommendation and the other engineers are calculated according to the technical interests. Then, some similar engineers are selected for the active engineer. At last, some technologies are recommended which attract the similar engineers. An experimental evaluation showed that the proposed method can make accurate recommendations than that of a naive (non-CF) method.

Awards & Honors

  •   2012 10 , International Workshop on Empirical Software Engineering in Practice (IWESEP 2012), Best Paper Award

Research Grants & Projects

  • Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C), Evaluation framework considering users for software development support methods
  • Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Challenging Exploratory Research, Furinkazan: Understanding Behaviors in Software Development based on Game Theoretical Modeling and Empirical Studies, This study aims to understand the various characteristics of software developers and their behavioral patterns. We have addressed this challenge from the following four aspects. 1) A survey study based on behavioral economics to clarify the characteristics of developers for risk management. 2) Data mining on open source software projects to identify patterns of developers’ behaviors. 3) Data mining on closed software development especially to find the patterns of novice developers’ behaviors. 4) Game theoretical modeling and analysis for actual data.
  • Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research (C), Planning support for efficient software maintenance and operation, The goal of the research is to support making the plan of software maintenance and system operation. To support that, we clarified the followings, (1) benchmark of software maintenance based on working time, (2) benchmark of information system operation based on working time and unit cost. Also, to support building prediction models of maintenance efficiency and operation efficiency, we clarified the followings, (1) influence of outliers on software development project prediction, (2) advantages of Tobit model on software development project prediction. Using the benchmarks and analysis results, we can make appropriate maintenance plan and operation plan, and it will enhance efficiency of software maintenance and system operation.
  • Japan Society for the Promotion of Science, Grants-in-Aid for Scientific Research Grant-in-Aid for Young Scientists (B), Software Development Project Prediction Framework, To achieve high accurate prediction in a software development project, software development project prediction framework and its element technologies was studied. The framework consists of(1) peculiar data point(outlier) deletion,(2) stratification,(3) selecting appropriate variable for prediction, and(4) selecting appropriate prediction model for a dataset, and each element technology is applied in the numerical order. In the research period, each technology was invented and the effects were examined.