Research – SEL@KIT そふらぼ

CNN based fault-prone commit detection

Osamu — Thu, 21 Sep 2017 02:40:14 +0000

Defect prediction is an important task for preserving software quality.
A lot of previous research has analyzed source code to predict defects; however,
it contains a problem that is its prediction grain is too coarse and its feedback is too late
for software developers.
To achieve a more fine-grained prediction and an earlier feedback, several approaches that analyzes source code changes has been reported.
Those approaches have applied various machine learning techniques and
deep learning techniques to change metrics, such as the number of lines added,
modified files, and modified directories.
In this paper, we propose a novel approach for defect prediction called Word-Convolutional Neural Network (W-CNN), which applies CNN to the modified source code itself.
Our evaluation results show that the proposed approach can improve the effectiveness of defect prediction with a small overhead on the prediction time.

Log analysis of cyber physical systems

Osamu — Sat, 08 Apr 2017 12:38:37 +0000

Detecting anomalies of a cyber physical system (CPS), which is a complex system consisting of both physical and software parts, is important because a CPS often operates autonomously in an unpredictable environment.
However, because of the ever-changing nature and lack of a precise model for a CPS, detecting anomalies is still a challenging task.
To address this problem, we propose applying an outlier detection method to a CPS log.
By using a log obtained from an actual aquarium management system, we evaluated the effectiveness of our proposed method by analyzing outliers that it detected.
By investigating the outliers with the developer of the system, we confirmed that some outliers indicate actual faults in the system.
For example, our method detected failures of mutual exclusion in the control system that were unknown to the developer.
Our method also detected transient losses of functionalities and unexpected reboots.
On the other hand, our method did not detect anomalies that were too many and similar.
In addition, our method reported rare but unproblematic concurrent combinations of operations as anomalies.
Thus, our approach is effective at finding anomalies, but there is still room for improvement.

Open Data

A log of CPS system, Aqua-tan, recorded from the beginning of system operation.
The log files contain id, timestamp, label, numeric value, and text value.
The “label” column denotes commands and events of Aqua-tan system.

This data is analyzed in our paper in IWESEP2017[1].

Data: log.csv

[1] Y. Harada, Y. Yamagata, O. Mizuno, and E. Choi, “A Log-Based Anomaly Detection of CPS Using a Statistical Method,” In Proc. of the 8th IEEE International Workshop on Empirical Software Engineering in Practice (IWESEP2017), pp. 1-6, March 2017. (Tokyo, Japan)

References

Y. Harada, Y. Yamagata, O. Mizuno, and E. Choi, "Log-Based Anomaly Detection of CPS Using a Statistical Method," In Proc. of the 8th IEEE International Workshop on Empirical Software Engineering in Practice (IWESEP2017), pp. 1-6, March 2017.
Y. Harada, Y. Yamagata, O. Mizuno, and E. Choi, "Best Paper Award: a Log-Based Anomaly Detection of Cps Using a Statistical Method," In the 8th IEEE International Workshop on Empirical Software Engineering in Practice (IWESEP2017), March 2017.

Fault localization from bug reports

Osamu — Tue, 27 Sep 2016 11:28:44 +0000

Once a bug in software is reported, developers have to determine which source files are related to the bug. This process is referred to as bug localization, and an automatic way of bug localization is important to improve developers’ productivity. This paper proposes an approach called DrewBL to efficiently localize faulty files for a given bug report using a natural language processing tool, word2vec. In DrewBL, we first build a vector space model named semantic-VSM which represents a distributed representation of words in the bug report and source code files and next compute the relevance between them by feeding the constructed model to word2vec. We also present an approach called CombBL to further improve the accuracy of bug localization which employs not only the proposed DrewBL but also existing bug localization techniques, such as BugLocator based on textual similarity and Bugspots based on bug-fixing history, in a combinatorial manner. This study gives our early experimental results to show the effectiveness and efficiency of the proposed approaches using two open source projects.

References

Y. Uneno, O. Mizuno, and E. Choi, "Using a Distributed Representation of Words in Localizing Relevant Files for Bug Reports," In Proc. of the 2016 IEEE International Conference on Software Quality, Reliability & Security (QRS2016), pp. 183-190, August 2016.
Y. Uneno, O. Mizuno, E. Choi, "Using Word2vec in Localizing Relevant Files for Bug Reports," 電子情報通信学会技術研究報告, 115(SS2015-85), pp. 55-60, March 2016.
Y. Uneno, "単語分散表現を用いたバグ報告からの不具合ファイル特定," Master thesis, 京都工芸繊維大学大学院工芸科学研究科, 2016.
Y. Uneno, O. Mizuno, "Word2Vecを利用したバグ報告に対する修正対象推薦手法," ソフトウェア信頼性研究会FORCE2015予稿集, November 2015.
Y. Uneno and O. Mizuno, "Identifying Bug Injected Files from Bug Description Using Word2vec," In Poster presentation of 6th International Workshop on Empirical Software Engineering in Practice (IWESEP2014), November 2014.

Visualization of Software Development

Osamu — Sat, 24 Sep 2016 01:11:51 +0000

visualization

Effective and Efficient Software Testing

Osamu — Sat, 24 Sep 2016 01:01:54 +0000

About this topic

We are investigating the code coverage of combinatorial testing and investigating prioritization of test cases using statistical analysis.

Publications

K. Nishiura, O. Mizuno, E. Choi, "An Investigation of Transplantable Test Methods Toward Automatic Java Test Codes Generation by Reusing Existing Test Codes," Trans. of Information Processing Society of Japan, 62(4), pp. 1019-1028, April 2021.
M. Jiang, T. Y. Chen, F. Kuo, Z. Ding, E. Choi, and O. Mizuno, "A Revisit of the Integration of Metamorphic Testing and Test Suite Based Automated Program Repair," In Proc. of 2017 IEEE/ACM 2nd International Workshop on Metamorphic Testing (MET2017) (In conjunction with ICSE2017), pp. 14-20, May 2017. (Acceptance rate: 83.3%)
E. Choi, T. Fujiwara, and O. Mizuno, "Weighting for Combinatorial Testing by Bayesian Inference," In Proc. of 10th IEEE International Conference on Software Testing Verification and Validation Workshop (ICST2017), Posters track, pp. 189-191, March 2017.
T. Fujiwara, "Improvement of the Bayesian Inference Based Prioritized Combinatorial Testing and Assessment of the Tendency to Detect Faults," Master thesis, 京都工芸繊維大学大学院工芸科学研究科, 2017.
E. Choi and O. Mizuno, "Towards Quality Improvement and Analysis of Combinatorial Testing," In IPSJ/SIGSE Winter Workshop 2017 in Hida-Takayama (WWS2017), pp. 13-14, January 2017.
E. Choi, O. Mizuno, and Y. Hu, "Code Coverage Analysis of Combinatorial Testing," In Proc. of 4th International Workshop on Quantitative Approaches to Software Quality (QuASoQ 2016), pp. 34-40, December 2016. (Hamilton, New Zealand)
K. Nishiura, E. Choi, O. Mizuno, "Fault Localization of Combinatorial Testing with Logistic Regression," FOSEソフトウェア工学の基礎研究会(FOSE2016), pp. 243-244, December 2016.
E. Choi, C. Artho, T. Kitamura, O. Mizuno, and A. Yamada, "Distance-Integrated Combinatorial Testing," In Proc. of 27th International Symposium on Software Reliability Engineering (ISSRE2016), pp. 93-104, October 2016. (Ottawa, Canada) (Acceptance rate: 35%, 45/130)
E. Choi, S. Kawabata, O. Mizuno, C. Artho, and T. Kitamura, "Test Effectiveness Evaluation of Prioritized Combinatorial Testing: a Case Study," In Proc. of the 2016 IEEE International Conference on Software Quality, Reliability & Security (QRS2016), pp. 61-68, August 2016. (Vienna, Austria) (Acceptance rate: 43%, 48/111)
S. Kawabata, E. Choi, O. Mizuno, "A Prioritization of Combinatorial Testing Using Bayesian Inference," 電子情報通信学会技術研究報告, 115(SS2015-95), pp. 115-120, March 2016. (宮古島市, 沖縄県)
O. Mizuno, "Auto-feeding and moving aquarium management droid — everybody’s Raspberry Pi contest, the grand prix work," Nikkei Linux, 17(4), pp. 77-83, April 2015.
E. Choi, H. Nishihara, T. Ando, N. V. Tang, M. Aoki, K. Yoshisaka, O. Mizuno, and H. Osaki, "Formal Specification Based Automatic Test Generation for Embedded Network Systems," Journal of Applied Mathematics, 2014(Article ID 909762), 21pages, May 2014. (JCR: 0.834 )
T. Ando, S. Kawasaki, E. Choi, H. Nishihara, M. Aoki, K. Yoshioka, K. Shimatani, M. Furuichi, and O. Mizuno, "Development of Formal Model Based Test -- Toward Automatic Testing Framework for Embedded Systems --," In Proc. of 22nd International Symposium on Software Reliability Engineering (ISSRE2011), Supplemental proceedings, 4-4, November 2011. (Hiroshima, Japan)
T. Sumi, O. Mizuno, T. Kikuno, and M. Hirayama, "An Effective Testing Method for Hardware Related Fault in Embedded Software," IEICE Trans. on Information and Systems, E88-D(6), pp. 1142-1149, June 2005. (JCR: 0.242 (2005))
M. Hirayama, O. Mizuno, and T. Kikuno, "Analysis of Software Test Item Generation --- Comparison between High Skilled and Low Skilled Engineers ---," Journal of Computer Science and Technology, 20(2), pp. 250-257, March 2005. (JCR: 0.353 (2005))
M. Hirayama, O. Mizuno, and T. Kikuno, "Test Item Prioritizing Metrics for Selective Software Testing," IEICE Trans. on Information and Systems, E87-D(12), pp. 2733-2743, December 2004. (JCR: 0.274 (2004))
M. Hirayama, T. Yamamoto, O. Mizuno, and T. Kikuno, "Analysis of Software Test Item Generation --- Comparison between High Skilled and Low Skilled Engineers ---," In Proc. of 12th Asian Test Symposium (ATS03), pp. 210-215, November 2003. (Xian, China)
O. Mizuno, E. Shigematsu, Y. Takagi, and T. Kikuno, "On Estimating Testing Effort Needed to Assure Field Quality in Software Development," In Proc. of 13th International Symposium on Software Reliability Engineering (ISSRE2002), pp. 139-146, November 2002. (Annapolis, MD, USA.) (Acceptance rate: 45%, 33/73)
S. Amasaki, T. Yoshitomi, O. Mizuno, T. Kikuno, and Y. Takagi, "Statistical Analysis of Time Series Data on the Number of Faults Detected by Software Testing," In Proc. of 11th Asian Test Symposium (ATS02), pp. 272-277, November 2002. (Guam, USA.)
M. Hirayama, T. Yamamoto, J. Okayasu, O. Mizuno, and T. Kikuno, "Elimination of Crucial Faults by a New Selective Testing Method," In Proc. of 1st Internationl Symposium on Empirical Software Engineering (ISESE2002), pp. 183-191, October 2002. (Nara, Japan.) (Acceptance rate: 60%, 20/33)
M. Hirayama, T. Yamamoto, J. Okayasu, O. Mizuno, and T. Kikuno, "Elimination of Crucial Faults for Embedded Software Using Functional Priority Testing," In Proc. of 6th International Conference on Probabilistic Safety Assessment and Management (PSAM6), pp. 715-721, June 2002. (Puerto Lico, USA.)
E. Shigematsu, O. Mizuno, T. Kikuno, Y. Takagi, "Estimation of Software Testing Effort to Assure Permissible Number of Field Defects," 電子情報通信学会技術研究報告, 101(629, SS2001-35), pp. 9-15, January 2002.
M. Hirayama, T. Yamamoto, J. Okayasu, O. Mizuno, and T. Kikuno, "A Selective Software Testing Method Based on Priorities Assigned to Functional Modules," In Proc. of 2nd Asia-Pacific Conference on Quality Software (APAQS2001), pp. 259-267, December 2001. (HongKong, China.) (Acceptance rate: 34%, 34/100)
M. Hirayama, T. Yamamoto, J. Okayasu, O. Mizuno, T. Kikuno, "A New Selective Software Testing Method Based on Priorities Assigned to Functional Modules," 電子情報通信学会技術研究報告, 101(97-98, SS2001-6), pp. 1--8, May 2001.
M. Hirayama, J. Okayasu, T. Yamamoto, O. Mizuno, and T. Kikuno, "Generating Test Items for Checking Illegal Behaviors in Software Testing," In Proc. of 9th Asian Test Symposium (ATS2000), pp. 235-240, December 2000. (Taipei, Taiwan.)
M. Hirayama, T. Yamamoto, T. Kishimoto, O. Mizuno, and T. Kikuno, "Systematic Generation of Software Test Items Based on System Behavior from User's Viewpoint," In Proc. of International Conference on Probabilistic Safety Assessment and Management (PSAM5), pp. 2377-2382, November 2000. (Osaka, Japan.)
M. Hirayama, T. Kishimoto, O. Mizuno, T. Kikuno, "Generating Test Items by Applying Software Fault Tree Analysis," 電子情報通信学会技術研究報告, 99(547-548, SS99-53), pp. 25-32, January 2000.

Analysis of Software Evolution

Osamu — Sat, 24 Sep 2016 00:58:48 +0000

We intend to assess the improvements of Gerrit. The central
concern is “Does Rietveld evolve into Gerrit as the developers intended?” To answer
this question, we first compare qualitative features of two code review tools. We
then conducted an interview with a developer of Gerrit and obtained the developer’s
original intention of improvements in Gerrit. By analyzing mined data from code
review logs, we try to explain the effects of improvements quantitatively. The result
of analysis showed us that the improvements of Gerrit that the developer is expected
are not observed explicitly.

References:

O. Mizuno and J. Liang, "Analysis of a Code Review Tool Evolution-- a Case Study of Rietveld to Gerrit --," ACIS International Journal of Software Innovation, 3(1), pp. 16-35, January 2015.
O. Mizuno and J. Liang, "Does a Code Review Tool Evolve as the Developer Intended?," In Proc. of 12th International Conference on Software Engineering Research, Management and Applications (SERA2014), Studies in Computational Intelligence, 578, pp. 59-74, August 2014.
J. Liang, "A Comparison and Analysis of Modern Code Review in Open Source Software Projects," Master thesis, Graduate School of Science and Technology, Kyoto Institute of Technology, 2013.
J. Liang and O. Mizuno, "Analyzing Involvements of Reviewers Through Mining a Code Review Repository," In Proc. of the Joint Conference of the 21th International Workshop on Software Measurement and the 6th International Conference on Software Process and Product Measurement (IWSM/MENSURA2011), pp. 126-132, November 2011.
J. Liang, O. Mizuno, "オープンソースソフトウェアのコードレビューにおけるレビュアーの活動の分析," 平成23年度情報処理学会関西支部大会講演論文集, B-01, September 2011.

Predicting fault-prone modules by SPAM filtering technique

Osamu — Sat, 24 Sep 2016 00:56:50 +0000

The fault-prone module detection in source code is of importance for assurance of software quality. Most of previous fault-prone detection approaches are based on software metrics. Such approaches, however, have difficulties in collecting the metrics and constructing mathematical models based on the metrics.

In order to mitigate such difficulties, we propose a novel approach for detecting fault-prone modules using a spam filtering technique, named Fault-Prone Filtering. Because of the increase of needs for spam e-mail detection, the spam filtering technique has been progressed as a convenient and effective technique for text mining. In our approach, fault-prone modules are detected in a way that the source code modules are considered as text files and are applied to the spam filter directly.

To show the usefulness of our approach, we conducted an experiment using a large source code repository of Java based open source project. The result of experiment shows that our approach can classify about 85% of software modules correctly. The result also indicates that fault-prone modules can be detected relatively low cost at an early stage.

Related paper:

A. Yamada and O. Mizuno, "Classification of Bug Injected and Fixed Changes Using a Text Discriminator," ACIS International Journal of Software Innovation, 3(1), pp. 50-62, January 2015.
O. Mizuno, N. Kawashima, and K. Kawamoto, "Fault-Prone Module Prediction Approaches Using Identifiers in Source Code," ACIS International Journal of Software Innovation, 3(1), pp. 36-49, January 2015.
O. Mizuno and H. Hata, "A Metric to Detect Fault-Prone Software Modules Using Text Classifier," International Journal of Reliability and Safety, 7(1), pp. 17-31, February 2013.
H. Hata, O. Mizuno, T. Kikuno, "Fault Prediction on Fine-Grained Modules Based on Historical Metrics," Trans. of Information Processing Society of Japan, 53(6), pp. 1635-1643, June 2012.
O. Mizuno and M. Nakai, "Can Faulty Modules Be Predicted by Warning Messages of Static Code Analyzer?," Advances in Software Engineering, 2012(924923), 8 pages, May 2012.
O. Mizuno, H. Hata, "A Comparative Study on Fault-Prone Module Prediction between Spam-Filter Based Approach and Complexity Metrics Based Approach," IEICE Transactions on Information and Systems, J94-D(1), pp. 409-412, January 2011.
O. Mizuno and H. Hata, "A Hybrid Fault-Proneness Detection Approach Using Text Filtering and Static Code Analysis," International Journal of Advancements in Computing Technology, 2(5), pp. 1-12, December 2010.
H. Hata, O. Mizuno, and T. Kikuno, "Fault-Prone Module Detection Using Large-Scale Text Features Based on Spam Filtering," Empirical Software Engineering, 15(2), pp. 147-165, April 2010. (JCR: 1.612 (2009))
O. Mizuno and H. Hata, "Prediction of Fault-Prone Modules Using a Text Filtering Based Metric," International Journal of Software Engineering and Its Application, 4(1), pp. 43-52, January 2010.
O. Mizuno and T. Kikuno, "Prediction of Fault-Prone Software Modules Using a Generic Text Discriminator," IEICE Trans. on Information and Systems, E91-D(4), pp. 888-896, April 2008. (JCR: 0.369 (2008))
O. Mizuno, T. Kikuno, "Fault-Prone Filtering: a Simple Approach to Predict Fault-Prone Modules Using Spam Filter," SEC journal, 4(1), pp. 6-15, February 2008.
T. Fujiwara, O. Mizuno, and P. Leelaprute, "Fault-Prone Byte-Code Detection Using Text Classifier," In Proc. of 16th International Conference on Product-Focused Software Process Improvement (PROFES2015), 1st International Workshop on Processes, Methods, and Tools for Engineering Embedded Systems, LNCS(9459), pp. 415-430, December 2015. (Bozen-Bolzano, Italy)
K. Mori and O. Mizuno, "An Implementation of Just-In-Time Fault-Prone Prediction Technique Using Text Classifier," In Proc. of the 39th IEEE Computers, Software, and Applications Conference (COMPSAC 2015), pp. 609-612, July 2015. (Taichung, Taiwan)
O. Mizuno and Y. Hirata, "A Cross-Project Evaluation of Text-Based Fault-Prone Module Prediction," In Proc. of 6th International Workshop on Empirical Software Engineering in Practice (IWESEP2014), pp. 43-48, November 2014. (Osaka, Japan) (Acceptance rate: 56%, 10/18)
A. Yamada and O. Mizuno, "A Text Filtering Based Approach to Classify Bug Injected and Fixed Changes," In Proc. of 12th International Conference on Software Engineering Research, Management and Applications (SERA2014), pp. 680-686, August 2014. (Kitakyushu, Japan) (Acceptance rate: 59%, 19/32)
N. Kawashima and O. Mizuno, "Predicting Fault-Prone Modules by Word Occurrence in Identifiers," In Proc. of 12th International Conference on Software Engineering Research, Management and Applications (SERA2014), Studies in Computational Intelligence , 578, pp. 87-98, August 2014. (Kitakyushu, Japan) (Acceptance rate: 59%, 19/32)
O. Mizuno, "On Effects of Tokens in Source Code to Accuracy of Fault-Prone Module Prediction," In Proc. of the 17th International Computer Science and Engineering Conference (ICSEC2013), 103 - 108, September 2013. (Bangkok, Thailand) (Acceptance rate: 57%, 73/128)
K. Kawamoto and O. Mizuno, "Predicting Fault-Prone Modules Using the Length of Identifiers," In Proc. of 4th International Workshop on Empirical Software Engineering in Practice (IWESEP 2012), pp. 30-34, October 2012. (Osaka, Japan) (Acceptance rate: 8/14, 57%)
Y. Hirata and O. Mizuno, "Investigating Effects of Tokens on Detecting Fault-Prone Modules by Text Filtering," In Proc. of 22nd International Symposium on Software Reliability Engineering (ISSRE2011), Supplemental proceedings, 3-2, November 2011. (Hiroshima, Japan)
M. Nakai and O. Mizuno, "Fault-Prone Module Prediction by Filtering Warning Messages of Static Code Analyzer," In Proc. of the Joint Conference of the 21th International Workshop on Software Measurement and the 6th International Conference on Software Process and Product Measurement (IWSM/MENSURA2011), Fast abstracts, pp. 18-21, November 2011. (Nara, Japan)
Y. Hirata and O. Mizuno, "Do Comments Explain Codes Adequately? -- Investigation by Text Filtering --," In Proc. of 8th Working Conference on Mining Software Repositories (MSR2011), pp. 242-245, May 2011. (Honolulu, HI, USA)
O. Mizuno and Y. Hirata, "Fault-Prone Module Prediction Using Contents of Comment Lines," In Proc. of International Workshop on Empirical Software Engineering in Practice 2010 (IWESEP2010), pp. 39-44, December 2010. (NAIST, Nara, Japan) (Acceptance rate: 66%)
O. Mizuno and H. Hata, "An Empirical Comparison of Fault-Prone Module Detection Approaches: Complexity Metrics and Text Feature Metrics," In Proc. of 34th Annual IEEE Computer Software and Applications Conference (COMPSAC2010), pp. 248-249, July 2010. (Seoul, Korea)
O. Mizuno and H. Hata, "An Integrated Approach to Detect Fault-Prone Modules Using Complexity and Text Feature Metrics," In Proc. of 2010 International Conference on Advanced Science and Technology (AST2010), LNCS 6059, pp. 457-468, June 2010. (Miyazaki, Japan)
O. Mizuno and H. Hata, "Yet Another Metric for Predicting Fault-Prone Modules," In Proc. of 2009 International Conference on Advanced Software Engineering & Its Applications (ASEA2009), CCIS 59, pp. 296-304, December 2009. (Cheju, Korea)
H. Hata, O. Mizuno, and T. Kikuno, "Comparative Study of Fault-Proneness Filtering with PMD," In Proc. of 19th International Symposium on Software Reliability Engineering (ISSRE2008), pp. 317-318, November 2008. (Seattle/Redmond, WA, USA) (Acceptance rate: 37%, 11/30)
H. Hata, O. Mizuno, and T. Kikuno, "An Extension of Fault-Prone Filtering Using Precise Training and a Dynamic Threshold," In Proc. of 5th Working Conference on Mining Software Repositories (MSR2008), pp. 89-97, May 2008. (Leipzig, Germany) (Acceptance rate: 19%)
T. Kondou, O. Mizuno, and T. Kikuno, "Investigating Factors Affecting Accuracy of Fault-Prone Filtering," In Proc. of 18th International Symposium on Software Reliability Engineering (ISSRE2007), Supplemental proceedings, CD-ROM, November 2007. (Trollhattan, Sweden)
T. Yagi, O. Mizuno, and T. Kikuno, "Analysing Effect of Pre-Training in Fault-Prone Prediction Using Spam Filter," In Proc. of 18th International Symposium on Software Reliability Engineering (ISSRE2007), Supplemental proceedings, CD-ROM, November 2007. (Trollhattan, Sweden)
O. Mizuno, S. Ikami, S. Nakaichi, and T. Kikuno, "Fault-Prone Filtering: Detection of Fault-Prone Modules Using Spam Filtering Technique," In Proc. 1st International Symposium on Empirical Software Engineering and Measurement (ESEM2007), pp. 374-383, September 2007. (Madrid, Spain) (Acceptance rate: 41%, 44/107)
O. Mizuno and T. Kikuno, "Training on Errors Experiment to Detect Fault-Prone Software Modules by Spam Filter," In The 6th joint meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE2007), pp. 405-414, September 2007. (Dubrovnik, Croatia) (Acceptance rate: 17%, 43/251)
M. Kimoto, O. Mizuno, and T. Kikuno, "Extraction of Fault-Prone Modules Based on Fault Tracking Data from Open Source Software Repository," In 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN2007), Supplemental Proceedings, pp. 366-367, June 2007. (Edinburgh, UK)
O. Mizuno, S. Ikami, S. Nakaichi, and T. Kikuno, "Spam Filter Based Approach for Finding Fault-Prone Software Modules," In Proc. of Fourth International Workshop on Mining Software Repositories (MSR07), p. 4, May 2007. (Minneapolis, MN, USA) (Acceptance rate: 51%)
K. Mori, O. Mizuno, "スパムフィルタに基づく即時バグ予測ツールの試作," ソフトウェア・シンポジウム2015, pp. 37-46, June 2015.
T. Fujiwara, O. Mizuno, "バイトコードを用いたテキスト分類による不具合予測," ソフトウェア・シンポジウム2015, pp. 80-88, June 2015.
N. Kawashima, O. Mizuno, "識別子中の単語情報を用いた Fault-prone モジュール予測," ソフトウェアシンポジウム2014論文集, pp. 72-80, June 2014. (秋田市)
H. Hata, O. Mizuno, T. Kikuno, "Historical Metrics Based Foult-Prone Module Prediction for Fine-Grained Modules," ソフトウェアエンジニアリングシンポジウム2011(SES2011), 4, September 2011.
M. Nakai, O. Mizuno, "ソースコード静的解析結果を利用した不具合混入モジュールの予測手法の提案," ソフトウェア・シンポジウム2011, 09_研究論文 (Online only), June 2011. (長崎市)
H. Hata, O. Mizuno, T. Kikuno, "Application of Machine Learning Without Negative Examples to Fault-Prone Module Detection," Software Engineering Symposium 2009, pp. 133-138, September 2009. (東京)
O. Mizuno, "Fault-proneness Filtering：スパムフィルタに基づく不具合混入ソフトウェアモジュールの予測手法," 生産と技術, 61(1), pp. 38-43, January 2009.
O. Mizuno, S. Kuroda, K. Ishihara, D. Yamashita, "An Implementation of Text-Classification Based Fault-Prone Module Detection and Its Application to Industrial Environment," 電子情報通信学会技術報告, SS2020-17, 電子情報通信学会, January 2021.
Y. Hirata, O. Mizuno, "テキスト分類に基づくFault-proneモジュール検出法におけるコメント行の影響の分析," 情報処理学会研究報告ソフトウェア工学(SE), 2010-SE-170(10), pp. 1-8, November 2010. (大阪大学)
H. Liu, O. Mizuno, T. Kikuno, "A Comparative Study of Fault-Prone Module Detection Methods -- Fault-Proneness Filtering and Logistic Regression --," Technical Report of IEICE, 108(384, KBSE2008-47), pp. 61-66, January 2009. (東京)
R. Morii, O. Mizuno, T. Kikuno, "Identifying Fault-Prone Tokens in Source Code Modules with Spam-Filtering Technique," Technical Report of IEICE, 108(64, SS2008-4), pp. 19-24, May 2008. (宮崎市)
T. Yagi, O. Mizuno, T. Kikuno, "SPAMフィルタを用いたFault-Proneモジュールの予測 -- 異なるプロジェクトの学習結果を利用した精度評価," ソフトウェア信頼性研究会第4回ワークショップ論文集, pp. 35-43, June 2007. (松山市)
S. Ikami, S. Nakaichi, O. Mizuno, T. Kikuno, "Prediction of Fault-Prone Source Code Modules Using Text Classifier," 電子情報通信学会技術研究報告, 106(522, SS2006-75), pp. 25-30, February 2007. (愛知県立大学, 名古屋市)
N. Kawashima, "識別子中の単語情報を用いたFault-proneモジュール予測手法の提案," 卒業研究報告書, 京都工芸繊維大学, February 2014.
Y. Hirata, "Application of Trend of Tokens in Source Code Modules to Fault-Prone Module Prediction," Master thesis, Graduate School of Science and Technology, Kyoto Institute of Technology, 2012.

Analysis of Identifiers in Source Code

Osamu — Sat, 24 Sep 2016 00:39:32 +0000

Identifiers such as variable names and function names in source code are important information to understand code. The way of naming for identifiers and the length of identifiers affects on code understandability, and thus, it is guessed that they affects on software quality. In this study, we investigate the relationship between the length of identifiers and software faults in a software module. The results show that there is a certain relationship between the length of identifier and existence of software faults.

References

O. Mizuno, N. Kawashima, and K. Kawamoto, "Fault-Prone Module Prediction Approaches Using Identifiers in Source Code," ACIS International Journal of Software Innovation, 3(1), pp. 36-49, January 2015.
N. Kawashima and O. Mizuno, "Predicting Fault-Prone Modules by Word Occurrence in Identifiers," In Proc. of 12th International Conference on Software Engineering Research, Management and Applications (SERA2014), Studies in Computational Intelligence , 578, pp. 87-98, August 2014.
N. Kawashima, O. Mizuno, "識別子中の単語情報を用いた Fault-prone モジュール予測," ソフトウェアシンポジウム2014論文集, pp. 72-80, June 2014.
N. Kawashima, "識別子中の単語情報を用いたFault-proneモジュール予測手法の提案," 卒業研究報告書, 京都工芸繊維大学, February 2014.
R. Mukudai, "Topic Analysis of Developer’s Commitments from the Viewpoint of Bug Injection," Master thesis, 京都工芸繊維大学大学院工芸科学研究科, 2014.

Social Network Analysis in Software

Osamu — Sat, 24 Sep 2016 00:38:11 +0000

We are analyzing the relationship between developers in software projects. The graph shown above represents hops between developers in 8500 projects in GitHub.

A tool for calculating developer hops is found at:

Developer Hops

Research – SEL@KIT そふらぼ

CNN based fault-prone commit detection

関連論文

Log analysis of cyber physical systems

Open Data

References

Fault localization from bug reports

References

Visualization of Software Development

Effective and Efficient Software Testing

About this topic

Publications

Analysis of Software Evolution

References:

Predicting fault-prone modules by SPAM filtering technique

Related paper:

Analysis of Identifiers in Source Code

References

Social Network Analysis in Software