研究発表会/2019年度
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研究発表会
開催日:毎週木曜日13:00
内容 : 研究発表×1,輪講×2
発表順:輪講→研究発表
研究発表のルール
持ち時間20分(発表12分,質疑8分)※輪講は特に時間厳守
特別な事情がない限り原則,全員参加(3年生は任意で参加可)
発表前日までに資料をアップすること(質の悪いスライドを全員に共有させない.)
急な予定が入った場合は,代わりの人を自分で探して下さい
司会者は小ゼミ進行と議事録をとる
備考
卒論・修論の成績に関係するので出席すること
発表の練習や研究のフィードバックを受けられる貴重な機会なので積極的に参加する方が好ましい
研究発表の順番
以下の順番で2人ずつ発表する
ICSE/MSR輪講
https://drive.google.com/drive/folders/1OTBbRqgqr0tK03X-hMGlHHbsxtLJF52u?usp=sharing
発表順
研究発表
輪講1
輪講2
司会・メモ係
1
福井
野口
作島
加藤
2
山崎
吉富
堀口
木村
3
池内
福井
野口
作島
4
加藤
山崎
吉富
堀口
5
木村
池内
福井
野口
6
作島
加藤
山崎
吉富
7
堀口
木村
池内
福井
8
野口
作島
加藤
山崎
9
吉富
堀口
木村
池内
10/23
†
↑
研究発表
†
発表タイトル
発表資料(
[添付]
)
↑
輪講1
†
発表者:吉富
発表タイトル:An industrial study on the differences between pre-release and post-release bugs
発表資料(
An industrial study on the differences between pre-release and post-release bugs_0.pdf
)
論文資料(
An industrial study on the differences between pre-release and post-release bugs .pdf
)
質問
p.12 変更パターンはどのように振り分けたか?→変更を高粒度に分類したあと目視で分類
チャンクとは?→ソースコード変更時の削除文と追加文のセットなど
↑
輪講2
†
発表者:作島
An Empirical Study of Abbreviations and Expansions in Software Artifacts
発表資料(
略語の展開.pdf
)
論文資料(
略語の展開_0.pdf
)
質問
隣接,非隣接とは?
↑
輪講3
†
発表者:堀口
発表タイトル
発表資料(
what_the_fork_presentation_0.pdf
)
論文資料(
What the fork a study of inefficient and efficient forking practices in social coding.pdf
)
質問
ハードフォークが一概に悪いとは言えない?→多様性をもたらす
開発者にとってissueでの事前調査は煩わしい?
↑
10/16
†
↑
研究発表
†
発表者:福井
発表タイトル:Dockerコンテナに含まれる OSSのライセンスの互換性の検証支援
発表資料(
Dockerコンテナに含まれるOSSのライセンス互換性の検証支援.pdf
)
↑
輪講2
†
発表者:野口
発表タイトル:Exploring and Exploiting the Correlations between Bug-Inducing and Bug-Fixing Commits
発表資料(
Exploring and Exploiting the Correlations between Bug-Inducing and Bug-Fixing Commits.pdf
)
論文資料(
FSE19-ming.pdf
)
↑
10/9
†
↑
輪講1
†
発表者:木村
発表タイトル:
発表資料(
A Statistics-Based Performance Testing Methodology for Cloud Applications.pdf
)
論文資料(
fse19main-id31-p.pdf
)
↑
9/8
†
↑
輪講1
†
発表者:福井
発表タイトル:The Importance of Accounting for Real-World Labelling When Predicting Software Vulnerabilities
発表資料(
2019_FSE_Jimenez.pdf
)
論文資料(
fse19main-id144-p.pdf
)
↑
輪講2
†
発表者:氏名
発表タイトル
発表資料(
[添付]
)
論文資料(
[添付]
)
↑
輪講3
†
発表者:氏名
発表タイトル
発表資料(
[添付]
)
論文資料(
[添付]
)
↑
8/1
†
↑
輪講1
†
発表者:木村
発表タイトル:A Large-Scale Study About Quality and Reproducibility of Jupyter Notebooks
発表資料(
jupyter_slide.pdf
)
論文資料(
A Large-Scale Study About Quality and Reproducibility of Jupyter Notebooks.pdf
)
↑
輪講2
†
発表者:作島
発表タイトル:Exploring Word Embedding Techniques to Improve Sentiment Analysis of Software Engineering Texts
発表資料(
MSR19.pdf
)
論文資料(
Exploring_Word_Embedding_Techniques_to_ImproveSentiment_Analysis_of_Software_Engineering_Texts.pdf
)
↑
輪講3
†
発表者:堀口
発表タイトル:git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories
発表資料(
git2net_presentation_1.pdf
)
論文資料(
git2net_1.pdf
)
↑
7/25
†
↑
輪講1
†
発表者:吉富
発表タイトル:
発表資料(
The Rise of Android Code Smells: Who Is to Blame?.pdf
)
論文資料(
The Rise of Android Code Smells_0.pdf
)
↑
輪講2
†
発表者:
発表タイトル:
発表資料(
[添付]
)
論文資料(
[添付]
)
↑
輪講3
†
発表者:
発表タイトル
発表資料(
[添付]
)
論文資料(
[添付]
)
↑
7/18
†
↑
輪講1
†
発表者:福井
発表タイトル:Import2vec Learning Embeddings for Software Libraries
発表資料(
import2vec_slide.pdf
)
論文資料(
p18-theeten.pdf
)
↑
輪講2
†
発表者:野口
発表タイトル:Cross-language clone detection by learning over abstract syntax trees
発表資料(
Cross-language clone detection by learning over abstract syntax trees.pdf
)
論文資料(
6VJl8lszX6uSO5qq9lcq3h.pdf
)
↑
輪講3
†
発表者:山崎
発表タイトル Generating Commit Messages from Diffs using Pointer-Generator Network
発表資料(
[添付]
)
論文資料(
[添付]
)
↑
7/4
†
↑
輪講1
†
発表者:作島
発表タイトル:FLOSS Participants’ Perceptions about Gender and Inclusiveness: A Survey
発表資料(
gender_0.pdf
)
論文資料(
2019_ICSE_FLOSS-Gender_0.pdf
)
↑
輪講2
†
発表者:
発表タイトル:
発表資料(
why_does_code_review_work.pdf
)
論文資料(
Why Does Code Review Work for Open Source Software Communities.pdf
)
↑
輪講3
†
発表者:
発表タイトル:
発表資料(
[添付]
)
論文資料(
[添付]
)
↑
輪講4
†
発表者:
発表タイトル:
発表資料(
[添付]
)
論文資料(
[添付]
)
↑
6/27
†
↑
輪講1
†
発表者:野口
発表タイトル:Analyzing and Supporting Adaptation of Online Code Examples
発表資料(
Analyzing and Supporting Adaptation of Online Code Examples.pdf
)
論文資料(
2mrfG8J8y60tapvxg5ZCLo.pdf
)
↑
輪講2
†
発表者:山崎
発表タイトル : Test-Driven Code Review: An Empirical Study
発表資料(
20190627_TDR.pdf
)
論文資料(
7z0RiufFqto5gZBksdR5Aa.pdf
)
↑
輪講3
†
発表者:池内
発表タイトル:Supporting Analysts by Dynamic Extraction and Classification of Requirements-Related Knowledge
発表資料(
Supporting Analysts by Dynamic Extraction and Classification of Requirements-Related Knowledge_1.pdf
)
論文資料(
Supporting Analysts by Dynamic Extraction and Classification of Requirements-Related Knowledge.pdf
)
↑
輪講4
†
発表者:木村
発表タイトル:Investigating the Effects of Gender Bias on GitHub
発表資料:(
Investigating the Effects of Gender Bias on GitHub.pdf
)
論文資料:(
p700-imtiaz.pdf
)
↑
6/19
†
↑
輪講1
†
発表者:福井
発表タイトル:Mining Software Defects: Should We Consider Affected Releases?
発表資料(
mining_software_defects(icse2019).pdf
)
論文資料(
yatish2019mining.pdf
)
↑
輪講2
†
発表者:吉富
発表タイトル:How Practitioners Perceive Coding Proficiency
発表資料(
How Practitioners Perceive Coding Proficiency.pdf
)
論文資料(
How Practitioners Perceive Coding Proficiency_0.pdf
)
↑
輪講3
†
発表者:加藤
発表タイトル:
発表資料(
Analysis and Detection of Information Types of Open Source Software Issue Discussions_5.pdf
)
論文資料(
Analysis and Detection of Information Types of Open Source Software Issue Discussions_0.pdf
)
↑
6/6
†
↑
輪講1
†
発表者:木村
発表タイトル:Do the Dependency Conflicts in My Project Matter?
発表資料(
Do the dependency conflicts in my project matter_0.pdf
)
論文資料(
Do the dependency conflicts in my project matter.pdf
)
↑
輪講2
†
発表者:作島
発表タイトル:Oreo: detection of clones in the twilight zone
発表資料(
Oreo_0.pdf
)
論文資料(
twilight.pdf
)
↑
輪講3
†
発表者:堀口
発表タイトル:
発表資料(
FSE18_MODE_presentation_0.pdf
)
論文資料(
FSE18_MODE_paper_0.pdf
)
↑
5/30
†
↑
輪講1
†
発表者:𠮷富
発表タイトル:Large-Scale Study of Substitutability in the Presence of Effects
発表資料(
Large-scale study of substitutability in the presence of effects_1.pdf
)
論文資料(
fse18.pdf
)
↑
輪講2
†
発表者:池内
発表タイトル:Detecting Speech Act Types in Developer Question/Answer Conversations during Bug Repair
発表資料(
Detecting Speech Act Types in Developer Question:Answer Conversations during Bug Repair_1.pdf
)
論文資料(
Detecting Speech Act Types in Developer Question:Answer Conversations during Bug Repair.pdf
)
↑
輪講3
†
発表者:加藤
発表タイトル:
発表資料(
Evolution Patterns of Open-Source Software Systems and Communities_1.pdf
)
論文資料(
p76-nakakoji.pdf
)
↑
5/23
†
↑
輪講1
†
発表者:福井
発表タイトル:Complementing Global and Local Contexts in Representing API Descriptions to Improve API Retrieval Tasks
発表資料(
Doc2vec.pdf
)
論文資料(
D2VEC_FSE18.pdf
)
↑
輪講2
†
発表者:山崎
発表タイトル:大ゼミ発練
発表資料(
review_presen.pdf
)
論文資料(
[添付]
)
↑
輪講3
†
発表者:野口
発表タイトル:Feedback-Directed Differential Testing of Interactive Debuggers
発表資料(
Feedback-Directed Differential Testing of Interactive Debuggers.pdf
)
論文資料(
fse18main-id5-p.pdf
)
↑
5/16
†
↑
輪講1
†
発表者:木村
発表タイトル:Predicting Node Failure in Cloud Service Systems
発表資料(
Predicting node failure in cloud service systems_0.pdf
)
論文資料(
Predicting Node Failure in Cloud Service Systems.pdf
)
↑
輪講2
†
発表者:作島
DeepSim: Deep Learning Code Functional Similarity
発表資料(
DeepSim_Deep Learning Code Functional Similarity.pdf
)
論文資料(
DeepSim_Deep Learning Code Functional Similarity_paper.pdf
)
↑
輪講3
†
発表者:堀口
Ecosystem-Level Determinants of Sustained Activity in Open-Source Projects: A Case Study of the PyPI Ecosystem
発表資料(
fse18sustainability_presentation_0.pdf
)
論文資料(
fse18sustainability.pdf
)
↑
5/7
†
↑
輪講1
†
発表者:𠮷富
発表タイトル:Empirical Study on Crash Recovery Bugs in Large-Scale Distributed Systems
発表資料(
Empirical Study on Crash Recovery Bugs in Large-Scale Distributed Systems_1.pdf
)
論文資料(
2018-fse-creb.pdf
)
↑
輪講2
†
発表者:池内
発表タイトル:Deep Learning Type Inference
発表資料(
Deep Learning Type Inference_0.pdf
)
論文資料(
Deep Learning Type Inference.pdf
)
↑
輪講3
†
発表者:加藤
発表タイトル:Be Careful of When: An Empirical Study on Time-Related Misuse of Issue Tracking Data
発表資料(
Time-Related Misuse of Issue Tracking Data_0.pdf
)
論文資料(
Be careful when_1.pdf
)
↑
4/25
†
↑
輪講1
†
発表者:福井
発表タイトル:Towards a Theory of Software Development Expertise
発表資料(
Towards a Theory of Software Development Expertise.pdf
)
論文資料(
fse18main-id155-p_0.pdf
)
↑
輪講2
†
発表者:山崎
発表タイトル
発表資料(
What_Makes_A_Code.pdf
)
論文資料(
Ram et al_0. - 2018 - What makes a code change easier to review an empi.pdf
)
↑
輪講3
†
発表者:野口
発表タイトル:Automated Patch Extraction via Syntax- and Semantics-Aware Delta Debugging on Source Code Changes
発表資料(
ddmin_with_AST_0.pdf
)
論文資料(
fse18main-id289-p.pdf
)
↑
テンプレート
†
↑
輪講1
†
発表者:
発表タイトル:
発表資料(
[添付]
)
論文資料(
[添付]
)
↑
輪講2
†
発表者:氏名
発表タイトル
発表資料(
[添付]
)
論文資料(
[添付]
)
↑
輪講3
†
発表者:氏名
発表タイトル
発表資料(
[添付]
)
論文資料(
[添付]
)
↑
6月の輪講テーマ1:ICSE2019
†
↑
Automated Program Repair
†
Learning to Spot and Refactor Inconsistent Method Names
Harnessing Evolution for Multi-Hunk Program Repair
On Learning Meaningful Code Changes Via Neural Machine Translation
VFix: Value-Flow-Guided Precise Program Repair for Null Pointer Dereferences
On Reliability of Patch Correctness Assessment
↑
Mining of Software Properties and Patterns
†
Natural Software Revisited
Towards Automating Precision Studies of Clone Detectors
↑
Static Analysis
†
SMOKE: Scalable Path-Sensitive Memory Leak Detection for Millions of Lines of Code
Reasonably-Most-General Clients for JavaScript Library Analysis
Resource-Aware Program Analysis Via Online Abstraction Coarsening
↑
Debugging and Fault Localization
†
A System Identification Based Oracle for Control-CPS Software Fault Localization
ReCDroid: Automatically Reproducing Android Application Crashes from Bug Reports
↑
DevOps and Logging
†
Mining Historical Test Logs to Predict Bugs and Localize Faults in the Test Logs
DLFinder: Characterizing and Detecting Duplicate Logging Code Smells
↑
Model-Based Software Engineering
†
Practical GUI Testing of Android Applications Via Model Abstraction and Refinement
AutoTap: Synthesizing and Repairing Trigger-Action Programs Using LTL Properties
↑
Program Comprehension and Reuse
†
Active Inductive Logic Programming for Code Search
NL2Type: Inferring JavaScript Function Types from Natural Language Information
(野口)Analyzing and Supporting Adaptation of Online Code Examples
DockerizeMe: Automatic Inference of Environment Dependencies for Python Code Snippets
↑
Studying Developers
†
How C++ Developers Use Immutability Declarations: An Empirical Study
Latent Patterns in Activities: A Field Study of How Developers Manage Context
Developer Reading Behavior While Summarizing Java Methods: Size and Context Matters
Distilling Neural Representations of Data Structure Manipulation using fMRI and fNIRS
↑
Requirements
†
Supporting Analysts by Dynamic Extraction and Classification of Requirements-Related Knowledge
↑
Software Analytics
†
(加藤)Analysis and Detection of Information Types of Open Source Software Issue Discussions
↑
Defect Prediction
†
Mining Software Defects: Should We Consider Affected Releases?
Class Imbalance Evolution and Verification Latency in Just-in-Time Software Defect Prediction
↑
Developer Biases and Trust
†
(作島)FLOSS Participants' Perceptions About Gender and Inclusiveness: A Survey
(堀口)Going Farther Together: The Impact of Social Capital on Sustained Participation in Open Source
(木村)Investigating the Effects of Gender Bias on GitHub
↑
Machine Learning in Static Analysis
†
Training Binary Classifiers as Data Structure Invariants
Graph Embedding Based Familial Analysis of Android Malware using Unsupervised Learning
A Novel Neural Source Code Representation Based on Abstract Syntax Tree
A Neural Model for Generating Natural Language Summaries of Program Subroutines
↑
Human Factors
†
How Practitioners Perceive Coding Proficiency
Socio-Technical Work-Rate Increase Associates With Changes in Work Patterns in Online Projects
Why Do Episodic Volunteers Stay in FLOSS Communities?
↑
Code Reviews
†
(山崎)Test-Driven Code Review: An Empirical Study
(堀口)Why Does Code Review Work for Open Source Software Communities?
↑
Software Quality
†
Leveraging Artifact Trees to Evolve and Reuse Safety Cases
↑
6月の輪講テーマ2:MSR2019
†
↑
Representations for Mining
†
SCOR: Source Code Retrieval with Semantics and Order
PathMiner: A Library for Mining of Path-Based Representations of Code
Import2vec: Learning Embeddings for Software Libraries
Semantic Source Code Models Using Identifier Embeddings
Exploring Word Embedding Techniques to Improve Sentiment Analysis of Software Engineering Texts
Cleaning StackOverflow for Machine Translation
Predicting Good Configurations for GitHub and Stack Overflow Topic Models
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Defect Prediction and Testing
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DeepJIT: An End-to-End Deep Learning Framework for Just-in-Time Defect Prediction
Lessons Learned from Using a Deep Tree-Based Model for Software Defect Prediction in Practice
Empirical Study in using Version Histories for Change Risk Classification
Snoring: A Noise in Defect Prediction Datasets
A Dataset of Parametric Cryptographic Misuses
Does UML Modeling Associate with Lower Defect Proneness?: A Preliminary Empirical Investigation
STRAIT: A Tool for Automated Software Reliability Growth Analysis
A Data Set of Program Invariants and Error Paths
Test Coverage in Python Programs
On the Effectiveness of Manual and Automatic Unit Test Generation: Ten Years Later
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Large-Scale Mining
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Time Present and Time Past: Analyzing the Evolution of JavaScript Code in the Wild
The Software Heritage Graph Dataset: Public Software Development Under One Roof
World of Code: An Infrastructure for Mining the Universe of Open Source VCS Data
Crossflow: A Framework for Distributed Mining of Software Repositories
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Energy and Economics
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Recommending Energy-Efficient Java Collections
GreenHub Farmer: Real-World Data for Android Energy Mining
GreenSource: A Large-Scale Collection of Android Code, Tests and Energy Metrics
Striking Gold in Software Repositories? An Econometric Study of Cryptocurrencies on GitHub
A Panel Data Set of Cryptocurrency Development Activity on GitHub
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Collaboration & Communication
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An Empirical Study of Multiple Names and Email Addresses in OSS Version Control Repositories
Characterizing the Roles of Contributors in Open-Source Scientific Software Projects
git2net - Mining Time-Stamped Co-Editing Networks from Large git Repositories
Can Issues Reported at Stack Overflow Questions be Reproduced? An Exploratory Study
Exploratory Study of Slack Q&A Chats as a Mining Source for Software Engineering Tools
Impacts of Daylight Saving Time on Software Development
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Software Quality
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The Rise of Android Code Smells: Who is to Blame?
Assessing Diffusion and Perception of Test Smells in Scala Projects
Style-Analyzer: Fixing Code Style Inconsistencies with Interpretable Unsupervised Algorithms
A Large-Scale Study About Quality and Reproducibility of Jupyter Notebooks
Cross-Language Clone Detection by Learning Over Abstract Syntax Trees
SeSaMe: A Data Set of Semantically Similar Java Methods
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Traceability
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Predicting Co-Changes between Functionality Specifications and Source Code in Behavior Driven Development
Tracing Back Log Data to its Log Statement: From Research to Practice
Beyond GumTree: A Hybrid Approach to Generate Edit Scripts
The Impact of Systematic Edits in History Slicing
Scalable Software Merging Studies with MERGANSER
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Building on Data
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Standing on Shoulders or Feet? The Usage of the MSR Data Papers
Boa Meets Python: A Boa Dataset of Data Science Software in Python Language
A Benchmark of Data Loss Bugs for Android Apps
RapidRelease - A Dataset of Projects and Issues on Github with Rapid Releases
ConPan: A Tool to Analyze Packages in Software Containers
An Empirical History of Permission Requests and Mistakes in Open Source Android Apps
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4月5月の輪講テーマ:FSE2018
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https://dl.acm.org/citation.cfm?id=3236024
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SESSION: Software Analysis I
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RefiNym: using names to refine types
Darwinian data structure selection
Scalability-first pointer analysis with self-tuning context-sensitivity
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SESSION: Deep Learning
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(作島)DeepSim: deep learning code functional similarity
(池内)Deep learning type inference
Code vectors: understanding programs through embedded abstracted symbolic traces
(堀口)MODE: automated neural network model debugging via state differential analysis and input selection
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SESSION: Developer Studies
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(福井)Towards a theory of software development expertise
(山崎)What makes a code change easier to review: an empirical investigation on code change reviewability
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SESSION: Testing I
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Singularity: pattern fuzzing for worst case complexity
Bug synthesis: challenging bug-finding tools with deep faults
Modify, enhance, select: co-evolution of combinatorial models and test plans
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SESSION: Security
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The impact of regular expression denial of service (ReDoS) in practice: an empirical study at the ecosystem scale
FraudDroid: automated ad fraud detection for Android apps
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SESSION: Mobile Apps
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AppFlow: using machine learning to synthesize robust, reusable UI tests
Winning the app production rally
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SESSION: Software Maintenance I
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(加藤)One size does not fit all: an empirical study of containerized continuous deployment workflows
(加藤)Be careful of when: an empirical study on time-related misuse of issue tracking data
(木村)Do the dependency conflicts in my project matter?
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SESSION: Software Analysis II
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Do Android taint analysis tools keep their promises?
Neural-augmented static analysis of Android communication
(作島)Oreo: detection of clones in the twilight zone
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SESSION: Symbolic Execution and Constraint Solving
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Concurrency verification with maximal path causality
Adversarial symbolic execution for detecting concurrency-related cache timing leaks
Symbolic execution with existential second-order constraints
Parameterized model counting for string and numeric constraints
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SESSION: Mining
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NAR-miner: discovering negative association rules from code for bug detection
Path-based function embedding and its application to error-handling specification mining
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SESSION: Estimation and Prediction
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(木村)A novel automated approach for software effort estimation based on data augmentation
(木村)Predicting Node failure in cloud service systems
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SESSION: Repair and Synthesis
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(池内)Detecting speech act types in developer question/answer conversations during bug repair
Visual web test repair
Syntax-guided synthesis of Datalog programs
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SESSION: Software Maintenance II
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(吉富)Large-scale study of substitutability in the presence of effects
(吉富)An empirical study on crash recovery bugs in large-scale distributed systems
(福井)Complementing global and local contexts in representing API descriptions to improve API retrieval tasks
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SESSION: Debugging and Bug Localization
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(野口)Automated patch extraction via syntax- and semantics-aware Delta debugging on source code changes
(野口)Feedback-directed differential testing of interactive debuggers
Improving IR-based bug localization with context-aware query reformulation
How should compilers explain problems to developers?
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SESSION: Ecosystems and Crowdsourcing
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(堀口)Ecosystem-level determinants of sustained activity in open-source projects: a case study of the PyPI ecosystem
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SESSION: Testing II
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Optimizing test prioritization via test distribution analysis
How well are regular expressions tested in the wild?
Which generated test failures are fault revealing? prioritizing failures based on inferred precondition violations using PAF
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SESSION: Formal Analysis
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Modeling and testing a family of surgical robots: an experience report
Efficient static checking of library updates