IWESEP 2019

The 10th International Workshop on Empirical Software Engineering in Practice (IWESEP)

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All programs of IWESEP 2019 have finished. Thanks you!!

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Best paper award: Ryo Ishizuka, et. al., “Categorizing and visualizing issue tickets to better understand the features implemented in existing software systems”. Congratulations!!

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Best poster award is: Supatsara Wattanakriengkrai, et al., “Identifying publication citations in source code comments using BERT”. Congratulations!!

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Thank you again for all participants!! We had many great presentations and posters!!

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Prof. Kenichi Matsumoto presents closing remarks of IWESEP series. Many thanks!!

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Spcial Talk from Prof. Kenichi Matsumoto.

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Session #4-3: Hironori Washizaki, “Studying Software Engineering Patterns for Designing Machine Learning Systems”

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Session #4-2: Tattiya Sakulniwat, “Visualizing the Usage of Pythonic Idioms Over Time: A Case Study of the with open Idiom”

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Session #4-1: Junnosuke Matsumoto, “GenProg meets Cluster Computing”

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MSR Asia Summit Session: Dr. Maurício Aniche, “ ‘Testing in production’: A Gentle Walk on Monitoring Research”

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MSR Asia Summit Session: Dr. Fabio Palomba, “Test code quality: A New Measure of Test Code Effectiveness”

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Session #3-2: Vara Arammongkolvichai, “Improving Clone Detection Precision using Machine Learning Techniques”

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Session #3-1: Ryo Ishizuka, “Categorizing and visualizing issue tickets to better understand the features implemented in existing software systems”

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Good morning everyone. Today is the 2nd day of IWESEP!

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All programs of 1st day are finished. Enjoy dinner. See you tomorrow!

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Poster session started!

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Session #2-2: Noppadol Assavakamhaenghan, “Software Team Member Configurations: A Study of Team Effectiveness in Moodle”

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Session #2-1: Kiyoshi Honda, “Industrial Case Study on Time Series Analysis of Metrics Changes Based on GQM Models”

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Session #1-2: Thanadon Bunkerd, “An Exploratory Study on how Contributors Impact Code Naturalness: The Case of 50 Python Projects”

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Session #1 Juntong Hong, “An empirical study of source code detection using image classification”