2016 - ACM Senior Member
Software maintenance, Software, Programming language, Software evolution and Code are his primary areas of study. He combines subjects such as Software engineering and Code refactoring with his study of Software maintenance. His studies in Software integrate themes in fields like Software deployment and Knowledge management.
His work on Set, Exception handling and Legacy system as part of general Programming language study is frequently linked to Reuse, bridging the gap between disciplines. Miryung Kim works mostly in the field of Software evolution, limiting it down to concerns involving Data mining and, occasionally, Software versioning, Regression testing and Block. The various areas that Miryung Kim examines in his Code study include Java and Information retrieval.
His scientific interests lie mostly in Software, Programming language, Software engineering, Code and Code refactoring. His work carried out in the field of Software brings together such families of science as Java and Data science. His work on Scripting language and Semantics as part of general Programming language research is frequently linked to Reuse and Transplantation, thereby connecting diverse disciplines of science.
The Software engineering study combines topics in areas such as Software development and Software bloat. His study in the fields of Clone under the domain of Code overlaps with other disciplines such as Process. His Code refactoring research is multidisciplinary, relying on both Software maintenance, Logic programming, Software bug, Correctness and Set.
His primary areas of study are Big data, Software, Dataflow, Software engineering and Code coverage. His studies deal with areas such as Debugging, Computer engineering and Data analysis as well as Big data. His Software study focuses on Software quality in particular.
The study incorporates disciplines such as Test data, SQL and Data mining in addition to Dataflow. His Software engineering research integrates issues from Heuristics, Commit, Software bloat and Code smell. His Code coverage research incorporates themes from Class, Test suite and Fuzz testing.
The scientist’s investigation covers issues in Empirical research, Construct, Code coverage, Artificial intelligence and Deep learning. He integrates many fields, such as Empirical research and engineering, in his works. His Construct study combines topics from a wide range of disciplines, such as Code, Information retrieval, Adaptation and Taxonomy.
His Code coverage study integrates concerns from other disciplines, such as SQL, Distributed computing, White-box testing, Class and Machine learning. His Artificial intelligence study combines topics in areas such as Test suite and Software development. His work deals with themes such as Field, Intelligent decision support system, Software quality, Data science and Profiling, which intersect with Deep learning.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
An empirical study of code clone genealogies
Miryung Kim;Vibha Sazawal;David Notkin;Gail Murphy.
foundations of software engineering (2005)
Managing technical debt in software-reliant systems
Nanette Brown;Yuanfang Cai;Yuepu Guo;Rick Kazman.
international conference on software engineering (2010)
An ethnographic study of copy and paste programming practices in OOPL
Miryung Kim;L. Bergman;T. Lau;D. Notkin.
international symposium on empirical software engineering (2004)
An Empirical Study of API Stability and Adoption in the Android Ecosystem
Tyler McDonnell;Baishakhi Ray;Miryung Kim.
international conference on software maintenance (2013)
A field study of refactoring challenges and benefits
Miryung Kim;Thomas Zimmermann;Nachiappan Nagappan.
foundations of software engineering (2012)
Template-based reconstruction of complex refactorings
Kyle Prete;Napol Rachatasumrit;Nikita Sudan;Miryung Kim.
international conference on software maintenance (2010)
Discovering and representing systematic code changes
Miryung Kim;David Notkin.
international conference on software engineering (2009)
LASE: locating and applying systematic edits by learning from examples
Na Meng;Miryung Kim;Kathryn S. McKinley.
international conference on software engineering (2013)
A graph-based approach to API usage adaptation
Hoan Anh Nguyen;Tung Thanh Nguyen;Gary Wilson;Anh Tuan Nguyen.
conference on object-oriented programming systems, languages, and applications (2010)
The emerging role of data scientists on software development teams
Miryung Kim;Thomas Zimmermann;Robert DeLine;Andrew Begel.
international conference on software engineering (2016)
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