D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 35 Citations 6,486 93 World Ranking 6068 National Ranking 2900

Research.com Recognitions

Awards & Achievements

2016 - ACM Senior Member

Overview

What is he best known for?

The fields of study he is best known for:

  • Programming language
  • Operating system
  • Software

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 most cited work include:

  • An empirical study of code clone genealogies (467 citations)
  • Managing technical debt in software-reliant systems (256 citations)
  • An ethnographic study of copy and paste programming practices in OOPL (231 citations)

What are the main themes of his work throughout his whole career to date?

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.

He most often published in these fields:

  • Software (38.32%)
  • Programming language (28.04%)
  • Software engineering (26.17%)

What were the highlights of his more recent work (between 2018-2021)?

  • Big data (13.08%)
  • Software (38.32%)
  • Dataflow (5.61%)

In recent papers he was focusing on the following fields of study:

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.

Between 2018 and 2021, his most popular works were:

  • An Empirical Study of Common Challenges in Developing Deep Learning Applications (30 citations)
  • Analyzing and supporting adaptation of online code examples (16 citations)
  • Active inductive logic programming for code search (10 citations)

In his most recent research, the most cited papers focused on:

  • Programming language
  • Operating system
  • Software

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.

Best Publications

An empirical study of code clone genealogies

Miryung Kim;Vibha Sazawal;David Notkin;Gail Murphy.
foundations of software engineering (2005)

714 Citations

Managing technical debt in software-reliant systems

Nanette Brown;Yuanfang Cai;Yuepu Guo;Rick Kazman.
international conference on software engineering (2010)

414 Citations

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)

373 Citations

An Empirical Study of API Stability and Adoption in the Android Ecosystem

Tyler McDonnell;Baishakhi Ray;Miryung Kim.
international conference on software maintenance (2013)

271 Citations

Discovering and representing systematic code changes

Miryung Kim;David Notkin.
international conference on software engineering (2009)

233 Citations

Template-based reconstruction of complex refactorings

Kyle Prete;Napol Rachatasumrit;Nikita Sudan;Miryung Kim.
international conference on software maintenance (2010)

231 Citations

A field study of refactoring challenges and benefits

Miryung Kim;Thomas Zimmermann;Nachiappan Nagappan.
foundations of software engineering (2012)

228 Citations

LASE: locating and applying systematic edits by learning from examples

Na Meng;Miryung Kim;Kathryn S. McKinley.
international conference on software engineering (2013)

206 Citations

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)

204 Citations

Automatic Inference of Structural Changes for Matching across Program Versions

Miryung Kim;David Notkin;Dan Grossman.
international conference on software engineering (2007)

182 Citations

Best Scientists Citing Miryung Kim

Chanchal K. Roy

Chanchal K. Roy

University of Saskatchewan

Publications: 61

Katsuro Inoue

Katsuro Inoue

Osaka University

Publications: 43

David Lo

David Lo

Singapore Management University

Publications: 43

Marouane Kessentini

Marouane Kessentini

University of Michigan–Ann Arbor

Publications: 34

Tien N. Nguyen

Tien N. Nguyen

The University of Texas at Dallas

Publications: 30

Gabriele Bavota

Gabriele Bavota

Universita della Svizzera Italiana

Publications: 29

Alessandro Garcia

Alessandro Garcia

Pontifical Catholic University of Rio de Janeiro

Publications: 29

Fabio Palomba

Fabio Palomba

University of Salerno

Publications: 27

Denys Poshyvanyk

Denys Poshyvanyk

William & Mary

Publications: 26

Xin Xia

Xin Xia

Monash University

Publications: 26

Foutse Khomh

Foutse Khomh

Polytechnique Montréal

Publications: 24

Rick Kazman

Rick Kazman

University of Hawaii System

Publications: 24

Andy Zaidman

Andy Zaidman

Delft University of Technology

Publications: 23

Rocco Oliveto

Rocco Oliveto

University of Molise

Publications: 23

Ahmed E. Hassan

Ahmed E. Hassan

Queen's University

Publications: 22

Andrea De Lucia

Andrea De Lucia

University of Salerno

Publications: 21

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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