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 64 Citations 17,931 160 World Ranking 1242 National Ranking 48

Overview

What is he best known for?

The fields of study he is best known for:

  • Programming language
  • Software
  • Software engineering

His primary areas of study are Software engineering, Software, Software system, Source code and Programming language. His work deals with themes such as Software maintenance, Software development, Software construction, Task and Java, which intersect with Software engineering. His work on Software development process, Software verification and validation and Package development process is typically connected to Eclipse as part of general Software development study, connecting several disciplines of science.

His research in the fields of Separation of concerns overlaps with other disciplines such as Coping. His Software system research integrates issues from Open-source software development, Software design, Software bug and Data science. His Source code research is multidisciplinary, relying on both Query language, Code review, Application software and KPI-driven code analysis.

His most cited work include:

  • Who should fix this bug (733 citations)
  • Predicting source code changes by mining change history (497 citations)
  • An empirical study of code clone genealogies (467 citations)

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

Software engineering, Software, Software development, Software system and Source code are his primary areas of study. His research in Software engineering intersects with topics in Task, Code, Java, Software development process and Software verification and validation. His work carried out in the field of Task brings together such families of science as Human–computer interaction and Programmer.

In general Software, his work in Software quality is often linked to Eclipse linking many areas of study. Gail C. Murphy interconnects Software deployment and Software design in the investigation of issues within Software system. His research in Source code focuses on subjects like KPI-driven code analysis, which are connected to Code review.

He most often published in these fields:

  • Software engineering (55.50%)
  • Software (38.50%)
  • Software development (37.00%)

What were the highlights of his more recent work (between 2013-2020)?

  • Software development (37.00%)
  • Software engineering (55.50%)
  • Software (38.50%)

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

Gail C. Murphy focuses on Software development, Software engineering, Software, Software system and World Wide Web. His Software development study combines topics in areas such as Variety and Knowledge management. His Software engineering study integrates concerns from other disciplines, such as Classifier, Code review, Systems engineering and Code.

The various areas that he examines in his Software study include Natural language, Data science and Source code. Gail C. Murphy has researched Software system in several fields, including Software deployment and Task. His work in the fields of World Wide Web, such as Recommender system and Technical report, overlaps with other areas such as Value and Degree of interest.

Between 2013 and 2020, his most popular works were:

  • Persuasive technology in the real world: a study of long-term use of activity sensing devices for fitness (264 citations)
  • Software developers' perceptions of productivity (113 citations)
  • Automatic Summarization of Bug Reports (104 citations)

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

  • Programming language
  • Software
  • Operating system

Gail C. Murphy mostly deals with Software development, Knowledge management, Software, World Wide Web and Software engineering. Software peer review is the focus of his Software development research. His Knowledge management study which covers Team software process that intersects with Software metric, Human resources, Source code and Software quality.

His work on Software review as part of general Software study is frequently connected to Quality, Interview study and Spell, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. He has included themes like Software bug and Knowledge transfer in his World Wide Web study. His research investigates the connection between Software engineering and topics such as Software system that intersect with issues in Classifier and Robustness.

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

Who should fix this bug

John Anvik;Lyndon Hiew;Gail C. Murphy.
international conference on software engineering (2006)

1148 Citations

Software reflexion models: bridging the gap between source and high-level models

Gail C. Murphy;David Notkin;Kevin Sullivan.
foundations of software engineering (1995)

917 Citations

An empirical study of code clone genealogies

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

714 Citations

Predicting source code changes by mining change history

A.T.T. Ying;G.C. Murphy;R. Ng;M.C. Chu-Carroll.
IEEE Transactions on Software Engineering (2004)

683 Citations

Using task context to improve programmer productivity

Mik Kersten;Gail C. Murphy.
foundations of software engineering (2006)

546 Citations

How are Java software developers using the Elipse IDE

G.C. Murphy;M. Kersten;L. Findlater.
IEEE Software (2006)

516 Citations

Using structural context to recommend source code examples

Reid Holmes;Gail C. Murphy.
international conference on software engineering (2005)

500 Citations

Software reflexion models: bridging the gap between design and implementation

G.C. Murphy;D. Notkin;K.J. Sullivan.
IEEE Transactions on Software Engineering (2001)

497 Citations

Concern graphs: finding and describing concerns using structural program dependencies

Martin P. Robillard;Gail C. Murphy.
international conference on software engineering (2002)

492 Citations

Automatic bug triage using text categorization.

Davor Cubranic;Gail C. Murphy.
software engineering and knowledge engineering (2004)

479 Citations

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