D-Index & Metrics Best Publications
Computer Science
Canada
2023

D-Index & Metrics 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.

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 65 Citations 13,358 274 World Ranking 1556 National Ranking 58

Research.com Recognitions

Awards & Achievements

2023 - Research.com Computer Science in Canada Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Programming language
  • Artificial intelligence

Software maintenance, Source code, Software system, Software and Software engineering are his primary areas of study. He interconnects Software evolution, Software construction, Program comprehension and Software quality in the investigation of issues within Software maintenance. His Source code study results in a more complete grasp of Programming language.

The study incorporates disciplines such as Redundant code and Traceability in addition to Programming language. His Software system study integrates concerns from other disciplines, such as Class, Object-oriented programming, Distributed computing and Algorithm. His studies deal with areas such as Machine learning, Probabilistic logic, Feature and Artificial intelligence as well as Data mining.

His most cited work include:

  • Recovering traceability links between code and documentation (825 citations)
  • Comparison and Evaluation of Clone Detection Tools (572 citations)
  • Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval (378 citations)

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

His primary areas of study are Software engineering, Software system, Software maintenance, Source code and Software. The Software engineering study which covers Software development that intersects with Software deployment. His Software system research is multidisciplinary, incorporating perspectives in Software architecture, Distributed computing and Software design.

His work in Software maintenance addresses subjects such as Theoretical computer science, which are connected to disciplines such as Algorithm. His Source code research is multidisciplinary, relying on both Program comprehension, Data mining and Traceability. He has included themes like Java and Systems engineering in his Software study.

He most often published in these fields:

  • Software engineering (28.17%)
  • Software system (22.89%)
  • Software maintenance (22.89%)

What were the highlights of his more recent work (between 2015-2021)?

  • Code refactoring (7.04%)
  • Software engineering (28.17%)
  • Android (4.23%)

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

Giuliano Antoniol focuses on Code refactoring, Software engineering, Android, Software and Software system. His Software engineering study incorporates themes from Software quality, Software development, Task, Code and Source code. His research investigates the link between Task and topics such as Program comprehension that cross with problems in Context and Empirical research.

The Source code study combines topics in areas such as Code, Affect and Lexicon. He combines subjects such as Machine learning, Cyber-physical system, Tracing and Artificial intelligence with his study of Software. Giuliano Antoniol works on Software system which deals in particular with Software maintenance.

Between 2015 and 2021, his most popular works were:

  • Linguistic antipatterns: what they are and how developers perceive them (48 citations)
  • Stack Overflow: A code laundering platform? (40 citations)
  • EARMO: An Energy-Aware Refactoring Approach for Mobile Apps (36 citations)

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

  • Operating system
  • Artificial intelligence
  • Programming language

Giuliano Antoniol mostly deals with Android, Software engineering, Database, Energy consumption and License. His study looks at the relationship between Android and fields such as Java, as well as how they intersect with chemical problems. Many of his studies on Software engineering involve topics that are commonly interrelated, such as Software system.

His Software system research is included under the broader classification of Programming language. His License research incorporates themes from Computer security, Mobile apps and Code Access Security. His study looks at the relationship between Code and topics such as Software quality, which overlap with Source code.

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

Recovering traceability links between code and documentation

G. Antoniol;G. Canfora;G. Casazza;A. De Lucia.
IEEE Transactions on Software Engineering (2002)

1270 Citations

Comparison and Evaluation of Clone Detection Tools

S. Bellon;R. Koschke;G. Antoniol;J. Krinke.
IEEE Transactions on Software Engineering (2007)

940 Citations

Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval

D. Poshyvanyk;Y.-G. Gueheneuc;A. Marcus;G. Antoniol.
IEEE Transactions on Software Engineering (2007)

603 Citations

Is it a bug or an enhancement?: a text-based approach to classify change requests

Giuliano Antoniol;Kamel Ayari;Massimiliano Di Penta;Foutse Khomh.
conference of the centre for advanced studies on collaborative research (2008)

459 Citations

An exploratory study of the impact of antipatterns on class change- and fault-proneness

Foutse Khomh;Massimiliano Di Penta;Yann-Gaël Guéhéneuc;Giuliano Antoniol.
Empirical Software Engineering (2012)

395 Citations

An Empirical Study of the Impact of Two Antipatterns, Blob and Spaghetti Code, on Program Comprehension

Marwen Abbes;Foutse Khomh;Yann-Gael Gueheneuc;Giuliano Antoniol.
conference on software maintenance and reengineering (2011)

336 Citations

DeMIMA: A Multilayered Approach for Design Pattern Identification

Y.-G. Gueheneuc;G. Antoniol.
IEEE Transactions on Software Engineering (2008)

244 Citations

EEG data compression techniques

G. Antoniol;P. Tonella.
IEEE Transactions on Biomedical Engineering (1997)

240 Citations

Design pattern recovery in object-oriented software

G. Antoniol;R. Fiutem;L. Cristoforetti.
workshop on program comprehension (1998)

210 Citations

CERBERUS: Tracing Requirements to Source Code Using Information Retrieval, Dynamic Analysis, and Program Analysis

M. Eaddy;A.V. Aho;G. Antoniol;Y.-G. Gueheneuc.
international conference on program comprehension (2008)

209 Citations

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