H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 33 Citations 4,717 133 World Ranking 6946 National Ranking 8

Overview

What is he best known for?

The fields of study he is best known for:

  • Operating system
  • Programming language
  • Artificial intelligence

Tegawendé F. Bissyandé spends much of his time researching Android, World Wide Web, Malware, Software and Computer security. His Android research integrates issues from Java, Machine learning and Static analysis. His research integrates issues of Security analysis, Functional requirement and Static program analysis in his study of Java.

Within one scientific family, Tegawendé F. Bissyandé focuses on topics pertaining to Software development under World Wide Web, and may sometimes address concerns connected to Construct. His studies in Malware integrate themes in fields like Detector and Artificial intelligence. His Software study combines topics in areas such as Software engineering and Reverse engineering.

His most cited work include:

  • IccTA: detecting inter-component privacy leaks in Android apps (358 citations)
  • AndroZoo: collecting millions of Android apps for the research community (267 citations)
  • Network Structure of Social Coding in GitHub (125 citations)

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

His primary areas of investigation include Android, Malware, Artificial intelligence, World Wide Web and Software. His Android research is multidisciplinary, incorporating elements of Computer security, Static analysis, Java and Data science. His Malware research integrates issues from Scalability, Mobile apps and Internet privacy.

His Artificial intelligence research includes elements of Natural language processing, Machine learning, Time series, Code and Pattern recognition. His work on Software development, Software product line and Software bug as part of his general Software study is frequently connected to Context, thereby bridging the divide between different branches of science. The study incorporates disciplines such as Software engineering and Source code in addition to Software development.

He most often published in these fields:

  • Android (37.06%)
  • Malware (21.76%)
  • Artificial intelligence (20.00%)

What were the highlights of his more recent work (between 2019-2021)?

  • Android (37.06%)
  • Malware (21.76%)
  • Artificial intelligence (20.00%)

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

His main research concerns Android, Malware, Artificial intelligence, Code and Machine learning. His Android study results in a more complete grasp of Operating system. His study in Malware is interdisciplinary in nature, drawing from both Human–computer interaction, Misinformation, Mobile apps, Focus and Internet privacy.

His work deals with themes such as Field and Natural language processing, which intersect with Artificial intelligence. His study with Code involves better knowledge in Computer security. Tegawendé F. Bissyandé focuses mostly in the field of Machine learning, narrowing it down to matters related to Correctness and, in some cases, Leverage, Test effort and Java.

Between 2019 and 2021, his most popular works were:

  • Mining Fix Patterns for FindBugs Violations (34 citations)
  • Rebooting Research on Detecting Repackaged Android Apps: Literature Review and Benchmark (26 citations)
  • FixMiner: Mining relevant fix patterns for automated program repair (15 citations)

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

  • Operating system
  • Programming language
  • Artificial intelligence

The scientist’s investigation covers issues in Android, Malware, Artificial intelligence, Machine learning and Mobile apps. His Android research is multidisciplinary, incorporating perspectives in Documentation, Software system, Deprecation and Maintainability, Software engineering. His studies deal with areas such as Reboot and Data science as well as Malware.

His study in the field of Benchmark is also linked to topics like Test suite. The various areas that Tegawendé F. Bissyandé examines in his Machine learning study include Software and Software development. His Mobile apps study is focused on World Wide Web in general.

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

IccTA: detecting inter-component privacy leaks in Android apps

Li Li;Alexandre Bartel;Tegawende F. Bissyande;Jacques Klein.
international conference on software engineering (2015)

488 Citations

AndroZoo: collecting millions of Android apps for the research community

Kevin Allix;Tegawende F. Bissyande;Jacques Klein;Yves Le Traon.
mining software repositories (2016)

399 Citations

Network Structure of Social Coding in GitHub

F. Thung;T. F. Bissyande;D. Lo;Lingxiao Jiang.
conference on software maintenance and reengineering (2013)

212 Citations

Popularity, Interoperability, and Impact of Programming Languages in 100,000 Open Source Projects

Tegawende F. Bissyande;Ferdian Thung;David Lo;Lingxiao Jiang.
computer software and applications conference (2013)

133 Citations

Understanding Android App Piggybacking: A Systematic Study of Malicious Code Grafting

Li Li;Daoyuan Li;Tegawende F. Bissyande;Jacques Klein.
IEEE Transactions on Information Forensics and Security (2017)

127 Citations

DroidRA: taming reflection to support whole-program analysis of Android apps

Li Li;Tegawendé F. Bissyandé;Damien Octeau;Jacques Klein.
international symposium on software testing and analysis (2016)

125 Citations

Got issues? Who cares about it? A large scale investigation of issue trackers from GitHub

Tegawende F. Bissyande;David Lo;Lingxiao Jiang;Laurent Reveillere.
international symposium on software reliability engineering (2013)

121 Citations

An Investigation into the Use of Common Libraries in Android Apps

Li Li;Tegawende F. Bissyande;Jacques Klein;Yves Le Traon.
ieee international conference on software analysis evolution and reengineering (2016)

118 Citations

Bottom-up adoption of software product lines: a generic and extensible approach

Jabier Martinez;Tewfik Ziadi;Tegawendé F. Bissyandé;Jacques Klein.
software product lines (2015)

103 Citations

ApkCombiner: Combining Multiple Android Apps to Support Inter-App Analysis

Li Li;Alexandre Bartel;Tegawendé François D Assise Bissyande;Jacques Klein.
information security conference (2015)

100 Citations

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