D-Index & Metrics Best Publications
Computer Science
Germany
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 64 Citations 21,835 281 World Ranking 1590 National Ranking 60

Research.com Recognitions

Awards & Achievements

2023 - Research.com Computer Science in Germany Leader Award

2010 - ACM Fellow For contributions to automated debugging, and to mining software archives.

Overview

What is he best known for?

The fields of study he is best known for:

  • Programming language
  • Operating system
  • Software

Programming language, Software, Data mining, Debugging and Delta Debugging are his primary areas of study. His Software research incorporates themes from Automatic test pattern generation and Component. The concepts of his Data mining study are interwoven with issues in Software bug, Artificial intelligence, Pattern recognition, Static analysis and Code smell.

His Artificial intelligence research integrates issues from Machine learning, Software maintenance, Set and Natural language processing. His Debugging study combines topics from a wide range of disciplines, such as Recommendation model and Software engineering. His Delta Debugging study combines topics in areas such as Tracing and Algorithmic program debugging.

His most cited work include:

  • Mining version histories to guide software changes (781 citations)
  • Simplifying and isolating failure-inducing input (754 citations)
  • Mining metrics to predict component failures (646 citations)

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

The scientist’s investigation covers issues in Programming language, Software, Software engineering, Debugging and Code. His studies link Delta Debugging with Programming language. His Software research is multidisciplinary, relying on both Empirical research, Data mining and Source code.

His Data mining research includes themes of Machine learning and Artificial intelligence. Andreas Zeller studies Algorithmic program debugging, a branch of Debugging. His Java study integrates concerns from other disciplines, such as Object-oriented programming and Theoretical computer science.

He most often published in these fields:

  • Programming language (23.72%)
  • Software (20.07%)
  • Software engineering (17.15%)

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

  • Programming language (23.72%)
  • Fuzz testing (5.11%)
  • Android (9.85%)

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

Andreas Zeller mainly focuses on Programming language, Fuzz testing, Android, Parsing and Python. In Programming language, Andreas Zeller works on issues like Maintenance engineering, which are connected to Visualization. His Fuzz testing research incorporates elements of Replication, Lift, Byte and Algorithm.

The various areas that Andreas Zeller examines in his Android study include Test, Pointer, User interface, App store and Empirical research. Andreas Zeller focuses mostly in the field of Debugging, narrowing it down to topics relating to Program analysis and, in certain cases, Process and Semantics. Andreas Zeller interconnects Coding, Software engineering, Data science and Code in the investigation of issues within Software.

Between 2018 and 2021, his most popular works were:

  • Learning user interface element interactions (13 citations)
  • The Fuzzing Book (12 citations)
  • Parser-directed fuzzing (12 citations)

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

  • Programming language
  • Operating system
  • Software

Andreas Zeller mainly investigates Fuzz testing, Programming language, Software, Code and Parsing. His study in Fuzz testing is interdisciplinary in nature, drawing from both Symbolic data analysis, Constraint and JavaScript. Many of his studies on Programming language apply to Robustness as well.

The Software study combines topics in areas such as Test, Control, Coding and Software engineering. His work deals with themes such as Visualization, Software quality and Maintenance engineering, which intersect with Code. His Parsing study combines topics in areas such as Lexical analysis, Security token, Byte and Lisp.

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

Mining version histories to guide software changes

T. Zimmermann;A. Zeller;P. Weissgerber;S. Diehl.
IEEE Transactions on Software Engineering (2005)

1676 Citations

Simplifying and isolating failure-inducing input

A. Zeller;R. Hildebrandt.
IEEE Transactions on Software Engineering (2002)

1142 Citations

Mining metrics to predict component failures

Nachiappan Nagappan;Thomas Ball;Andreas Zeller.
international conference on software engineering (2006)

1027 Citations

When do changes induce fixes

Jacek Śliwerski;Thomas Zimmermann;Andreas Zeller.
mining software repositories (2005)

1021 Citations

Predicting Defects for Eclipse

Thomas Zimmermann;Rahul Premraj;Andreas Zeller.
model driven engineering languages and systems (2007)

880 Citations

Locating causes of program failures

Holger Cleve;Andreas Zeller.
international conference on software engineering (2005)

831 Citations

Isolating cause-effect chains from computer programs

Andreas Zeller.
foundations of software engineering (2002)

802 Citations

Why Programs Fail: A Guide to Systematic Debugging

Andreas Zeller.
(2005)

797 Citations

Mining version histories to guide software changes

T. Zimmermann;P. Weibgerber;S. Diehl;A. Zeller.
international conference on software engineering (2004)

728 Citations

Predicting Faults from Cached History

Sunghun Kim;T. Zimmermann;E.J. Whitehead;A. Zeller.
international conference on software engineering (2007)

642 Citations

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