D-Index & Metrics Best Publications

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 55 Citations 11,461 307 World Ranking 2877 National Ranking 1515

Overview

What is he best known for?

The fields of study he is best known for:

  • Programming language
  • Operating system
  • Algorithm

Daniel Kroening mainly focuses on Model checking, Programming language, Theoretical computer science, Software and Predicate abstraction. His Model checking study is concerned with the larger field of Algorithm. His study looks at the relationship between Programming language and fields such as Verilog, as well as how they intersect with chemical problems.

His Theoretical computer science study integrates concerns from other disciplines, such as ANSI C, Propositional calculus, Pointer and Symbolic execution. His Software research integrates issues from Machine learning, Correctness, Artificial intelligence and Deep neural networks. His studies in Predicate abstraction integrate themes in fields like Kernel, Boolean algebra, Reachability, Shared memory and Abstraction model checking.

His most cited work include:

  • A Tool for Checking ANSI-C Programs (1120 citations)
  • Behavioral consistency of C and Verilog programs using bounded model checking (268 citations)
  • SATABS: SAT-Based predicate abstraction for ANSI-C (261 citations)

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

His main research concerns Programming language, Theoretical computer science, Model checking, Software and Algorithm. His Programming language course of study focuses on Verilog and Formal equivalence checking. Theoretical computer science connects with themes related to Set in his study.

His research integrates issues of Discrete mathematics, Counterexample, Program analysis and Correctness in his study of Model checking. His work focuses on many connections between Software and other disciplines, such as Parallel computing, that overlap with his field of interest in Thread. He has included themes like Software verification and validation, Verification, Software engineering and Embedded software in his Software verification study.

He most often published in these fields:

  • Programming language (32.86%)
  • Theoretical computer science (31.16%)
  • Model checking (30.59%)

What were the highlights of his more recent work (between 2016-2021)?

  • Software (19.26%)
  • Programming language (32.86%)
  • Artificial intelligence (5.10%)

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

His scientific interests lie mostly in Software, Programming language, Artificial intelligence, Theoretical computer science and Deep neural networks. The concepts of his Software study are interwoven with issues in Java and Software engineering. Daniel Kroening regularly links together related areas like Exploit in his Programming language studies.

His studies examine the connections between Artificial intelligence and genetics, as well as such issues in Machine learning, with regards to Range, Benchmark and Set. His Theoretical computer science study frequently links to adjacent areas such as Modular design. Daniel Kroening works mostly in the field of Model checking, limiting it down to topics relating to Software verification and, in certain cases, Embedded software.

Between 2016 and 2021, his most popular works were:

  • Concolic testing for deep neural networks (144 citations)
  • Testing Deep Neural Networks (102 citations)
  • Reinforcement Learning for Temporal Logic Control Synthesis with Probabilistic Satisfaction Guarantees (33 citations)

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

  • Programming language
  • Operating system
  • Algorithm

The scientist’s investigation covers issues in Deep neural networks, Reinforcement learning, Mathematical optimization, Artificial intelligence and Limit. His research on Deep neural networks also deals with topics like

  • Adversarial system, which have a strong connection to Data science, Computer security and Software verification,
  • Concolic testing which intersects with area such as Symbolic data analysis, Computer engineering and Debugging. His Software verification research is multidisciplinary, incorporating perspectives in Java and Model checking, Bounded model checker.

His Machine learning research includes elements of Software and Code coverage. Java bytecode is connected with Set and Programming language in his research. Daniel Kroening interconnects Data center and Code in the investigation of issues within Programming language.

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

A Tool for Checking ANSI-C Programs

Edmund M. Clarke;Daniel Kroening;Flavio Lerda.
tools and algorithms for construction and analysis of systems (2004)

1735 Citations

A Survey of Automated Techniques for Formal Software Verification

V. D'Silva;D. Kroening;G. Weissenbacher.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2008)

504 Citations

Behavioral consistency of C and Verilog programs using bounded model checking

Edmund Clarke;Daniel Kroening;Karen Yorav.
design automation conference (2003)

401 Citations

Satabs : SAT-based predicate abstraction for ANSI-C

Edmund Clarke;Daniel Kroening;Natasha Sharygina;Karen Yorav.
Lecture Notes in Computer Science (2005)

396 Citations

Decision Procedures: An Algorithmic Point of View

Daniel Kroening;Ofer Strichman.
(2008)

382 Citations

CBMC – C Bounded Model Checker

Daniel Kroening;Michael Tautschnig.
tools and algorithms for construction and analysis of systems (2014)

321 Citations

Efficient computation of recurrence diameters

Daniel Kroening;Ofer Strichman.
Lecture Notes in Computer Science (2003)

316 Citations

Predicate Abstraction of ANSI-C Programs Using SAT

Edmund Clarke;Daniel Kroening;Natasha Sharygina;Karen Yorav.
formal methods (2004)

277 Citations

Concolic testing for deep neural networks

Youcheng Sun;Min Wu;Wenjie Ruan;Xiaowei Huang.
automated software engineering (2018)

240 Citations

Error explanation with distance metrics

Alex Groce;Sagar Chaki;Daniel Kroening;Ofer Strichman.
International Journal on Software Tools for Technology Transfer (2006)

211 Citations

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