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 46 Citations 8,331 145 World Ranking 3447 National Ranking 1787

Overview

What is he best known for?

The fields of study he is best known for:

  • Programming language
  • Operating system
  • Software

His scientific interests lie mostly in Symbolic execution, Programming language, Theoretical computer science, Algorithm and Code coverage. Symbolic execution is a subfield of Software that he explores. His study involves Program analysis, Concolic testing, Object-oriented programming, Software development and Keyword-driven testing, a branch of Programming language.

His Theoretical computer science research is multidisciplinary, incorporating perspectives in Solver and Data mining. Nikolai Tillmann usually deals with Algorithm and limits it to topics linked to Set and Parameterized complexity and Test case. His Code coverage study integrates concerns from other disciplines, such as Object, Iterative method, Unit testing and Heuristic.

His most cited work include:

  • Pex: white box test generation for .NET (674 citations)
  • Symbolic execution for software testing in practice: preliminary assessment (262 citations)
  • Parameterized unit tests (230 citations)

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

His primary scientific interests are in Programming language, Symbolic execution, Software, Unit testing and Software engineering. The Programming language study which covers Test case that intersects with Process. His Concolic testing study, which is part of a larger body of work in Symbolic execution, is frequently linked to Constraint satisfaction problem, bridging the gap between disciplines.

His Software study which covers Code that intersects with Algorithm, Source code and Artificial intelligence. His Unit testing study combines topics from a wide range of disciplines, such as White-box testing, Parameterized complexity, Dynamic testing, Real-time computing and Non-regression testing. His research in Software engineering intersects with topics in Test strategy and Software development, Software construction.

He most often published in these fields:

  • Programming language (32.35%)
  • Symbolic execution (29.41%)
  • Software (17.65%)

What were the highlights of his more recent work (between 2013-2017)?

  • Cloud computing (14.12%)
  • Symbolic execution (29.41%)
  • Multimedia (12.94%)

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

Nikolai Tillmann mainly investigates Cloud computing, Symbolic execution, Multimedia, Programming language and World Wide Web. His research integrates issues of Human–computer interaction, App store, Mobile device and JavaScript in his study of Cloud computing. His studies deal with areas such as Microsoft Visual Studio, Unit testing and Source code as well as Symbolic execution.

His studies in Unit testing integrate themes in fields like Dynamic testing, Software engineering, Software performance testing and Systems engineering. His work deals with themes such as Web application and Software development, which intersect with Multimedia. His Programming language research incorporates themes from Test case and Code.

Between 2013 and 2017, his most popular works were:

  • Code hunt: experience with coding contests at scale (37 citations)
  • Transferring an automated test generation tool to practice: from pex to fakes and code digger (28 citations)
  • Code hunt: gamifying teaching and learning of computer science at scale (24 citations)

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

  • Programming language
  • Operating system
  • Software

Symbolic execution, Multimedia, World Wide Web, Programming language and Coding are his primary areas of study. He interconnects Random testing and Source code in the investigation of issues within Symbolic execution. The various areas that Nikolai Tillmann examines in his Source code study include White-box testing, Code, Redundant code, Test case and Artificial intelligence.

Nikolai Tillmann has included themes like Microsoft Visual Studio, Download and Task in his Multimedia study. When carried out as part of a general World Wide Web research project, his work on HTML5 is frequently linked to work in Native API, therefore connecting diverse disciplines of study. His Programming language research includes elements of Use case and Code generation.

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

Pex: white box test generation for .NET

Nikolai Tillmann;Jonathan De Halleux.
tests and proofs (2008)

1141 Citations

Symbolic execution for software testing in practice: preliminary assessment

Cristian Cadar;Patrice Godefroid;Sarfraz Khurshid;Corina S. Pasareanu.
international conference on software engineering (2011)

426 Citations

Demand-driven compositional symbolic execution

Saswat Anand;Patrice Godefroid;Nikolai Tillmann.
tools and algorithms for construction and analysis of systems (2008)

319 Citations

Parameterized unit tests

Nikolai Tillmann;Wolfram Schulte.
foundations of software engineering (2005)

292 Citations

Fitness-guided path exploration in dynamic symbolic execution

Tao Xie;Nikolai Tillmann;Jonathan de Halleux;Wolfram Schulte.
dependable systems and networks (2009)

286 Citations

Model-based testing of object-oriented reactive systems with spec explorer

Margus Veanes;Colin Campbell;Wolfgang Grieskamp;Wolfram Schulte.
formal methods (2008)

244 Citations

DySy: dynamic symbolic execution for invariant inference

Christoph Csallner;Nikolai Tillmann;Yannis Smaragdakis.
international conference on software engineering (2008)

228 Citations

Approximating finite domains in symbolic state exploration

Nikolai Tillmann;Wolfgang Grieskamp;Wolfram Schulte.
(2005)

222 Citations

Path Feasibility Analysis for String-Manipulating Programs

Nikolaj Bjørner;Nikolai Tillmann;Andrei Voronkov.
tools and algorithms for construction and analysis of systems (2009)

213 Citations

Rex: Symbolic Regular Expression Explorer

Margus Veanes;Peli de Halleux;Nikolai Tillmann.
international conference on software testing, verification, and validation (2010)

169 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Nikolai Tillmann

Gordon Fraser

Gordon Fraser

University of Passau

Publications: 52

Tao Xie

Tao Xie

Peking University

Publications: 46

Mark Harman

Mark Harman

University College London

Publications: 32

Sarfraz Khurshid

Sarfraz Khurshid

The University of Texas at Austin

Publications: 28

Andrea Arcuri

Andrea Arcuri

Campus Kristiania

Publications: 26

Nikolaj Bjørner

Nikolaj Bjørner

Microsoft (United States)

Publications: 23

Koushik Sen

Koushik Sen

University of California, Berkeley

Publications: 23

Darko Marinov

Darko Marinov

University of Illinois at Urbana-Champaign

Publications: 22

Mauro Pezzè

Mauro Pezzè

Universita della Svizzera Italiana

Publications: 22

Lu Zhang

Lu Zhang

Peking University

Publications: 20

Willem Visser

Willem Visser

Stellenbosch University

Publications: 19

Michael D. Ernst

Michael D. Ernst

University of Washington

Publications: 19

Dawn Song

Dawn Song

University of California, Berkeley

Publications: 19

Patrice Godefroid

Patrice Godefroid

Microsoft (United States)

Publications: 18

Robert M. Hierons

Robert M. Hierons

University of Sheffield

Publications: 17

Zhendong Su

Zhendong Su

ETH Zurich

Publications: 16

Something went wrong. Please try again later.