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 47 Citations 9,335 226 World Ranking 4204 National Ranking 185

Overview

What is he best known for?

The fields of study he is best known for:

  • Programming language
  • Software
  • Artificial intelligence

His primary areas of investigation include Unit testing, Test suite, Software, Code coverage and Test case. His research investigates the connection between Unit testing and topics such as Software engineering that intersect with problems in Software construction and Root cause. Fault detection and isolation and Variation is closely connected to Software testing in his research, which is encompassed under the umbrella topic of Test suite.

His Software study integrates concerns from other disciplines, such as Java, Test data generation and Automatic test pattern generation. His work deals with themes such as Reliability engineering and Data mining, which intersect with Code coverage. Gordon Fraser has researched Test case in several fields, including Formal specification and Computer engineering.

His most cited work include:

  • EvoSuite: automatic test suite generation for object-oriented software (536 citations)
  • Are mutants a valid substitute for real faults in software testing (367 citations)
  • Whole Test Suite Generation (361 citations)

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

His primary areas of study are Software engineering, Unit testing, Code coverage, Test and Test case. His study looks at the relationship between Software engineering and fields such as Software, as well as how they intersect with chemical problems. His Unit testing research integrates issues from Java, Search-based software engineering and Regression testing.

As a part of the same scientific study, he usually deals with the Code coverage, concentrating on Genetic algorithm and frequently concerns with Theoretical computer science. His Test research incorporates themes from Empirical research, Data mining, Artificial intelligence and Code. His Test suite research is multidisciplinary, relying on both Test data generation, Reliability engineering, Machine learning and Test Management Approach.

He most often published in these fields:

  • Software engineering (28.05%)
  • Unit testing (28.51%)
  • Code coverage (25.79%)

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

  • Scratch (6.33%)
  • Software engineering (28.05%)
  • Test (23.98%)

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

His main research concerns Scratch, Software engineering, Test, Java and Code. Gordon Fraser focuses mostly in the field of Software engineering, narrowing it down to topics relating to Software testing and, in certain cases, Quality software and University level. His research in Test is mostly concerned with Code coverage.

His Code coverage research includes elements of Genetic algorithm, Premature convergence, Source code and Search algorithm. His studies in Machine learning integrate themes in fields like Test suite, Fitness landscape and Testability. Gordon Fraser interconnects False positive paradox, Maintainability, Test case, Benchmark and Software in the investigation of issues within Empirical research.

Between 2019 and 2021, his most popular works were:

  • Revisiting the relationship between fault detection, test adequacy criteria, and test set size (6 citations)
  • Common Bugs in Scratch Programs (5 citations)
  • Verified from scratch: program analysis for learners' programs (3 citations)

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

  • Programming language
  • Artificial intelligence
  • Software

Code, Scratch, Software quality, Test and Programming language are his primary areas of study. His research in Code intersects with topics in Machine learning, Unit testing and Artificial intelligence. His study in Machine learning is interdisciplinary in nature, drawing from both Software development, Test suite, Benchmark, Maintainability and Empirical research.

The various areas that he examines in his Artificial intelligence study include Test case, Workflow and Code review. Gordon Fraser works in the field of Test, namely Code coverage. His work on Java code and Executable as part of general Programming language study is frequently linked to Competition, bridging the gap between disciplines.

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

EvoSuite: automatic test suite generation for object-oriented software

Gordon Fraser;Andrea Arcuri.
foundations of software engineering (2011)

880 Citations

Are mutants a valid substitute for real faults in software testing

René Just;Darioush Jalali;Laura Inozemtseva;Michael D. Ernst.
foundations of software engineering (2014)

653 Citations

Mutation-Driven Generation of Unit Tests and Oracles

G. Fraser;A. Zeller.
IEEE Transactions on Software Engineering (2012)

627 Citations

Whole Test Suite Generation

G. Fraser;A. Arcuri.
IEEE Transactions on Software Engineering (2013)

549 Citations

A Survey on Metamorphic Testing

Sergio Segura;Gordon Fraser;Ana B. Sanchez;Antonio Ruiz-Cortes.
IEEE Transactions on Software Engineering (2016)

319 Citations

Evaluating and improving fault localization

Spencer Pearson;Jose Campos;Rene Just;Gordon Fraser.
international conference on software engineering (2017)

302 Citations

Parameter tuning or default values? An empirical investigation in search-based software engineering

Andrea Arcuri;Gordon Fraser.
Empirical Software Engineering (2013)

296 Citations

Testing with model checkers: a survey

Gordon Fraser;Franz Wotawa;Paul E. Ammann.
Software Testing, Verification & Reliability (2009)

284 Citations

On parameter tuning in search based software engineering

Andrea Arcuri;Gordon Fraser.
symposium on search based software engineering (2011)

212 Citations

Do Automatically Generated Unit Tests Find Real Faults? An Empirical Study of Effectiveness and Challenges (T)

Sina Shamshiri;Rene Just;Jose Miguel Rojas;Gordon Fraser.
automated software engineering (2015)

194 Citations

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