P. McMinn

Publications127
h-index38
Citations6,524
Highly Influential Citations466
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Search‐based software test data generation: a survey
  • P. McMinn
  • Computer Science
    Softw. Test. Verification Reliab.
  • 1 June 2004
TLDR
Some of the work undertaken in the use of metaheuristic search techniques for the automatic generation of test data is surveyed, discussing possible new future directions of research for each of its different individual areas.
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The Oracle Problem in Software Testing: A Survey
TLDR
This paper provides a comprehensive survey of current approaches to the test oracle problem and an analysis of trends in this important area of software testing research and practice.
View on IEEE
Search Based Software Engineering: Techniques, Taxonomy, Tutorial
TLDR
This tutorial will present the reader with a step-by-step guide to the application of SBSE techniques to Software Engineering, and assumes neither previous knowledge nor experience with Search Based Optimisation.
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An orchestrated survey of methodologies for automated software test case generation
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A Theoretical and Empirical Study of Search-Based Testing: Local, Global, and Hybrid Search
TLDR
A theoretical exploration of the most widely studied approach, the global search technique embodied by Genetic Algorithms, reveals that cases exist of test data generation problem that suit each algorithm, thereby suggesting that a hybrid global-local search (a Memetic Algorithm) may be appropriate.
View on IEEE
Do Automatically Generated Unit Tests Find Real Faults? An Empirical Study of Effectiveness and Challenges (T)
TLDR
Three state-of-the-art unit test generation tools for Java (Randoop, EvoSuite, and Agitar) are applied to the 357 real faults in the Defects4J dataset and investigated how well the generated test suites perform at detecting these faults.
View on IEEE
Search-Based Software Testing: Past, Present and Future
  • P. McMinn
  • Computer Science
    IEEE Fourth International Conference on Software…
  • 21 March 2011
TLDR
Past work and the current state of the art on Search-Based Software Testing are reviewed, and potential future research areas and open problems that remain in the field are discussed.
View on IEEE
Search-based software test data generation: a survey: Research Articles
TLDR
Some of the work undertaken in the use of metaheuristic search techniques for the automatic generation of test data is surveyed, discussing possible new future directions of research for each of its different individual areas.
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A Memetic Algorithm for whole test suite generation
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Symbolic search-based testing
TLDR
The algorithm combines symbolic information with dynamic analysis and has two key advantages: It does not require any change in the underlying test data generation technique and it avoids many problems traditionally associated with symbolic execution, in particular the presence of loops.
View on ACM
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