Phil McMinn | The University of Sheffield (original) (raw)

Papers by Phil McMinn

Research paper thumbnail of Search-based software test data generation: a survey

Software Testing, Verification & Reliability, 2004

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Research paper thumbnail of An integrated systems biology approach to understanding the rules of keratinocyte colony formation

Journal of The Royal Society Interface, 2007

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Research paper thumbnail of A survey of evolutionary testing

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Research paper thumbnail of The State Problem for Evolutionary Testing

This paper shows how the presence of states in test objects can hinder or render impossible the s... more This paper shows how the presence of states in test objects can hinder or render impossible the search for test data using evolutionary testing. Additional guidance is required to find sequences of inputs that put the test object into some necessary state for certain test goals to become feasible. It is shown that data dependency analysis can be used to identify program statements responsible for state transitions, and then argued that an additional search is needed to find required transition sequences. In order to be able to deal with complex examples, the use of ant colony optimization is proposed. The results of a simple initial experiment are reported

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Research paper thumbnail of Agent Based Modelling Helps in Understanding the Rules by Which Fibroblasts Support Keratinocyte Colony Formation

PLOS One, 2008

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Research paper thumbnail of Evolutionary Testing Using an Extended Chaining Approach

Evolutionary Computation, 2006

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Research paper thumbnail of An Agent-Based software platform for modelling systems biology

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Research paper thumbnail of Evolutionary testing of state-based programs

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Research paper thumbnail of Hybridizing Evolutionary Testing with the Chaining Approach

Fitness functions derived for certain white-box test goals can cause problems for Evolutionary Te... more Fitness functions derived for certain white-box test goals can cause problems for Evolutionary Testing (ET), due to a lack of sufficient guidance to the required test data. Often this is because the search does not take into account data dependencies within the program, and the fact that some special intermediate statement (or statements) needs to have been executed in order for the target structure to be feasible. This paper proposes a solution which combines ET with the Chaining Approach. The Chaining Approach is a simple method which probes the data dependencies inherent to the test goal. By incorporating this facility into ET, the search can be directed into potentially promising, unexplored areas of the test object’s input domain. Encouraging results were obtained with the hybrid approach for seven programs known to originally cause problems for ET.

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Research paper thumbnail of Validation and discovery from computational biology models

Biosystems, 2008

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Research paper thumbnail of Using compression algorithms to support the comprehension of program traces

... Our future work will also look at existing visualisation tools to investigate how the hierarc... more ... Our future work will also look at existing visualisation tools to investigate how the hierarchical infor-mation can be used to make the visualisations more useful to the developer. Acknowledgments Walkinshaw and McMinn are supported by the EPSRC REGI grant EP/F065825/ ...

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Research paper thumbnail of Superstate identification for state machines using search-based clustering

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Research paper thumbnail of Testability Transformation - Program Transformation to Improve Testability

Testability transformation is a new form of program transformation in which the goal is not to pr... more Testability transformation is a new form of program transformation in which the goal is not to preserve the standard semantics of the program, but to preserve test sets that are adequate with respect to some chosen test adequacy criterion. The goal is to improve the testing process by transforming a program to one that is more amenable to testing while remaining within the same equivalence class of programs defined by the adequacy criterion. The approach to testing and the adequacy criterion are parameters to the overall approach. The transformations required are typically neither more abstract nor are they more concrete than standard “meaning preserving transformations”. This leads to interesting theoretical questions. but also has interesting practical implications. This chapter provides an introduction to testability transformation and a brief survey of existing results.

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Research paper thumbnail of Automated Test Data Generation for Coverage: Haven't We Solved This Problem Yet

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Research paper thumbnail of A Theoretical and Empirical Study of Search-Based Testing: Local, Global, and Hybrid Search

IEEE Transactions on Software Engineering, 2010

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Research paper thumbnail of A theoretical & empirical znalysis of evolutionary testing and hill climbing for structural test data generation

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Research paper thumbnail of A Theoretical & Empirical Analysis of Evolutionary Testing and Hill Climbing for Structural Test Data Generation

Evolutionary testing has been widely studied as a technique for automating the process of test ca... more Evolutionary testing has been widely studied as a technique for automating the process of test case generation. However, to date, there has been no theoretical examination of when and why it works. Furthermore, the empirical evidence for the effectiveness of evolutionary testing consists largely of small scale laboratory studies. This paper presents a first theoretical analysis of the scenarios in

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Research paper thumbnail of A multi-objective approach to search-based test data generation

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Research paper thumbnail of Search-based failure discovery using testability transformations to generate pseudo-oracles

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Research paper thumbnail of The impact of input domain reduction on search-based test data generation

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Research paper thumbnail of Search-based software test data generation: a survey

Software Testing, Verification & Reliability, 2004

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Research paper thumbnail of An integrated systems biology approach to understanding the rules of keratinocyte colony formation

Journal of The Royal Society Interface, 2007

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Research paper thumbnail of A survey of evolutionary testing

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Research paper thumbnail of The State Problem for Evolutionary Testing

This paper shows how the presence of states in test objects can hinder or render impossible the s... more This paper shows how the presence of states in test objects can hinder or render impossible the search for test data using evolutionary testing. Additional guidance is required to find sequences of inputs that put the test object into some necessary state for certain test goals to become feasible. It is shown that data dependency analysis can be used to identify program statements responsible for state transitions, and then argued that an additional search is needed to find required transition sequences. In order to be able to deal with complex examples, the use of ant colony optimization is proposed. The results of a simple initial experiment are reported

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Research paper thumbnail of Agent Based Modelling Helps in Understanding the Rules by Which Fibroblasts Support Keratinocyte Colony Formation

PLOS One, 2008

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Research paper thumbnail of Evolutionary Testing Using an Extended Chaining Approach

Evolutionary Computation, 2006

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Research paper thumbnail of An Agent-Based software platform for modelling systems biology

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Research paper thumbnail of Evolutionary testing of state-based programs

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Research paper thumbnail of Hybridizing Evolutionary Testing with the Chaining Approach

Fitness functions derived for certain white-box test goals can cause problems for Evolutionary Te... more Fitness functions derived for certain white-box test goals can cause problems for Evolutionary Testing (ET), due to a lack of sufficient guidance to the required test data. Often this is because the search does not take into account data dependencies within the program, and the fact that some special intermediate statement (or statements) needs to have been executed in order for the target structure to be feasible. This paper proposes a solution which combines ET with the Chaining Approach. The Chaining Approach is a simple method which probes the data dependencies inherent to the test goal. By incorporating this facility into ET, the search can be directed into potentially promising, unexplored areas of the test object’s input domain. Encouraging results were obtained with the hybrid approach for seven programs known to originally cause problems for ET.

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Research paper thumbnail of Validation and discovery from computational biology models

Biosystems, 2008

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Research paper thumbnail of Using compression algorithms to support the comprehension of program traces

... Our future work will also look at existing visualisation tools to investigate how the hierarc... more ... Our future work will also look at existing visualisation tools to investigate how the hierarchical infor-mation can be used to make the visualisations more useful to the developer. Acknowledgments Walkinshaw and McMinn are supported by the EPSRC REGI grant EP/F065825/ ...

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Research paper thumbnail of Superstate identification for state machines using search-based clustering

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Research paper thumbnail of Testability Transformation - Program Transformation to Improve Testability

Testability transformation is a new form of program transformation in which the goal is not to pr... more Testability transformation is a new form of program transformation in which the goal is not to preserve the standard semantics of the program, but to preserve test sets that are adequate with respect to some chosen test adequacy criterion. The goal is to improve the testing process by transforming a program to one that is more amenable to testing while remaining within the same equivalence class of programs defined by the adequacy criterion. The approach to testing and the adequacy criterion are parameters to the overall approach. The transformations required are typically neither more abstract nor are they more concrete than standard “meaning preserving transformations”. This leads to interesting theoretical questions. but also has interesting practical implications. This chapter provides an introduction to testability transformation and a brief survey of existing results.

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Research paper thumbnail of Automated Test Data Generation for Coverage: Haven't We Solved This Problem Yet

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Research paper thumbnail of A Theoretical and Empirical Study of Search-Based Testing: Local, Global, and Hybrid Search

IEEE Transactions on Software Engineering, 2010

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Research paper thumbnail of A theoretical & empirical znalysis of evolutionary testing and hill climbing for structural test data generation

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Research paper thumbnail of A Theoretical & Empirical Analysis of Evolutionary Testing and Hill Climbing for Structural Test Data Generation

Evolutionary testing has been widely studied as a technique for automating the process of test ca... more Evolutionary testing has been widely studied as a technique for automating the process of test case generation. However, to date, there has been no theoretical examination of when and why it works. Furthermore, the empirical evidence for the effectiveness of evolutionary testing consists largely of small scale laboratory studies. This paper presents a first theoretical analysis of the scenarios in

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Research paper thumbnail of A multi-objective approach to search-based test data generation

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Research paper thumbnail of Search-based failure discovery using testability transformations to generate pseudo-oracles

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Research paper thumbnail of The impact of input domain reduction on search-based test data generation

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