An Exploratory Study of Higher Order Mutation Testing in Aspect-Oriented Programming

Omar, Elmahdi; Ghosh, Sudipto

doi:10.1109/issre.2012.6

Cited by 22 publications

(17 citation statements)

References 22 publications

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“…Omar and Ghosh [29] proposed four approaches for generating higher order mutants for AspectJ programs, with a tool that automates these approaches and creates HOMs. AspectJ faults are classified according to where they occur, that is, faults that can occur in base classes, aspects, or in the interaction between the base classes and aspects.…”

Section: Related Workmentioning

confidence: 99%

“…Higher Order mutation testing is a mutation testing technique in which a mutant contains more than one fault. A number of studies (e.g., [26][27][28][29][30][31][32][33]) shows that higher order mutation supports solving the two problems of mutation testing, that is, help in reducing the number of generated mutants and reducing the number of equivalent mutants.…”

Section: Introductionmentioning

confidence: 99%

“…Several studies had used genetic algorithms to generate higher order mutants, and the results they obtained are promising (e.g., [27][28][29]). In order to apply the proposed approach, a software tool has been implemented with Java called HOMJava (Higher Order Mutation for Java).…”

Section: Introductionmentioning

confidence: 99%

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An Approach for the Generation of Higher Order Mutants Using Genetic Algorithms

Abuljadayel¹,

Wedyan²

2018

IJISA

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Abstract-Mutation testing is a structural testing technique in which the effectiveness of a test suite is measured by the suite ability to detect seeded faults. One fault is seeded into a copy of the program, called mutant, leading to a large number of mutants with a high cost of compiling and running the test suite against the mutants. Moreover, many of the mutants produce the same output as the original program (called equivalent mutants), such mutants need to be minimized to produce accurate results. Higher order mutation testing aims at solving these problems by allowing more than one fault to be seeded in the mutant. Recent work in higher order mutation show promising result in reducing the cost of mutation testing and increasing the approach effectiveness. In this paper, we present an approach for generating higher order mutants using a genetic algorithm. The aim of the proposed approach is to produce subtle and harder to kill mutants, and reduce the percentage of produced equivalent mutants. A Java tool has been developed, called HOMJava (Higher Order Mutation for Java), which implements the proposed approach. An experimental study was performed to evaluate the effectiveness of the proposed approach. The results show that the approach was able to produce subtle higher order mutants, the fitness of mutants improved by almost 99% compared with the first order mutants used in the experiment. The percentage of produced equivalent mutants was about 4%.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Approach for the Generation of Higher Order Mutants Using Genetic Algorithms

Abuljadayel¹,

Wedyan²

2018

IJISA

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“…Omar and Ghosh [18] presented four approaches to generate higher order mutants for AspectJ programs. The approaches were evaluated in terms of the ability to create mutants of higher order resulting in higher efficacy and less effort when compared with first order mutants.…”

Section: Related Work On Mutation-based Testingmentioning

confidence: 99%

“…Ever since, the software testing community has been investigating ways of dealing with the challenges described by them. In summary, research on testing of AO programs (hereafter called AO testing) has been mainly concerned with: (i) the characterisation of fault types and bug patterns [2][3][4][5][6][7], (ii) the definition of underlying test models and test selection criteria [8][9][10][11][12][13][14][15][16][17][18] and (iii) the provision of automated tool support [11,14,16,[18][19][20][21][22]. In particular, structural-based and mutation-based testing have been on focus by several research initiatives [8,9,[11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Testing of aspect-oriented programs: difficulties and lessons learned based on theoretical and practical experience

et al. 2015

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Background: Since the first discussions of new challenges posed by aspect-oriented programming (AOP) to software testing, the real difficulties of testing aspect-oriented (AO) programs have not been properly analysed. Firstly, despite the customisation of traditional testing techniques to the AOP context, the literature lacks discussions on how hard it is to apply them to (even ordinary) AO programs based on practical experience. Secondly, and equally important, due to the cautious AOP adoption focused on concern refactoring, test reuse is another relevant issue that has been overlooked so far. This paper deals with these two issues. It discusses the difficulties of testing AO programs from three perspectives: (i) structural-based testing, (ii) fault-based testing and (iii) test set reuse across paradigms. Methods: Perspectives (i) and (ii) are addressed by means of a retrospective of research done by the authors' group. We analyse the impact of using AOP mechanisms on the testability of programs in terms of the underlying test models, the derived test requirements and the coverage of such requirements. The discussion is based on our experience on developing and applying testing approaches and tools to AspectJ programs at both unit and integration levels. Perspective (iii), on the other hand, consists of recent exploratory studies that analyse the effort to adapt test sets for refactored systems and the quality of such test sets in terms of structural coverage. Results: Building test models for AO programs imposes higher complexity when compared to the OO paradigm. Besides this, adapting test suites for OO programs to AO equivalent programs tends to require less effort than doing the other way around, and resulting suites achieve similar quality levels for small-sized aplications. Conclusions: The conclusion is that building test models for AO programs, as well as deriving and covering paradigm-specific test requirements, is not straightforward as it has been for procedural and object-oriented (OO) programs at some extent. Once you have test suites in conformance with programs implemented in both paradigms, the quality of such suited in termos of code coverage may vary depending on the size and characteristics of the applications under testing.

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Increasing Mutation Testing Effectiveness by Combining Lower Order Mutants to Construct Higher Order Mutants

Nguyen

2020

Lecture Notes in Computer Science

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An Exploratory Study of Higher Order Mutation Testing in Aspect-Oriented Programming

Cited by 22 publications

References 22 publications

An Approach for the Generation of Higher Order Mutants Using Genetic Algorithms

An Approach for the Generation of Higher Order Mutants Using Genetic Algorithms

Testing of aspect-oriented programs: difficulties and lessons learned based on theoretical and practical experience

Increasing Mutation Testing Effectiveness by Combining Lower Order Mutants to Construct Higher Order Mutants

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