Applying genetic algorithm to increase the efficiency of a data flow-based test data generation approach

Mahajan, Manish; Kumar, Sumit; Porwal, Rabins

doi:10.1145/2347696.2347707

Cited by 23 publications

(7 citation statements)

References 12 publications

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“…Mahajan et al [25] applied genetic algorithm to improve data flow-based test data generation. In this approach, the authors use the CFG to generate the data flow model of the program under test (i.e.…”

Section: Related Work On Structural-based Testing Of Ao Programsmentioning

confidence: 99%

“…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%

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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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Section: Related Work On Structural-based Testing Of Ao Programsmentioning

confidence: 99%

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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“…Since then, several articles have been presented, e.g. [50][51][52][53][54][55]. It should be noted, however, that all of the results presented in these articles have been based on the fact that they had access to the source code.…”

Section: Related Workmentioning

confidence: 99%

Ontology-based Software Test Case Generation (OSTAG)

Tarasov

Tan

Adlemo

et al. 2015

European Projects in Knowledge Applications and Intelligent Systems

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Testing is a paramount quality assurance activity in every software development project, especially for embedded, safety critical systems. During the test process, a lot of effort is put into the generation of test cases. The presented OSTAG project aimed at developing methods and techniques to automate the software test case generation for black-box testing. The proposed approach was based on the creation of a software requirements ontology and the application of inference rules on the ontology to derive test cases. The ontology represents knowledge of the requirements, the software system and the corresponding application domain while the inference rules formalize knowledge from documents and experienced testers in the domain of test planning and test case generation. A software prototype of the approach was implemented and one of the industrial project partners evaluated the results. An alternative method for generating test cases, based on genetic algorithms, was also explored.

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“…The data flow testing approach can be used in combination with traditional coverage criteria to generate test data automatically. Meta heuristics like Genetic algorithms have been used effectively for this purpose [23].…”

Section: Integration Testingmentioning

confidence: 99%

A critical review of various testing techniques in aspect-oriented software systems

Singhal

Bansal

Kumar

2013

SIGSOFT Softw. Eng. Notes

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Software testing is a very crucial phase of the software development life cycle. In order to develop quality software using any approach such as module-oriented, object-oriented, aspect-oriented and componentbased, testing plays a crucial role. Aspect-Oriented Programming (AOP) is a relatively new software development approach and testing of software developed using this approach has not matured enough. Researchers have proposed various testing techniques for AOP. It is important to analyze existing Aspect-Oriented testing techniques in order to develop new, better, more efficient techniques. This paper presents a critical review of various existing testing techniques for AOP.

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Applying genetic algorithm to increase the efficiency of a data flow-based test data generation approach

Cited by 23 publications

References 12 publications

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

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

Ontology-based Software Test Case Generation (OSTAG)

A critical review of various testing techniques in aspect-oriented software systems

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