Implementation of Efficient Test Case Optimization Technique Using Meta-Heuristic Algorithm

Test case selection helps in improving quality of test suites by removing ambiguous, redundant test cases, thereby reducing the cost of software testing. Various works carried out have chosen test cases based on single parameter and optimized the test cases using single objective employing single strategies. In this article, a parameter selection technique is combined with an optimization technique for optimizing the selection of test cases. A two-step approach has been employed. In first step, the fuzzy entropy-based filtration is used for test case fitness evaluation and selection. In second step, the improvised ant colony optimization is employed to select test cases from the previously reduced test suite. The experimental evaluation using coverage parameters namely, average percentage statement coverage and average percentage decision coverage along with suite size reduction, demonstrate that by using this proposed approach, test suite size can be reduced, reducing further the computational effort incurred.

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Efficient test case generation for validation of UML activity diagrams

Design Automation for Embedded Systems ◽

10.1007/s10617-010-9052-4 ◽

2010 ◽

Vol 14 (2) ◽

pp. 105-130 ◽

Cited By ~ 12

Author(s):

Mingsong Chen ◽

Prabhat Mishra ◽

Dhrubajyoti Kalita

Keyword(s):

Test Case Generation ◽

Test Case ◽

Activity Diagrams ◽

Efficient Test ◽

Uml Activity Diagrams

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Efficient Test Case Generation for Thread-Safe Classes

IEEE Access ◽

10.1109/access.2019.2901588 ◽

2019 ◽

Vol 7 ◽

pp. 26984-26995

Author(s):

Lili Bo ◽

Shujuan Jiang ◽

Junyan Qian ◽

Rongcun Wang ◽

Xingya Wang

Keyword(s):

Test Case Generation ◽

Test Case ◽

Efficient Test

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Optimization of Test Cases in Object-Oriented Systems Using Fractional-SMO

International Journal of Open Source Software and Processes ◽

10.4018/ijossp.2021010103 ◽

2021 ◽

Vol 12 (1) ◽

pp. 41-59

Author(s):

Satya Sobhan Panigrahi ◽

Ajay Kumar Jena

Keyword(s):

Unified Modeling Language ◽

Boundary Structure ◽

Test Case ◽

Test Cases ◽

Unified Modeling ◽

Efficient Test ◽

Fitness Value ◽

Fitness Parameters ◽

And Behavior ◽

Object Oriented Systems

This paper introduces the technique to select the test cases from the unified modeling language (UML) behavioral diagram. The UML behavioral diagram describes the boundary, structure, and behavior of the system that is fed as input for generating the graph. The graph is constructed by assigning the weights, nodes, and edges. Then, test case sequences are created from the graph with minimal fitness value. Then, the optimal sequences are selected from the proposed fractional-spider monkey optimization (fractional-SMO). The developed fractional-SMO is designed by integrating fractional calculus and SMO. Thus, the efficient test cases are selected based on the optimization algorithm that uses fitness parameters, like coverage and fault. Simulations are performed via five synthetic UML diagrams taken from the dataset. The performance of the proposed technique is computed using coverage and the number of test cases. The maximal coverage of 49 and the minimal number of test cases as 2,562 indicate the superiority of the proposed technique.

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An Effective Mixed Annealing/Heuristic Algorithm for Problems in Mechanical Design

Journal of Mechanical Design ◽

10.1115/1.2826694 ◽

1995 ◽

Vol 117 (3) ◽

pp. 409-418 ◽

Cited By ~ 7

Author(s):

M. M. Ogot ◽

S. S. Alag

Keyword(s):

Stochastic Optimization ◽

Heuristic Algorithm ◽

Design Space ◽

Simulated Annealing Algorithm ◽

Mechanical Design ◽

Optimization Technique ◽

Computation Time ◽

Optimization Methods ◽

Computational Effort ◽

Stochastic Algorithm

The wide application of stochastic optimization methods in mechanical design has been partially hindered due to (a) the relatively long computation time required, and (b) discretization of the design space at the onset of the optimization process. This work proposes a new stochastic algorithm, the Mixed Annealing/Heuristic Algorithm (MAH), which addresses both these issues. It is based on the Simulated Annealing algorithm (SA) and the Heuristic Optimization Technique (HOT). Both these algorithms have been successfully applied to problems in mechanical design and up to now have been considered as competing algorithms. MAH capitalizes on each of their individual strengths and addresses their weaknesses, thereby considerably reducing the computational effort required to attain the final solution. A pseudo-continuous approach for configuration generation is employed, making the discretization of the design space no longer necessary. The effectiveness of MAH is demonstrated via three problems in kinematic synthesis. Comparison of the results with other stochastic optimization methods illustrates the potential of this technique.

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Validation of a CFD-Based Numerical Wave Tank Model of the 1/20th Scale Wavestar Wave Energy Converter

Fluids ◽

10.3390/fluids5030112 ◽

2020 ◽

Vol 5 (3) ◽

pp. 112

Author(s):

Christian Windt ◽

Nicolás Faedo ◽

Demián García-Violini ◽

Yerai Peña-Sanchez ◽

Josh Davidson ◽

...

Keyword(s):

Experimental Data ◽

Numerical Model ◽

Model Validation ◽

Wave Energy ◽

Test Case ◽

Data Sets ◽

Wave Energy Converters ◽

Efficient Test ◽

Numerical Wave ◽

Wave Induced

Numerical wave tanks (NWTs) provide efficient test beds for the numerical analysis at various stages during the development of wave energy converters (WECs). To ensure the acquisition of accurate, high-fidelity data sets, validation of NWTs is a crucial step. However, using experimental data as reference during model validation, exact knowledge of all system parameters is required, which may not always be available, thus making an incremental validation inevitable. The present paper documents the numerical model validation of a 1/20 scale Wavestar WEC. The validation is performed considering different test case of increasing complexity: wave-only, wave excitation force, free decay, forced oscillation, and wave-induced motion cases. The results show acceptable agreement between the numerical and experimental data so that, under the well-known modelling constraints for mechanical friction and uncertainties in the physical model properties, the developed numerical model can be declared as validated.

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Optimized Design of Structural Components Realized Through Additive Manufacturing

Volume 11: Systems, Design, and Complexity ◽

10.1115/imece2015-51336 ◽

2015 ◽

Author(s):

Stefano Baglioni ◽

Claudio Braccesi ◽

Filippo Cianetti ◽

Paolo Conti ◽

Gianluca Rossi

Keyword(s):

Additive Manufacturing ◽

Stress Field ◽

Optimization Technique ◽

Field Application ◽

Production Costs ◽

Raw Material ◽

Test Case ◽

Optimized Design ◽

Material Distribution ◽

Specific Test

Nowadays Additive Manufacturing (AM) is going through a very fast development, spreading in many different mechanical contexts. The main advantages of this technology are: production costs reduction (prototype realization time reduction, raw material consumption reduction, almost zero manpower needed...), significant reliability (compared to the standard production process) and last but not least extreme freedom in product shape design. The last characteristic makes it possible to adopt new design approach focusing on component shape and material distribution optimization; a new design paradigm must be developed to fully take advantage of these opportunities: the designer can develop new concepts with very complex shapes and sophisticated topological solution owing to opportunities yielded by AM with in mind only the week limitations given by this technology. In detail this work aims to highlight a new design strategy that consist of a combination of structural optimization tools (Topology Optimization TO) and non-contact stress field measurement technique (based on thermo-elasticity). The goal is to develop an iterative design procedures which links the design shape optimization with the experimental stress evaluation, allowing a wise material distribution in order to enhance the resistance. The idea is to accomplish an initial designing phase, letting the designer free to define a first rough design concept taking into account the information provided by the TO to exploit the material in the best way. Then, the concept must be verified in both: model numerical F.E.M. analysis and prototype experimental evaluation of the stress field. Eventually, according to the verification analysis results, the model will be modified to reach the desired requirements in terms of allowed deformation, stress resistance and fatigue life. The paper will display the optimization technique iterative process (based on Solid Isotropic Material with Penalization – SIMP – scheme) in a general way and through a practical example. As a reference, this methodology has been applied to a specific test case in order to design and optimize a new concept of a structural mechanical component of a mountain bike. The component was, first realized as a prototype in thermoplastic material and finally designed to be realized in metal for in field application.

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