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Essay On Test Data Generation

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2. Related works
Some of the recent work related to the automated test data generation is listed below:
Search-based approaches have been extensively applied to solve the problem of software test-data generation. Yet, test-data generation for object-oriented programming (OOP) is challenging due to the features of OOP, e.g., abstraction, encapsulation, and visibility that prevent direct access to some parts of the source code. To address this problem Abdelilah Sakti et al. [26] have presented an automated search-based software test-data generation approach that achieves high code coverage for unit-class testing. The test-data generation problem for unit-class testing to generate relevant sequences of method calls were described at first. …show more content…

A set of search heuristics targeted to OCL constraints to guide test data generation and automate MBT in industrial applications was proposed. These heuristics for three search algorithms: Genetic Algorithm, (1+1) Evolutionary Algorithm, and Alternating Variable Method were evaluated. Empirically evaluated the heuristics using complex artificial problems, followed by empirical analyses of the feasibility of our approach on one industrial system in the context of robustness testing.
A feature model is a compact representation of the products of a software product line. The automated extraction of information from feature models is a thriving topic involving numerous analysis operations, techniques and tools. Performance evaluations in this domain mainly rely on the use of random feature models. However, these only provide a rough idea of the behaviour of the tools with average problems and are not sufficient to reveal their real strengths and weaknesses.
Sergio Segura et al. [28] have proposed to model the problem of finding computationally hard feature models as an optimization problem and solved it using a novel evolutionary algorithm for optimized feature models (ETHOM). Tool and an analysis operation were given in ETHOM generated input models of a predefined size maximizing aspects such as the execution time or the memory consumption of the tool when performing the

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