scholarly journals Design and Implementation of Human Space-based Automated Test Cases based on Script

2018 ◽  
Author(s):  
Feng Yang
2020 ◽  
Vol 8 (6) ◽  
pp. 4466-4473

Test data generation is the task of constructing test cases for predicting the acceptability of novel or updated software. Test data could be the original test suite taken from previous run or imitation data generated afresh specifically for this purpose. The simplest way of generating test data is done randomly but such test cases may not be competent enough in detecting all defects and bugs. In contrast, test cases can also be generated automatically and this has a number of advantages over the conventional manual method. Genetic Algorithms, one of the automation techniques, are iterative algorithms and apply basic operations repeatedly in greed for optimal solutions or in this case, test data. By finding out the most error-prone path using such test cases one can reduce the software development cost and improve the testing efficiency. During the evolution process such algorithms pass on the better traits to the next generations and when applied to generations of software test data they produce test cases that are closer to optimal solutions. Most of the automated test data generators developed so far work well only for continuous functions. In this study, we have used Genetic Algorithms to develop a tool and named it TG-GA (Test Data Generation using Genetic Algorithms) that searches for test data in a discontinuous space. The goal of the work is to analyze the effectiveness of Genetic Algorithms in automated test data generation and to compare its performance over random sampling particularly for discontinuous spaces.


2018 ◽  
Vol 21 (1) ◽  
Author(s):  
Constanza Pérez ◽  
Beatriz Marín

[Context] The growing demand for high-quality software has caused the industry to incorporate processes to enable them to comply with these standards, but increasing the cost of development. A strategy to reduce this cost is to incorporate quality evaluations from early stages of software development. A technique that facilitates this evaluation is the model-based testing, which allows to generate test cases at early phases using as input the conceptual models of the system. [Objective] In this paper, we introduce TCGen, a tool that enables the automatic generation of abstract test cases starting from UML conceptual models. [Method] The design and implementation of TCGen, a technique that applies different testing criteria to class diagrams and state transition diagrams to generates test cases, is presented as a model-based testing approach. To do that, TCGen uses UML models, which are widely used at industry and a set of algorithms that recognize the concepts in the models in order to generate abstract test cases. [Results] An exploratory experimental evaluation has been performed to compare the TCGen tool with traditional testing. [Conclusions] Even though the exploratory evaluation shows promising results, it is necessary to perform more empirical evaluations in order to generalize the results. Abstract (in Spanish): [Contexto] La creciente demanda de software de alta calidad ha provocado que la industria incorpore procesos para permitirles cumplir con estos estándares, pero aumentando el costo del desarrollo. Una estrategia para reducir este costo es incorporar evaluaciones de calidad desde las primeras etapas del desarrollo del software. Una técnica que facilita esta evaluación es la prueba basada en modelos, que permite generar casos de prueba en fases tempranas utilizando como entrada los modelos conceptuales del sistema. [Objetivo] En este artículo, presentamos TCGen, una herramienta que permite la generación automática de casos de pruebas abstractas a partir de modelos conceptuales UML. [Método] El diseño e implementación de TCGen, una técnica que aplica diferentes criterios de prueba a los diagramas de clases y diagramas de transición de estados para generar casos de prueba, se presenta como un enfoque de prueba basado en modelos. Para hacer eso, TCGen utiliza modelos UML, que son ampliamente utilizados en la industria y un conjunto de algoritmos que reconocen los conceptos en los modelos para generar casos de prueba abstractos. [Resultados] Se realizó una evaluación experimental exploratoria para comparar la herramienta TCGen con las pruebas tradicionales. [Conclusiones] Aunque la evaluación exploratoria muestra resultados prometedores, es necesario realizar más evaluaciones empíricas para generalizar los resultados.  


2021 ◽  
Vol 23 (06) ◽  
pp. 746-755
Author(s):  
Shridhar Prabhu ◽  
◽  
Manoj Naik ◽  
Firdosh A D ◽  
Sohan S A ◽  
...  

Continuous Integration (CI) is a practice in the software program development process where software program builders combine code into a shared repository frequently, more than one instance throughout the day. Jenkins is a continuous integration tool which assists developer and testers by using automating the entire test, on the way to reduce their work with the aid of tracking the development at each and every stage in software development, each integration push is then tested by means of automated test cases, and an easy way to make CI quicker and accelerate. CI procedure is to automate the testing of a recent build. In this paper, a real scenario is taken into consideration, how the software program trying out is performed in corporate sectors and how Jenkins can save developers/testers important valuable hours by automating the whole software development system.


Author(s):  
Peng Xie ◽  
Li Du ◽  
Bing Zhou ◽  
Yongyan Yu ◽  
Haixia Hu ◽  
...  

Author(s):  
Pranali Mahadik ◽  
Debnath Bhattacharyya ◽  
Hye-jin Kim
Keyword(s):  

2014 ◽  
Vol 654 ◽  
pp. 378-381
Author(s):  
Yu Lin Liu ◽  
Yan Wang ◽  
Jian Tao Zhou

In the traditional software testing, a large collection of test cases of the tested system automatically generated , in the process of actual execution, all of the test cases are executed is not possible. Normally, we test a certain function of the tested system, so choosing the test cases about a certain function is very important. This paper focuses on solving the problem of choosing test cases about a certain function of the tested system based on CPN model, the method which is based on purpose is used in this process. In the process of test cases selection, there are a whole lot of repeated calculation and operation, this characteristic just can make it combined with the parallel advantage of cloud computing. In summary, this dissertation focus on the test cases selection problem, using MapReduce programming on Hadoop platform, a test case selection tool is designed to improve the efficiency and service capabilities of test selection, the result of the experiment is consistent with the expected result.


Sign in / Sign up

Export Citation Format

Share Document