scholarly journals A Novel Framework Design for Test Case Authoring and Auto Test Scripts Generation

2021 ◽  
Vol 12 (6) ◽  
pp. 1479-1487
Author(s):  
Srinivas Perala, Dr. Ajay Roy
Keyword(s):  
Software Testing ◽  
Embedded Software ◽  
Product Launch ◽  
Software Test ◽  
Design For Test ◽  
Test Case ◽  
Test Cases ◽  
Test Automation ◽  
Automation Test ◽  
Automate Testing

Every product has defects and identifying defects in the process of development and rectifying them before the launch of the product is very important. Embedded software testing process find the bugs in the software and report to the developer to fix issues. Sometimes to meet the product release deadlines, test engineers will not get much time to cover all test cases. That is why most software testing depends on test automation. In this paper, we focused on the area of automotive and home appliances embedded software test automation. Test automation is the only solution to improve the test phase and meet the timeline of the product launch. There are many test Automation tools like LabVIEW, test stand, and automation desk to automate testing embedded software. However, there is still manual efforts are required to use these tools. This paper deals automate those manual efforts. This Works shows how to generate test scripts from test cases to reduce the manual efforts, time, and cost.

scholarly journals Software Test Case Generation and it’s curtail using G-Genetic Algorithm

2019 ◽  
Vol 8 (2) ◽  
pp. 852-855
Keyword(s):  
Software Testing ◽  
Optimization Problem ◽  
Information Age ◽  
Software Test ◽  
Test Case ◽  
Test Cases ◽  
Show Business ◽  
Np Complete ◽  
The Mean ◽  
The Ideal

Project is a collection of similar activities that are going to be executed in certain order. Among the phases of project management testing show business crucial role. The intension of testing is not to prove the correctness; it is the process of verifying and validation. Software Testing is the most challenging job among all the peers of the industry. Exhaustive software Testing is never possible only Optimized software testing is possible. Hence Software Testing can be viewed as optimization problem as it fall under NP complete. Because of the extensive number of experiments that are required to perform adequate testing of the ideal programming application; the different strategies to decrease the test suite is required. One of the normal contemplated strategies is evacuating the repetitive experiments; the reason is insignificant number of experiments and greatest number of mistakes seclusion or revealing. In this exploration work consider is directed to address the usage and viability of G-hereditary calculation so as to decrease the quantity of experiments that don't included unmistakable incentive in the mean of test inclusion or where the experiments can't separate blunders. Hereditary calculation is used in this work to help in limiting the experiments or streamlining the experiments, where the hereditary calculation creates the primer populace arbitrarily, computes the wellness esteem utilizing inclusion measurements, and after that particular the posterity in back to back ages utilizing hereditary tasks choice, traverse and transformation. The hereditary displaying activities are explicit and dependent on the task may fluctuate to ordinary Genetic calculation. This procedure of age is rehashed until there is no adjustment in the wellness esteems for two successive ages, when there is no adjustment in the information age for two emphases so union accomplished or a minimized test case is achieved. The results of study demonstrate that, genetic algorithms can significantly reduce the size of the test cases

Framework for Reusable Test Case Generation in Software Systems Testing

2020 ◽  
pp. 212-229
Author(s):  
Kamalendu Pal
Keyword(s):  
Software Development ◽  
Software Testing ◽  
Software Test ◽  
Test Case Generation ◽  
Software Systems ◽  
Test Case ◽  
Case Based Reasoning ◽  
Test Cases ◽  
Development Teams ◽  
Functional Software

Agile methodologies have become the preferred choice for modern software development. These methods focus on iterative and incremental development, where both requirements and solutions develop through collaboration among cross-functional software development teams. The success of a software system is based on the quality result of each stage of development with proper test practice. A software test ontology should represent the required software test knowledge in the context of the software tester. Reusing test cases is an effective way to improve the testing of software. The workload of a software tester for test-case generation can be improved, previous software testing experience can be shared, and test efficiency can be increased by automating software testing. In this chapter, the authors introduce a software testing framework (STF) that uses rule-based reasoning (RBR), case-based reasoning (CBR), and ontology-based semantic similarity assessment to retrieve the test cases from the case library. Finally, experimental results are used to illustrate some of the features of the framework.

scholarly journals Test Automation Framework for Embedded Linux Testing

2021 ◽  
Vol 23 (06) ◽  
pp. 633-639
Author(s):  
Sahana K S ◽  
◽  
Maanas M D ◽  
M Govinda Raju ◽  
◽  
...  
Keyword(s):  
Software Testing ◽  
Embedded Software ◽  
Test Cases ◽  
Test Automation ◽  
Testing Environment ◽  
Entire Process ◽  
Board Support Package ◽  
Huge Challenge ◽  
Roll Out ◽  
Automation Framework

Software testing is one of the most important steps before its official roll–out to the market. Testing of embedded software is a very complex, tedious, and time–consuming process. Manual execution of the test cases can pose a huge challenge to the test engineers in terms of the time consumed to execute and compile the results of hundreds of test cases. This paper presents a solution to automate the entire process of build and install of Board Support Package (BSP) using Jenkins, along with the automation of the testing process using Linaro Automation and Validation Architecture (LAVA). The proposed design is validated in a BSP testing environment to show the ease of testing using the framework mentioned in this paper.

Framework for Reusable Test Case Generation in Software Systems Testing

2022 ◽  
pp. 1090-1108
Author(s):  
Kamalendu Pal
Keyword(s):  
Software Development ◽  
Software Testing ◽  
Software Test ◽  
Test Case Generation ◽  
Software Systems ◽  
Test Case ◽  
Case Based Reasoning ◽  
Test Cases ◽  
Development Teams ◽  
Functional Software

Agile methodologies have become the preferred choice for modern software development. These methods focus on iterative and incremental development, where both requirements and solutions develop through collaboration among cross-functional software development teams. The success of a software system is based on the quality result of each stage of development with proper test practice. A software test ontology should represent the required software test knowledge in the context of the software tester. Reusing test cases is an effective way to improve the testing of software. The workload of a software tester for test-case generation can be improved, previous software testing experience can be shared, and test efficiency can be increased by automating software testing. In this chapter, the authors introduce a software testing framework (STF) that uses rule-based reasoning (RBR), case-based reasoning (CBR), and ontology-based semantic similarity assessment to retrieve the test cases from the case library. Finally, experimental results are used to illustrate some of the features of the framework.

scholarly journals Performance of Enhanced Multiple-Searching Genetic Algorithm for Test Case Generation in Software Testing

Mathematics ◽  
2021 ◽  
Vol 9 (15) ◽  
pp. 1779
Author(s):  
Wanida Khamprapai ◽  
Cheng-Fa Tsai ◽  
Paohsi Wang ◽  
Chi-En Tsai
Keyword(s):  
Genetic Algorithm ◽  
Software Testing ◽  
Random Search ◽  
Automatic Generation ◽  
Superior Performance ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Network Systems ◽  
Routing Problem

Test case generation is an important process in software testing. However, manual generation of test cases is a time-consuming process. Automation can considerably reduce the time required to create adequate test cases for software testing. Genetic algorithms (GAs) are considered to be effective in this regard. The multiple-searching genetic algorithm (MSGA) uses a modified version of the GA to solve the multicast routing problem in network systems. MSGA can be improved to make it suitable for generating test cases. In this paper, a new algorithm called the enhanced multiple-searching genetic algorithm (EMSGA), which involves a few additional processes for selecting the best chromosomes in the GA process, is proposed. The performance of EMSGA was evaluated through comparison with seven different search-based techniques, including random search. All algorithms were implemented in EvoSuite, which is a tool for automatic generation of test cases. The experimental results showed that EMSGA increased the efficiency of testing when compared with conventional algorithms and could detect more faults. Because of its superior performance compared with that of existing algorithms, EMSGA can enable seamless automation of software testing, thereby facilitating the development of different software packages.

Research in Test Case Method in Software Testing

2013 ◽  
Vol 457-458 ◽  
pp. 1163-1166
Author(s):  
Hua Bo Xiao ◽  
Shu Li Huang
Keyword(s):  
Artificial Intelligence ◽  
Software Testing ◽  
Domain Knowledge ◽  
Predicate Calculus ◽  
Software Test ◽  
Test Case ◽  
Case Method ◽  
Designing Method

Based on existing software test case designing method, combining artificial intelligence domain knowledge and methods, we design a method of Predicate Calculus for Test case designing, using this method to provide detailed information to testers.

A Software Testing-Progress Evaluation Model Based on a Digestion Process of Test-Cases

1997 ◽  
Vol 04 (03) ◽  
pp. 229-239 ◽  
Author(s):  
Mitsuhiro Kimura ◽  
Shigeru Yamada
Keyword(s):  
Software Testing ◽  
Large Scale ◽  
Evaluation Model ◽  
Test Case ◽  
Test Cases ◽  
Software Production ◽  
Proposed Model ◽  
Software Product ◽  
Software Engineers ◽  
Case Data

It is of great importance for software engineers and managers to evaluate software testing-progress in a large-scale software production process, since tremendous software development resources must be consumed to achieve high quality and reliability of a software product. By focusing on the behavior of the digested test-case data observed in the testing process, we construct a stochastic model and derive several quantitative measures for software testing-progress evaluation. Actual data observed in the testing process are analyzed by the proposed model, and we discuss the applicability of our models.

Research on Automatic Test Case Generation Framework for Java

2014 ◽  
Vol 568-570 ◽  
pp. 1488-1496
Author(s):  
Ming Gang Xu ◽  
Yong Min Mu ◽  
Zhi Hua Zhang ◽  
Ang Liu
Keyword(s):  
Software Testing ◽  
Automatic Generation ◽  
Difficult Problem ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Labor Costs ◽  
Automatic Test ◽  
Automatic Test Case Generation ◽  
Java Program

Automatic test case generation has been a hotspot and a difficult problem in the software testing, Accurately and efficiently generate test cases can improve the efficiency of software testing. Java programs have many characteristics such as encapsulation, inheritance, polymorphism and so on, it is convenient for software design and development, but to bring automated testing some difficulties. This article on the Java program of automatic test case generation method is studied and presents a framework for automatic generation of test cases. With this framework, test case suite will be generated quickly and accurately. Experimental results show that automatic Java test case generation framework can quickly and accurately generate test cases , reduce labor costs and improve efficiency.

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