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.

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 An Enhanced Multiview Test Case Generation Technique for Object-oriented Software using Class and Activity Diagrams

2020 ◽  
Vol 9 (4) ◽  
pp. 186-195
Keyword(s):  
Software Development ◽  
Software Testing ◽  
Unified Modeling Language ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Software Faults ◽  
Single View ◽  
Effective Product ◽  
Uml Models

Software testing is one of the vital steps in software development life cycle. Test case generation is the first process in software testing which takes a lot of time, cost and effort to build an effective product from the start. Automatic test case generation is the best way to address this issue and model-based test case generation approach would be suitable for this automation process. One way to generate test cases automatically is by generating test cases from Unified Modeling Language (UML) models. The challenge with the existing test case generation techniques using UML models is that they provide a single view, meaning that the techniques capture a single aspect of the system, such as structural or behavioral but not both. In this paper, we have successfully developed a technique that automatically generates test cases which capture both structural and behavioral views of the system. These test cases can help to discover software faults early in the software development cycle. Finally, we conducted an experiment by comparing our technique with a manual process. The results show that the proposed technique can produce same test cases as manually writing test cases of the same system model but this technique saves a lot of time, effort and cost as well.

scholarly journals Automatic Generation and Optimization of Test case using Hybrid Cuckoo Search and Bee Colony Algorithm

2020 ◽  
Vol 30 (1) ◽  
pp. 59-72
Author(s):  
P Lakshminarayana ◽  
T V SureshKumar
Keyword(s):  
Software Development ◽  
Software Testing ◽  
Test Data ◽  
Cuckoo Search ◽  
Optimization Method ◽  
Automatic Generation ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Bee Colony

AbstractSoftware testing is a very important technique to design the faultless software and takes approximately 60% of resources for the software development. It is the process of executing a program or application to detect the software bugs. In software development life cycle, the testing phase takes around 60% of cost and time. Test case generation is a method to identify the test data and satisfy the software testing criteria. Test case generation is a vital concept used in software testing, that can be derived from the user requirements specification. An automatic test case technique determines automatically where the test cases or test data generates utilizing search based optimization method. In this paper, Cuckoo Search and Bee Colony Algorithm (CSBCA) method is used for optimization of test cases and generation of path convergence within minimal execution time. The performance of the proposed CSBCA was compared with the performance of existing methods such as Particle Swarm Optimization (PSO), Cuckoo Search (CS), Bee Colony Algorithm (BCA), and Firefly Algorithm (FA).

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 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.

scholarly journals TEST CASE PRIORTIZATION USING GENETIC ALGORITHM

2014 ◽  
pp. 151-154
Author(s):  
RUCHIKA MALHOTRA ◽  
ABHISHEK BHARADWAJ
Keyword(s):  
Genetic Algorithm ◽  
Software Development ◽  
Software Testing ◽  
Major Part ◽  
Test Case ◽  
Test Cases ◽  
Development Lifecycle ◽  
Software Development Lifecycle ◽  
The One

Software is built by human so it cannot be perfect. So in order to make sure that developed software does not do any unintended thing we have to test every software before launching it in the operational world. Software testing is the major part of software development lifecycle. Testing involves identifying the test cases which can find the errors in the program. Exhaustive testing is not a good idea to follow. It is very difficult and time consuming to perform. In this paper a technique has been proposed to do prioritize test cases according to their capability of finding errors. One which is more likely to find the errors has been assigned a higher priority and the one which is less likely to find the errors in the program has been assigned low priority. It is recommended to execute the test cases according their priority to find the errors.

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

Use of Qualitative Research to Generate a Function for Finding the Unit Cost of Software Test Cases

2020 ◽  
Vol 31 (2) ◽  
pp. 42-63
Author(s):  
Mark L. Gillenson ◽  
Thomas F. Stafford ◽  
Xihui “Paul” Zhang ◽  
Yao Shi
Keyword(s):  
Software Development ◽  
Software Testing ◽  
Unit Cost ◽  
Software Test ◽  
Test Cases ◽  
Subject Matter Experts ◽  
Case Research ◽  
Qualitative Interaction ◽  
Important Field ◽  
The Cost

In this article, we demonstrate a novel use of case research to generate an empirical function through qualitative generalization. This innovative technique applies interpretive case analysis to the problem of defining and generalizing an empirical cost function for test cases through qualitative interaction with an industry cohort of subject matter experts involved in software testing at leading technology companies. While the technique is fully generalizable, this article demonstrates this technique with an example taken from the important field of software testing. The huge amount of software development conducted in today's world makes taking its cost into account imperative. While software testing is a critical aspect of the software development process, little attention has been paid to the cost of testing code, and specifically to the cost of test cases, in comparison to the cost of developing code. Our research fills the gap by providing a function for estimating the cost of test cases.

scholarly journals A Stochastic Method for Test Case Selection in Software Testing

2020 ◽  
Vol 8 (4S5) ◽  
pp. 265-271
Keyword(s):  
Software Development ◽  
Software Testing ◽  
Test Case ◽  
Test Cases ◽  
Nsga Ii ◽  
Code Coverage ◽  
Test Case Selection ◽  
Redundant Data ◽  
Case Selection ◽  
Selection Of

The quality of the software is a very important aspect in the development of software application. In order to make sure there is the software of good quality, testing is a critical activity of software development. Thus, software testing is the activity which focuses on the computation of an attribute or the ability of either a system or program that decides if user requirements are met. There is a proper strategy for the design of software for which testing has to be adopted. The techniques of test case selection attempt at reduction of the test cases that need to be executed at the same time satisfying the needs of testing that has been denoted by the test criteria. In the time of software testing, and the resource will be the primary constraints at the time of testing since this has been a highly neglected phase in the Software Development Life Cycle (SDLC). The optimizing of a test suite is very critical for the reduction of the testing phase and also the selection of the test cases that eliminate unwanted or redundant data. All work in literature will make use of techniques of single objective optimization that does not have to be efficient as the code coverage will play an important role at the time of selection of test case. As the test case choice is Non-Deterministic, the work also proposes a novel and multi-objective algorithm like the Non-Dominated Sorting Genetic Algorithm II (NSGA II) and the Stochastic Diffusion Search (SDS) algorithm that makes use of the cost of execution and code coverage as its objective function. The results prove a faster level of convergence of the algorithm with better coverage of code in comparison to the NSGA II.

scholarly journals Smart Test Case Quantifier Based on Mc/Dc Coverage Criterion with Uml Sequence Diagram

2020 ◽  
Vol 9 (1) ◽  
pp. 1266-1278
Keyword(s):  
Software Testing ◽  
Initial Phase ◽  
Black Box ◽  
Sequence Diagram ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Maximum Coverage ◽  
Coverage Criterion ◽  
White Box Testing

Software testing is an inevitable phase in the Software Development Life Cycle (SDLC). It plays a vital role in ensuring the quality of the product. Testing can be performed on requirement, design and code. Traditional test case generation approaches majorly focuses on designing and implementation models, as a huge percentage of errors in the software are caused due to the lack of understanding in the early phases. So, it’s advisory to follow testing in the initial phase in SDLC as most of the errors/faults can be eliminated and can be prevented without disseminating to the next phase. So, testing must not be secluded to a single phase alone in SDLC. In software testing, test case generation is the fundamental and challenging part. The major purpose to design test case is to create set of tests that are valuable in validation. Due to the increase in software size, it’s not quite advisable to have the choice as manual testing to test the code as its error prone, complex and time consuming. Automation of testing would help the tester to test effectively and timely. Applications of new techniques improve the test process and cut down the tester’s effort. The proposed work presents a sandwich of black box and white box testing. Design-based testing, a black box approach is implemented, that aids in fixing the errors at initial phase. Unified Modeling Language (UML) Use case diagram, Activity diagram and Sequence Diagram are considered for designing. The code-based generation of test cases, is a white box testing approach, test coverage criteria Modified Condition/Decision Condition (MC/DC) has been used to ensure the maximum coverage of the code during testing phase for generating the test cases. The objective of this paper is to automate the generation of minimal number of test cases required to test a system with maximum coverage by removing the redundant test cases using MC/DC criterion. This present an idea to the beginners of the testing about minimal test cases they necessitate for testing their system.

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