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

2022 ◽  
pp. 836-860
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.

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.

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.

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 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

Direct-Indirect Link Matrix

2020 ◽  
Vol 11 (4) ◽  
pp. 56-69
Author(s):  
Saurabh Rawat ◽  
Anushree Sah ◽  
Ankur Dumka
Keyword(s):  
Software Development ◽  
Software Testing ◽  
Source Code ◽  
Black Box ◽  
Test Cases ◽  
Unit Testing ◽  
Integration Testing ◽  
Testing Technique ◽  
Testing Unit ◽  
Black Box Testing

Testing of software remains a fundamentally significant way to check that software behaves as required. Component-based software testing (CBST) is a crucial activity of component-based software development (CBSD) and is based on two crucial proportions: components testing by developers with the source code (e.g., system testing, integration testing, unit testing, etc.) and components testing by end users without source code (black box testing). This work proposes a black box testing technique that calculates the total number of interactions made by component-based software. This technique is helpful to identify the number of test cases for those components where availability of source code is questionable. On the basis of interaction among components, the authors draw a component-link graph and a direct-indirect-link matrix, which helps to calculate the number of interactions in component-based software.

Analysis of VDM++ in Regression Test Suite

2015 ◽  
pp. 382-417
Author(s):  
Zahid Hussain Qaisar ◽  
Farooq Ahmad
Keyword(s):  
Software Development ◽  
Software Testing ◽  
Maintenance Phase ◽  
Vital Role ◽  
Regression Testing ◽  
Test Suite ◽  
Test Cases ◽  
To Come ◽  
The Impact ◽  
Development Methods

Regression testing is important activity during the maintenance phase. An important work during maintenance of the software is to find impact of change. One of the essential attributes of Software is change i.e. quality software is more vulnerable to change and provide facilitation and ease for developer to do required changes. Modification plays vital role in the software development so it is highly important to find the impact of that modification or to identify the change in the software. In software testing that issue gets more attention because after change we have to identify impact of change and have to keenly observe what has happened or what will happen after that particular change that we have made or going to make in software. After change software testing team has to modify its testing strategy and have to come across with new test cases to efficiently perform the testing activity during the software development Regression testing is performed when the software is already tested and now some change is made to it. Important thing is to adjust those tests which were generated in the previous testing processes of the software. This study will present an approach by analyzing VDM (Vienna Development Methods) to find impact of change which will describe that how we can find the change and can analyze the change in the software i.e. impact of change that has been made in software. This approach will fulfill the purpose of classifying the test cases from original test suite into three classes obsolete, re-testable, and reusable test cases. This technique will not only classify the original test cases but will also generate new test cases required for the purpose of regression testing.

scholarly journals Introduction to Lean Canvas Transformation Models and Metrics in Software Testing

2016 ◽  
Vol 19 (1) ◽  
pp. 30-36 ◽  
Author(s):  
Padmaraj Nidagundi ◽  
Leonids Novickis
Keyword(s):  
Software Development ◽  
Software Testing ◽  
Resource Planning ◽  
Software Test ◽  
Acceptance Testing ◽  
Test Plan ◽  
Transformation Models ◽  
Development Methodology ◽  
Lean Transformation ◽  
Software Development Methodologies

Abstract Software plays a key role nowadays in all fields, from simple up to cutting-edge technologies and most of technology devices now work on software. Software development verification and validation have become very important to produce the high quality software according to business stakeholder requirements. Different software development methodologies have given a new dimension for software testing. In traditional waterfall software development software testing has approached the end point and begins with resource planning, a test plan is designed and test criteria are defined for acceptance testing. In this process most of test plan is well documented and it leads towards the time-consuming processes. For the modern software development methodology such as agile where long test processes and documentations are not followed strictly due to small iteration of software development and testing, lean canvas transformation models can be a solution. This paper provides a new dimension to find out the possibilities of adopting the lean transformation models and metrics in the software test plan to simplify the test process for further use of these test metrics on canvas.

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 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.

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