scholarly journals RISK-BASED TESTING: IDENTIFYING, ASSESSING, MITIGATING & MANAGING RISKS EFFICIENTLY IN SOFTWARE TESTING

2020 ◽  
Author(s):  
Omdev Dahiya ◽  
Kamna Solanki ◽  
Amita Dhankhar
Keyword(s):  
Software Testing ◽  
Test Cases ◽  
Novel Technique ◽  
Software Product ◽  
Testing Schedule ◽  
Client Side ◽  
Bug Fixes ◽  
Source Of Information ◽  
Important Test

Most of the software organizations often strive hard while deciding the releasedates of their software product. This is because no organization wants to take riskswhere the fault is revealed in the developed product on the client-side. This will leadto expensive bug-fixes, and the image of the developer company is tarnished. On theother hand, testing beyond a particular time would lead to a loss of revenue for theorganization. The effective approach for handling the risky components will enablesoftware testers to identify more important test cases that can reveal faults associatedwith those components. After identification of those test cases, software testers work tofix fault sooner by managing the testing schedule by running such test cases earlier.Faults associated with hazardous components can also be detected sooner. In riskbased testing, the probability of a fault becoming a reality is assessed, and the damagethat this fault can cause when leading to failure is considered. This study haspresented an overall layout of risk-based testing. We have summarized the researchfindings of numerous researchers in this field. This will help the newcomers in thisfiled to provide a comprehensive source of information altogether. The futuredirection of this study will focus on proposing a novel technique for risk-based testing,considering different parameters together.

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.

scholarly journals Survey on Various Testing Techniques and Strategies for Bug Finding

2013 ◽  
Vol 11 (1) ◽  
pp. 2150-2155
Author(s):  
Mohit Kumar ◽  
Geetika Gandhi ◽  
Sushil Garg
Keyword(s):  
Software Testing ◽  
Verification And Validation ◽  
Test Cases ◽  
Validation Process ◽  
Software Product ◽  
Bug Finding ◽  
Testing Techniques ◽  
The Right ◽  
Selection Of

Software testing is verification and validation process aimed for evaluating a program and ensures that it meets the required result. The main goal of software testing is to uncover the errors in software. So the main aim of test cases is to derive set of tests that have highest probability of finding bugs. There are many approaches to software testing, but effective testing of any software product is essentially a tough process. It is nearly impossible to find all the errors in the program. The major problem in testing is what would be the strategy that we should adopt for testing. Thus, the selection of right strategy at the right time will make the software testing efficient and effective. In this paper I have described software testing techniques which are classified by purpose.

scholarly journals Using Aggloramative Clustering to Asses and Improve Software Reliability

2019 ◽  
Vol 8 (4) ◽  
pp. 10530-10535
Keyword(s):  
Software Testing ◽  
Software Reliability ◽  
Clustering Algorithms ◽  
Test Cases ◽  
Clustering Methods ◽  
Novel Technique ◽  
Data Treatment ◽  
Test Study

For the reduction of cost in software testing we propose a novel technique for testing and classifying methods based on clustering methods for classifying test cases for powerful and non-viable groups. This technique is based on data treatment obtained by pre-release of program while testing. Here we introduce 2 new clustering algorithms such as centroid and hierarchical based clustering. The test study expresses that the experiment bunching results can be distinguished viably with high review proportion and noteworthy rate exactness. The present paper tells about the presentation of clustering which move towards by comparing and investigating the factors like criteria coverage, features of construction and pre-release faults quality.

Generating test cases and procedures from use cases in dynamic software product lines

2017 ◽  
Author(s):  
Italo L. Araújo ◽  
Ismayle S. Santos ◽  
João B. Ferreira Filho ◽  
Rossana M. C. Andrade ◽  
Pedro Santos Neto
Keyword(s):  
Software Product Lines ◽  
Use Cases ◽  
Test Cases ◽  
Product Lines ◽  
Software Product ◽  
Dynamic Software

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.

scholarly journals A Prioritization Approach for Regression Test Cases Based on a Revised Genetic Algorithm

2021 ◽  
Vol 50 (3) ◽  
pp. 443-457
Author(s):  
Thamer Alrawashdeh ◽  
Fuad ElQirem ◽  
Ahmad Althunibat ◽  
Roba Alsoub
Keyword(s):  
Genetic Algorithm ◽  
Software Testing ◽  
Regression Testing ◽  
Test Cases ◽  
Average Percentage ◽  
Lower Priority ◽  
Regression Test ◽  
Predefined Criterion ◽  
Good Coverage ◽  
Selection Of

The regression testing is a software-based testing approach executed to verify that changes made to the softwaredo not affect the existing functionality of the product. On account of the constraints of time and cost, it isimpractical to re-execute all the test cases for software whenever a change occurs. In order to overcome sucha problem in the selection of regression test cases, a prioritization technique should be employed. On the basisof some predefined criterion, the prioritization techniques create an execution schedule for the test cases, sothe higher priority test cases can be performed earlier than the lower priority test cases in order to improvethe efficiency of the software testing. Many prioritization criteria for regression test cases have been proposedin software testing literature; however, most of such techniques are code-based. Keeping in view this fact, thisresearch work has proposed a prioritization approach for regression test cases generated from software specificationswhich are based on the criterion of the Average Percentage Transition Coverage (APTC) by using arevised genetic algorithm. This criterion evaluates the rate of transitions coverage by incorporating knowledgeabout the significance of transitions between activates in the form of weights. APTC has been used as a fitnessevaluation function in a genetic algorithm to measure the effectiveness of a test cases sequence. Moreover, inorder to improve the coverage percentage, the proposed approach has revised the genetic algorithm by solvingthe problem of the optimal local solution. The experimental results show that the proposed approach demonstratesa good coverage performance with less execution time as compared to the standard genetic algorithmand some other prioritization techniques.

scholarly journals Selection of Best Test Cases using Support Vector Machine for ARPT

2019 ◽  
Vol 8 (3) ◽  
pp. 4265-4271
Keyword(s):  
Support Vector Machine ◽  
Software Testing ◽  
Support Vector ◽  
Test Cases ◽  
Testing Strategy ◽  
Random Partition ◽  
Code Coverage ◽  
Time Consumption ◽  
Branch Coverage ◽  
Selection Of

Software testing is an essential activity in software industries for quality assurance; subsequently, it can be effectively removing defects before software deployment. Mostly good software testing strategy is to accomplish the fundamental testing objective while solving the trade-offs between effectiveness and efficiency testing issues. Adaptive and Random Partition software Testing (ARPT) approach was a combination of Adaptive Testing (AT) and Random Partition Approach (RPT) used to test software effectively. It has two variants they are ARPT-1 and ARPT-2. In ARPT-1, AT was used to select a certain number of test cases and then RPT was used to select a number of test cases before returning to AT. In ARPT-2, AT was used to select the first m test cases and then switch to RPT for the remaining tests. The computational complexity for random partitioning in ARPT was solved by cluster the test cases using a different clustering algorithm. The parameters of ARPT-1 and ARPT-2 needs to be estimated for different software, it leads to high computation overhead and time consumption. It was solved by Improvised BAT optimization algorithms and this approach is named as Optimized ARPT1 (OARPT1) and OARPT2. By using all test cases in OARPT will leads to high time consumption and computational overhead. In order to avoid this problem, OARPT1 with Support Vector Machine (OARPT1-SVM) and OARPT2- SVM are introduced in this paper. The SVM is used for selection of best test cases for OARPT-1 and OARPT-2 testing strategy. The SVM constructs hyper plane in a multi-dimensional space which is used to separate test cases which have high code and branch coverage and test cases which have low code and branch coverage. Thus, the SVM selects the best test cases for OARPT-1 and OARPT-2. The selected test cases are used in OARPT-1 and OARPT-2 to test software. In the experiment, three different software is used to prove the effectiveness of proposed OARPT1- SVM and OARPT2-SVM testing strategies in terms of time consumption, defect detection efficiency, branch coverage and code coverage.

Cloud-Enabled Software Testing Based on Program Understanding

2012 ◽  
pp. 54-67
Author(s):  
Chia-Chu Chiang ◽  
Shucheng Yu
Keyword(s):  
Cloud Computing ◽  
Software Testing ◽  
Software As A Service ◽  
Innovative Technology ◽  
Test Cases ◽  
Program Understanding ◽  
On Demand ◽  
Computing Technologies

Cloud computing provides an innovative technology that enables Software as a Service (SaaS) to its customers. With cloud computing technologies, a suite of program understanding tools is suggested to be deployed in a cloud to aid the generation of test cases for software testing. This cloud-enabled service allows customers to use these tools through an on-demand, flexible, and pay-per-use model. Lastly, the issues and challenges of cloud computing are presented.

Towards Automated Bypass Testing of Web Applications

2010 ◽  
pp. 212-229 ◽  
Author(s):  
J. Miller ◽  
L. Zhang ◽  
E. Ofuonye ◽  
M. Smith
Keyword(s):  
Test Data ◽  
Web Applications ◽  
Test Cases ◽  
Web Based ◽  
Is Security ◽  
Mission Critical ◽  
Client Side ◽  
Input Validation

The construction and testing of Web-based systems has become more complex and challenging with continual innovations in technology. One major concern particularly for the deployment of mission critical applications is security. In Web-based systems, the principal vulnerabilities revolve around deficient input validation. This chapter describes a partially automated mechanism, the tool InputValidator, which seeks to address this issue through bypassing client-side checking and sending test data directly to the server to test the robustness and security of the back-end software. The tool allows a user to construct, execute and evaluate a number of test cases through a form-filling exercise instead of writing bespoke test code.

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