Search-based test case selection of cyber-physical system product lines for simulation-based validation

2016 ◽  
Author(s):  
Aitor Arrieta ◽  
Shuai Wang ◽  
Goiuria Sagardui ◽  
Leire Etxeberria
Keyword(s):  
Physical System ◽  
Cyber Physical System ◽  
Test Case ◽  
Product Lines ◽  
Test Case Selection ◽  
Case Selection ◽  
Simulation Based ◽  
System Product ◽  
Selection Of

Test Case Selection: A Systematic Literature Review

2014 ◽  
Vol 24 (04) ◽  
pp. 653-676 ◽  
Author(s):  
Everton Note Narciso ◽  
Márcio Eduardo Delamaro ◽  
Fátima De Lourdes Dos Santos Nunes
Keyword(s):  
Resource Constraints ◽  
Test Case ◽  
Test Cases ◽  
Random Testing ◽  
Test Case Selection ◽  
Test Strategies ◽  
Case Selection ◽  
Definition Of ◽  
Selection Of ◽  
Leading Journals

Time and resource constraints should be taken into account in software testing activities, and thus optimizing the test suite is fundamental in the development process. In this context, the test case selection aims to eliminate redundant or unnecessary test data, which is crucial for the definition of test strategies. This paper presents a systematic review on the test case selection conducted through a selection of 449 articles published in leading journals and conferences in Computer Science. We addressed the state-of-art by collecting and comparing existing evidence on the methods used in the different software domains and the methods used to evaluate the test case selection. Our study identified 32 papers that met the research objectives, which featured 18 different selection methods and were evaluated through 71 case studies. The most commonly reported methods are adaptive random testing, genetic algorithms and greedy algorithm. Most approaches rely on heuristics, such as diversity of test cases and code or model coverage. This paper also discusses the key concepts and approaches, areas of application and evaluation metrics inherent to the methods of test case selection available in the literature.

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 AVISAR – An Automated Framework for Test Case Selection & Prioritization using GA for OOS.

2020 ◽  
Vol 9 (4) ◽  
pp. 1556-1563
Keyword(s):  
Large Scale ◽  
Object Oriented ◽  
Test Case ◽  
Test Cases ◽  
Unified Approach ◽  
Test Case Selection ◽  
Case Selection ◽  
Object Oriented Systems ◽  
Efficient Selection ◽  
Selection Of

In this paper we have presented an automated unified approach called AVISAR for the testing of the Object-oriented Systems (OOS) by Test Case Prioritization (TCP) & their selection using Genetic Algorithm for the OOS. The testing of OOS has become a more challenging task as nowadays it has been widely accepted as a paradigm for large-scale system designing. In this research paper we have also studied the Genetic algorithms in relation to their applications for providing solutions to the various aspects of the OO Testing. As a result after implementing the tool AVISAR using GA’s it has proven to be useful in providing effective solutions to resolve the issues related to the OO Testing domain. Thus it can be used for reducing the efforts of the users for testing by efficient selection of effective test cases

Pareto efficient multi-objective black-box test case selection for simulation-based testing

2019 ◽  
Vol 114 ◽  
pp. 137-154 ◽  
Author(s):  
Aitor Arrieta ◽  
Shuai Wang ◽  
Urtzi Markiegi ◽  
Ainhoa Arruabarrena ◽  
Leire Etxeberria ◽  
...  
Keyword(s):  
Black Box ◽  
Test Case ◽  
Test Case Selection ◽  
Multi Objective ◽  
Case Selection ◽  
Simulation Based ◽  
Pareto Efficient ◽  
Selection For

Test Case Selection Using Feature Extraction and Clustering

2018 ◽  
Vol 8 (2) ◽  
pp. 18-31 ◽  
Author(s):  
Angelin Gladston ◽  
H. Khanna Nehemiah ◽  
P. Narayanasamy ◽  
A. Kannan
Keyword(s):  
Feature Extraction ◽  
Test Case ◽  
Test Cases ◽  
Test Case Selection ◽  
Case Selection ◽  
Function Call ◽  
Clustering Approach ◽  
Execution Pattern ◽  
Profile Approach ◽  
Selection Of

This article explains the selection of important parameters from an execution pattern which brings out the details of the application of test cases. Hence, execution profiles are captured and a new execution profile-based clustering approach is chosen for test case selection, which uses three new features. These are Function frequency, Branches taken and Block percentage. The test cases are clustered using the extracted features. The experiments show that the proposed FBB selects smaller size of more relevant test cases which are more fault revealing compared to the existing Function Call Profile approach.

Sign in / Sign up

Export Citation Format

Share Document