Automatic Generation of Basis Component Path Coverage for Software Architecture Testing

2017 ◽  
Vol 36 (2) ◽  
pp. 386-404
Author(s):  
Lijun Lun ◽  
Shaoting Wang ◽  
Xin Chi ◽  
Hui Xu
Keyword(s):  
Software Architecture ◽  
Automatic Generation ◽  
Path Coverage

A Analysis and Research on the Methods of Object Oriented Software Testing

2013 ◽  
Vol 709 ◽  
pp. 616-619
Author(s):  
Jing Chen
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Test Data ◽  
Object Oriented ◽  
Automatic Generation ◽  
Test Case Generation ◽  
Test Case ◽  
Test Cases ◽  
Path Coverage ◽  
Parameter Values

This paper proposes a genetic algorithm-based method to generate test cases. This method provides information for test case generation using state machine diagrams. Its feature is realizing automation through fewer generated test cases. In terms of automatic generation of test data based on path coverage, the goal is to build a function that can excellently assess the generated test data and guide the genetic algorithms to find the targeting parameter values.

Test Data Generation Based on Test Path Discovery Using Intelligent Water Drop

2012 ◽  
Vol 3 (2) ◽  
pp. 56-74 ◽  
Author(s):  
Praveen Ranjan Srivastava ◽  
Amitkumar Patel ◽  
Kunal Patel ◽  
Prateek Vijaywargiya
Keyword(s):  
Test Data ◽  
Water Drop ◽  
Automatic Generation ◽  
Control Flow ◽  
Test Cases ◽  
Test Data Generation ◽  
Data Generation ◽  
Path Coverage ◽  
Automatic Test Data Generation ◽  
Generate Test Data

Automatic test data generation is required to generate test cases dynamically for a specific software program. Manual generation of test data is too tedious and a time consuming task. This paper proposes a technique using Intelligent Water Drop (IWD) for automatic generation of test data. Correctly generated test data helps in reducing the effort while testing the software. This paper discusses different algorithms based on IWD to generate test data and path coverage over Control Flow Graph. Test data is generated keeping in mind all of the programming constraints like “if,” “while,” “do while,” etc., available in the program.

Breadth First Search Based COSINE Software Code Framework Automation Algorithm

2015 ◽  
Author(s):  
Hao Ren ◽  
Wentao Mo ◽  
Guang Zhao ◽  
Dangpei Ren ◽  
Shuo Liu
Keyword(s):  
Data Structure ◽  
Software Development ◽  
Software Architecture ◽  
Automatic Generation ◽  
Software Framework ◽  
Breadth First Search ◽  
Design And Optimization ◽  
Tree Data ◽  
Tree Data Structure ◽  
Automation Technology

Using software automation technology can significantly improve the quality and productivity of software development. Based on the tree data structure, this paper proposed the Breadth First Search (BFS) based software framework automatic generation algorithm called CFAA (Code Framework Automation Algorithm). The algorithm uses tree data structure to represent scientific computing software architecture, then uses the BFS to traverse all nodes of the tree to generate code framework of software. CFAA enable programmers to focus more on computing software architecture design and optimization, and then automatically generate the skeleton code. CFAA has been applied to COSINE (Core and System Integrated Engine for design and analysis) software development process. Practice proved that CFAA can improve the efficiency of building software framework, while reducing the defect rate of software development.

The Role of Visual Distractors in the Simon Effect

2017 ◽  
Vol 64 (6) ◽  
pp. 387-397 ◽  
Author(s):  
Luisa Lugli ◽  
Stefania D’Ascenzo ◽  
Roberto Nicoletti ◽  
Carlo Umiltà
Keyword(s):  
Simon Effect ◽  
Simon Task ◽  
Automatic Generation ◽  
Spatial Code ◽  
Attentional Model ◽  
Previous Evidence ◽  
Spatial Stimulus ◽  
Attentional Resources ◽  
Code Changes

Abstract. The Simon effect lies on the automatic generation of a stimulus spatial code, which, however, is not relevant for performing the task. Results typically show faster performance when stimulus and response locations correspond, rather than when they do not. Considering reaction time distributions, two types of Simon effect have been individuated, which are thought to depend on different mechanisms: visuomotor activation versus cognitive translation of spatial codes. The present study aimed to investigate whether the presence of a distractor, which affects the allocation of attentional resources and, thus, the time needed to generate the spatial code, changes the nature of the Simon effect. In four experiments, we manipulated the presence and the characteristics of the distractor. Findings extend previous evidence regarding the distinction between visuomotor activation and cognitive translation of spatial stimulus codes in a Simon task. They are discussed with reference to the attentional model of the Simon effect.

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