Finding Errors in Programs for Processing Graphic Images using the Fuzzing Method

2021 ◽  
pp. 4-23
Author(s):  
G.S. Baydin ◽  
M.V. Khizova
Keyword(s):  
Bayesian Networks ◽  
Software Testing ◽  
Test Data ◽  
Simulation Environment ◽  
Structural Components ◽  
Testing Methods ◽  
Process Step ◽  
Executable Code ◽  
Graphic Images ◽  
Graphics Processing

Increasing number of software for automated graphics processing requires effective testing methods. One of these methods is fuzzing, for which it is necessary to determine the most effective algorithms for creating test data in order to increase the number of errors found and minimize hardware resources. The comparison of algorithms for creating test data for finding errors in the executable code of programs designed for processing graphic images is the result of the performed research. Using Bayesian networks to describe fuzzing allows determining the relationships between structural components during testing. Based on the results of the comparison of fuzzing algorithms for creating test data, the most effective algorithms for finding errors in the executable code of programs for processing graphic images have been identified. The performance of the proposed algorithms was tested on a number of existing vulnerabilities classified as CVE (Common Vulnerabilities and Exposures). The processing of the results of experiments on the creation of test data was carried out using the simulation environment, allowing analyzing the testing process step by step. The obtained research results, algorithms for creating test data for finding errors can be used at various stages of software testing

scholarly journals Comprehensive study of software testing: Categories, levels, techniques, and types

2020 ◽  
Author(s):  
Mubarak Albarka Umar
Keyword(s):  
Software Testing ◽  
Software Quality ◽  
Testing Methods ◽  
Development Lifecycle ◽  
Software Development Lifecycle ◽  
Pros And Cons ◽  
Testing Techniques ◽  
Combination Of Methods ◽  
The Right ◽  
Comprehensive Study

<p><i>Software Testing is the process of evaluating a software program to ensure that it performs its intended purpose. Software testing verifies the safety, reliability, and correct working of software. The growing need for quality software makes software testing a crucial stage in Software Development Lifecycle. There are many methods of testing software, however, the choice of method to test a given software remains a major problem in software testing. Although, it is often impossible to find all errors in software, employing the right combination of methods will make software testing efficient and successful. Knowing these software testing methods is the key to making the right selection. This paper presents a comprehensive study of software testing methods. An explanation of Testing Categories was presented first, followed by Testing Levels (and their comparison), then Testing Techniques (and their comparison). For each Testing Levels and Testing Techniques, examples of some testing types and their pros and cons were given with a brief explanation of some of the important testing types. Furthermore, a clear and distinguishable explanation of two confused and contradictory terms (Verification and Validation) and how they relate to Software Quality was provided.</i></p>

scholarly journals Research on the Computer Software Testing Method Based on Multiple Platforms

2020 ◽  
Vol 2 (3) ◽  
Author(s):  
Yongfang Sun ◽  
Jianjun Li
Keyword(s):  
Software Development ◽  
Software Testing ◽  
Computer Software ◽  
Test Accuracy ◽  
Testing Methods ◽  
Modern Life ◽  
Testing Method ◽  
Software Companies ◽  
And Control

Informationization plays an important role in modern life and production. And various software is one of the bases for it. Before it goes into service, software needs to go through many steps, including software development, design, etc. In software development, test is the key to identify and control bugs and errors in the software. Therefore, software companies often test the software to ensure that it is qualified. In recent years, more attention has been paid to a multi-platform computer software testing method, which can make up for defects in traditional testing methods to improve test accuracy. Firstly, this paper illustrates the connotation and features of software testing. Secondly, common software testing platforms and their requirements are analyzed. Finally, this paper proposes software testing method based on multiple platforms.

Concolic Test Generation and the Cloud

2015 ◽  
pp. 302-322
Author(s):  
Nikolai Kosmatov
Keyword(s):  
Software Testing ◽  
Test Generation ◽  
Symbolic Execution ◽  
Major Obstacle ◽  
Testing Methods ◽  
C Programs ◽  
Security Issues ◽  
Efficient Alternative ◽  
Cloud Environments ◽  
Testing Techniques

Software testing in the cloud can reduce the need for hardware and software resources and offer a flexible and efficient alternative to the traditional software testing process. A major obstacle to the wider use of testing in the cloud is related to security issues. This chapter focuses on test generation techniques that combine concrete and symbolic execution of the program under test. Their deployment in the cloud leads to complex technical and security issues that do not occur for other testing methods. This chapter describes recent online deployment of such a technique implemented by the PathCrawler test generation tool for C programs, where the author faced, studied, and solved many of these issues. Mixed concrete/symbolic testing techniques not only constitute a challenging target for deployment in the cloud, but they also provide a promising way to improve the reliability of cloud environments. The author argues that these techniques can be efficiently used to help to create trustworthy cloud environments.

AUTOMATIC PRODUCTION OF TEST DATA WITH A MULTIPLE BATCH-OPTIMISTIC METHOD

2009 ◽  
Vol 18 (01) ◽  
pp. 61-80 ◽  
Author(s):  
ANASTASIS A. SOFOKLEOUS ◽  
ANDREAS S. ANDREOU
Keyword(s):  
Genetic Algorithms ◽  
Software Testing ◽  
Test Data ◽  
Automatic Testing ◽  
Test Data Generation ◽  
Data Generation ◽  
Generation System ◽  
Automatic Production ◽  
Coverage Criterion ◽  
Testing Coverage

Recent research on software testing focuses on integrating techniques, such as computational intelligence, with special purpose software tools so as to minimize human effort, reduce costs and automate the testing process. This work proposes a complete software testing framework that utilizes a series of specially designed genetic algorithms to generate automatically test data with reference to the edge/condition testing coverage criterion. The framework utilizes a program analyzer, which examines the program's source code and builds dynamically program models for automatic testing, and a test data generation system that utilizes genetic algorithms to search the input space and determine a near to optimum set of test cases with respect to the testing coverage criterion. The performance of the framework is evaluated on a pool of programs consisting of both standard and random-generated programs. Finally, the proposed test data generation system is compared against other similar approaches and the results are discussed.

Research about the Testing Methods of Varistor Tester

2014 ◽  
Vol 986-987 ◽  
pp. 1545-1548
Author(s):  
Fu Quan Wang ◽  
Jin Huang ◽  
Kang Gao ◽  
Zhuang Ouyang ◽  
Chao Sheng Liang
Keyword(s):  
Leakage Current ◽  
Test Data ◽  
Testing Methods ◽  
Voltage Ratio ◽  
Current Voltage

We had described and discussed the testing methods of varistor tester about DC reference current, varistor voltage, leakage current, voltage ratio, and provided the corresponding test data,which has proved that the methods are feasible.

TEST DATA GENERATION FOR SOFTWARE TESTING BASED ON QUANTUM-INSPIRED GENETIC ALGORITHM

2013 ◽  
Vol 12 (01) ◽  
pp. 1350004 ◽  
Author(s):  
CHENGYING MAO ◽  
XINXIN YU
Keyword(s):  
Genetic Algorithm ◽  
Software Testing ◽  
Test Data ◽  
Optimal Solution ◽  
Search Space ◽  
Structural Testing ◽  
Test Data Generation ◽  
Data Generation ◽  
Quantum Bit

The quality of test data has an important impact on the effect of software testing, so test data generation has always been a key task for finding the potential faults in program code. In structural testing, the primary goal is to cover some kinds of structure elements with some specific inputs. Search-based test data generation provides a rational way to handle this difficult problem. In the past, some well-known meta-heuristic search algorithms have been successfully utilized to solve this issue. In this paper, we introduce a variant of genetic algorithm (GA), called quantum-inspired genetic algorithm (QIGA), to generate the test data with stronger coverage ability. In this new algorithm, the traditional binary bit is replaced by a quantum bit (Q-bit) to enlarge the search space so as to avoid falling into local optimal solution. On the other hand, some other strategies such as quantum rotation gate and catastrophe operation are also used to improve algorithm efficiency and quality of test data. In addition, experimental analysis on eight real-world programs is performed to validate the effectiveness of our method. The results show that QIGA-based method can generate test data with higher coverage in much smaller convergence generations than GA-based method. More importantly, our proposed method is more robust for algorithm parameter change.

scholarly journals Development of Combined Manufacturing Technologies for High-Strength Structural Components

2010 ◽  
Vol 137 ◽  
pp. 219-246 ◽  
Author(s):  
Berend Denkena ◽  
Bernd Breidenstein ◽  
Luis de Leon ◽  
Jan Dege
Keyword(s):  
Material Properties ◽  
High Strength ◽  
Tool Geometry ◽  
Structural Components ◽  
Deep Rolling ◽  
Process Step ◽  
Single Process ◽  
Local Modification ◽  
Manufacturing Technologies ◽  
Finishing Processes

Novel manufacturing technologies for high-strength structural components of aluminium allow a local modification of material properties to respond to operational demands. Machining and finishing processes for changing material properties like deep rolling or rubbing are to be combined to a single process step. The intention is the controlled adjustment of the component’s properties by the modification of its subsurface. For that purpose the essential understanding of the interaction mechanisms of the basic processes turning, deep rolling and rubbing is necessary. Influences of the tool geometry as well as of the process parameters on the material properties are investigated. The results will be extended by parameter studies within numerical simulations. Thereafter, combinations of the basic processes in process sequences are analyzed to their ability to modify the subsurface properties. In consideration of these results, a prototypic combined turn-rolling tool is developed

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