scholarly journals Combining Symbolic Execution and Model Checking for Data Flow Testing

2015 ◽  
Author(s):  
Ting Su ◽  
Zhoulai Fu ◽  
Geguang Pu ◽  
Jifeng He ◽  
Zhendong Su
Keyword(s):  
Model Checking ◽  
Data Flow ◽  
Symbolic Execution ◽  
Data Flow Testing

scholarly journals Data flow testing as model checking

2003 ◽  
Author(s):  
Hyoung Seok Hong ◽  
Sung Deok Cha ◽  
Insup Lee ◽  
O. Sokolsky ◽  
H. Ural
Keyword(s):  
Model Checking ◽  
Data Flow ◽  
Data Flow Testing

scholarly journals FuSeBMC: A White-Box Fuzzer for Finding Security Vulnerabilities in C Programs (Competition Contribution)

2021 ◽  
pp. 363-367 ◽  
Author(s):  
Kaled M. Alshmrany ◽  
Rafael S. Menezes ◽  
Mikhail R. Gadelha ◽  
Lucas C. Cordeiro
Keyword(s):  
Model Checking ◽  
Symbolic Execution ◽  
Bounded Model Checking ◽  
Test Cases ◽  
Security Vulnerabilities ◽  
C Programs ◽  
Code Coverage

AbstractWe describe and evaluate a novel white-box fuzzer for C programs named , which combines fuzzing and symbolic execution, and applies Bounded Model Checking (BMC) to find security vulnerabilities in C programs. explores and analyzes C programs (1) to find execution paths that lead to property violations and (2) to incrementally inject labels to guide the fuzzer and the BMC engine to produce test-cases for code coverage. successfully participates in Test-Comp’21 and achieves first place in the category and second place in the category.

scholarly journals Test Case Generation for Data Flow Testing using Cuckoo Search Algorithm

2019 ◽  
Vol 8 (2S11) ◽  
pp. 2953-2964
Keyword(s):  
Data Flow ◽  
Search Algorithm ◽  
Fitness Function ◽  
Cuckoo Search ◽  
Automatic Generation ◽  
Cuckoo Search Algorithm ◽  
Test Case ◽  
Stochastic Algorithm ◽  
Data Flow Testing ◽  
Work Done

Software testing consumes the major portion of the total efforts required for software development. This activity is very time consuming and labor intensive. It is very hard to do testing in optimal manner. In this paper a new approach is proposed, which uses the nature inspired stochastic algorithm called Cuckoo Search Algorithm (CSA) for the automatic generation of test data for data flow testing. This approach considers all def-use as test adequacy criteria. For assistance to CSA in the state space a new fitness function is also proposed by using the concept of dominator tree and branch distance in a CFG. To validate the proposed approach experiments are carried out on 10 benchmarked programs and findings are contrasted with earlier work done in this domain. Further in order to prove that proposed approach performs better than the above mentioned approaches a statistical difference test (T-test) is also performed.

Fault detection effectiveness of mutation and data flow testing

1995 ◽  
Vol 4 (1) ◽  
pp. 69-83 ◽  
Author(s):  
W. Eric Wong ◽  
Aditya P. Mathur
Keyword(s):  
Fault Detection ◽  
Data Flow ◽  
Data Flow Testing
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