Results 41 to 50 of about 337 (131)

ColorGo: Directed Concolic Execution

CoRR
Directed fuzzing is a critical technique in cybersecurity, targeting specific sections of a program. This approach is essential in various security-related domains such as crash reproduction, patch testing, and vulnerability detection. Despite its importance, current directed fuzzing methods exhibit a trade-off between efficiency and effectiveness. For
Jia Li, Jiacheng Shen, Yuxin Su 0001, Michael R. Lyu   +3 more
openaire   +2 more sources

Automatic Testing of Program Slicers

Scientific Programming, Volume 2019, Issue 1, 2019., 2019
Program slicing is a technique to extract the part of a program (the slice) that influences or is influenced by a set of variables at a given point (the slicing criterion). Computing minimal slices is undecidable in the general case, and obtaining the minimal slice of a given program is normally computationally prohibitive even for very small programs.
Sergio Pérez, Josep Silva, Salvador Tamarit, Michele Risi   +3 more
wiley   +1 more source

Concolic Testing in CLP [PDF]

, 2020
[EN] Concolic testing is a popular software verification technique based on a combination of concrete and symbolic execution. Its main focus is finding bugs and generating test cases with the aim of maximizing code coverage.
Payet, Etienne, Vidal, Germán, Mesnard, Fred, Mesnard, Frédéric   +3 more
core   +1 more source

USING CONCOLIC EXECUTION TO IDENTIFY IA32 PROGRAM ERRORS [PDF]

, 2020
In Computer Science education, one of the most important tasks is to provide students with feedback that can help them discover errors in their assignment code. Traditionally, this check is achieved by executing a series of pre-defined test cases.
Zhang, Carl
core   +1 more source

Discover deeper bugs with dynamic symbolic execution and coverage‐based fuzz testing

IET Software, Volume 12, Issue 6, Page 507-519, December 2018., 2018
Coverage‐based fuzz testing and dynamic symbolic execution are both popular program testing techniques. However, on their own, both techniques suffer from scalability problems when considering the complexity of modern software. Hybrid testing methods attempt to mitigate these problems by leveraging dynamic symbolic execution to assist fuzz testing ...
Bin Zhang, Chao Feng, Adrian Herrera, Vitaly Chipounov, George Candea, Chaojing Tang   +5 more
wiley   +1 more source

The progress, challenges, and perspectives of directed greybox fuzzing

Software Testing, Verification and Reliability, Volume 34, Issue 2, March 2024.
Based on the investigation of 42 state‐of‐the‐art fuzzers that are closely related to directed greybox fuzzing (DGF), we conduct the first in‐depth study to summarize the empirical evidence on the research progress of DGF. By analyzing the benefits and limitations of DGF research, we try to identify gaps in current research.
Pengfei Wang, Xu Zhou, Tai Yue, Peihong Lin, Yingying Liu, Kai Lu   +5 more
wiley   +1 more source

How test suites impact fault localisation starting from the size

IET Software, Volume 12, Issue 3, Page 190-205, June 2018., 2018
Although a test suite is indispensable for conducting effective fault localisation, not much work has been done to study how the test suite impacts fault localisation. This study presents a systematic study for a deeper understanding of their relation.
Yan Lei, Chengnian Sun, Xiaoguang Mao, Zhendong Su   +3 more
wiley   +1 more source

A Unified Framework for Automated Testing of Robotic Process Automation Workflows Using Symbolic and Concolic Analysis

Machines
Robotic Process Automation is a technology that replicates human interactions with user interfaces across various applications. However, testing Robotic Process Automation implementations remains challenging due to the dynamic nature of workflows.
Ciprian Paduraru, Marina Cernat, Adelina-Nicoleta Staicu   +2 more
doaj   +1 more source

CAFA: A Checksum‐Aware Fuzzing Assistant Tool for Coverage Improvement

Security and Communication Networks, Volume 2018, Issue 1, 2018., 2018
Fuzzing is an effective technique to discover vulnerabilities that involves testing applications by constructing invalid input data. However, for applications with checksum mechanism, fuzzing can only achieve low coverage because samples generated by the fuzzer are possibly incapable of passing the checksum verification.
Xiaolong Liu, Qiang Wei, Qingxian Wang, Zheng Zhao, Zhongxu Yin, Emanuele Maiorana   +5 more
wiley   +1 more source

Behaviour Preservation across Code Versions in Erlang

Scientific Programming, Volume 2018, Issue 1, 2018., 2018
In any alive and nontrivial program, the source code naturally evolves along the lifecycle for many reasons such as the implementation of new functionality, the optimization of a bottleneck, or the refactoring of an obscure function. Frequently, these code changes affect various different functions and modules, so it can be difficult to know whether ...
David Insa, Sergio Pérez, Josep Silva, Salvador Tamarit, Can Özturan   +4 more
wiley   +1 more source