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Detecting SQL injection attacks by binary gray wolf optimizer and machine learning algorithms
SQL injection is one of the important security issues in web applications because it allows
an attacker to interact with the application's database. SQL injection attacks can be detected …
an attacker to interact with the application's database. SQL injection attacks can be detected …
A software defect prediction method using binary gray wolf optimizer and machine learning algorithms
Context Software defect prediction means finding defect-prone modules before the testing
process which will reduce testing cost and time. Machine learning methods can provide …
process which will reduce testing cost and time. Machine learning methods can provide …
A new binary chaos-based metaheuristic algorithm for software defect prediction
Software defect prediction is a critical challenge within software engineering aimed at
enhancing software quality by proactively identifying potential defects. This approach …
enhancing software quality by proactively identifying potential defects. This approach …
A Cost-effective and Machine-learning-based method to identify and cluster redundant mutants in software mutation testing
The quality of software test data is assessed through mutation testing. This technique
involves introducing various modifications (mutants) to the original code of the program. The …
involves introducing various modifications (mutants) to the original code of the program. The …
Data replication in distributed systems using olympiad optimization algorithm
Achieving timely access to data objects is a major challenge in big distributed systems like
the Internet of Things (IoT) platforms. Therefore, minimizing the data read and write …
the Internet of Things (IoT) platforms. Therefore, minimizing the data read and write …
Reliability estimation for inverse Pareto lifetime model based on unified hybrid censored data
Censoring plays an important role in the reliability and life testing trials due to its cost
optimality and time reduction properties. The unified hybrid censoring scheme is the …
optimality and time reduction properties. The unified hybrid censoring scheme is the …
An error-propagation aware method to reduce the software mutation cost using genetic algorithm
S Mohammad Javad Hosseini, B Arasteh… - Data technologies and …, 2021 - emerald.com
Purpose The purpose of this study is to reduce the number of mutations and, consequently,
reduce the cost of mutation test. The results of related studies indicate that about 40% of …
reduce the cost of mutation test. The results of related studies indicate that about 40% of …
Efficient software mutation test by clustering the single-line redundant mutants
Purpose Reducing the number of generated mutants by clustering redundant mutants,
reducing the execution time by decreasing the number of generated mutants and reducing …
reducing the execution time by decreasing the number of generated mutants and reducing …
Sahand: a software fault-prediction method using autoencoder neural network and k-means algorithm
B Arasteh, S Golshan, S Shami, F Kiani - Journal of Electronic Testing, 2024 - Springer
Software is playing a growing role in many safety-critical applications, and software systems
dependability is a major concern. Predicting faulty modules of software before the testing …
dependability is a major concern. Predicting faulty modules of software before the testing …
Effective software mutation-test using program instructions classification
The quantity of bugs that a software test-data finds determines its effectiveness. A useful
technique for assessing the efficacy of a test set is mutation testing. The primary issues with …
technique for assessing the efficacy of a test set is mutation testing. The primary issues with …