98 Publications (Page 1 of 4)
2024
An empirical study of task infections in Ansible scripts. Empirical Software Engineering
. | Journal Article
 
Authentic Learning for Information Flow Analysis
 
Container Orchestration Smells in ChaGPT-generated Kubernetes Manifests
 
Defect Categorization in Compilers: A Multi-vocal Literature Review. ACM Computing Surveys
. | Journal Article
 
State Reconciliation Defects in Infrastructure as Code
 
Student Perceptions of Authentic Learning to Learn White-box Testing
2023
Case Study-Based Approach of Quantum Machine Learning in Cybersecurity: Quantum Support Vector Machine for Malware Classification and Protection
Akter, M.S.⋅Shahriar, H.⋅Ahamed, S.I.⋅Gupta, K.D.⋅Rahman, M.⋅Mohamed, A.⋅Rahman, M.⋅Rahman, A. and Wu, F.
 
Come for syntax, stay for speed, understand defects: an empirical study of defects in Julia programs. Empirical Software Engineering
. | Journal Article
 
Dataset and Source Code for Paper: An Empirical Study of Insecure Coding Patterns in Julia Programs
 
Dataset and Source Code for the Paper Titled An Empirical Study of Task Infections in Ansible Manifests
 
Dataset - Defects in Ansible Infrastructure Orchestrator
 
Dataset for Paper - An Empirical Study of Bugs in Julia Programs
 
Detecting and Characterizing Propagation of Security Weaknesses in Puppet-based infrastructure Management. IEEE Transactions on Software Engineering
. | Journal Article
 
Log-related Coding Patterns to Conduct Postmortems of Attacks in Supervised Learning-based Projects. ACM Transactions on Privacy and Security
. | Journal Article
 
Practitioner Perceptions of Ansible Test Smells
Zhang, Y.⋅Wu, F. and Rahman, A.
(pp. 325-327)
 
Quality Assurance for Infrastructure Orchestrators: Emerging Results from Ansible
Zhang, Y.⋅Rahman, M.⋅Wu, F. and Rahman, A.
(pp. 322-324)
 
Security Misconfigurations in Open Source Kubernetes Manifests: An Empirical Study. ACM Transactions on Software Engineering and Methodology
. | Journal Article
 
Software Supply Chain Vulnerabilities Detection in Source Code: Performance Comparison between Traditional and Quantum Machine Learning Algorithms
Akter, M.S.⋅Faruk, Md.J.H.⋅Anjum, N.⋅Masum, M.⋅Shahriar, H.⋅Rahman, A.⋅Wu, F. and Cuzzocrea, A.
 
Survey - Ansible Test Smell
 
TaintPup
2022
A Novel Machine Learning Based Framework for Bridge Condition Analysis
Masum, M.⋅Anjum, N.⋅Hossain Faruk, M.J.⋅Shahriar, H.⋅Sakib, N.⋅Valero, M.⋅Karim, M.A.⋅Rahman, A.⋅Wu, F. and Cuzzocrea, A.
(pp. 5530-5535)
 
As Code Testing: Characterizing Test Quality in Open Source Ansible Development
Hassan, M.M. and Rahman, A.
(pp. 208-219)
 
Benefits, Challenges, and Research Topics: A Multi-vocal Literature Review of Kubernetes
Shamim, S.I.⋅Gibson, J.A.⋅Morrison, P. and Rahman, A.
 
Bie Vote: A Biometric Identification Enabled Blockchain-Based Secure and Transparent Voting Framework
Faruk, M.J.H.⋅Islam, M.⋅Alam, F.⋅Shahriar, H. and Rahman, A.
(pp. 253-258)
 
Can We use Authentic Learning to Educate Students about Secure Infrastructure as Code Development?
Rahman, A.⋅Shamim, S.I.⋅Shahriar, H. and Wu, F.
(pp. 631)