Asif Imtiaz Shaafi
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Asif Imtiaz Shaafi has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Eunjee Song
Department of Computer Science, Baylor University, Waco, TX, USA
3 shared publications - Tingshuo Miao
Department of Computer Science, Baylor University, Waco, TX, USA
3 shared publications - Greg Speegle
Baylor University
1 shared publication
Latest Publications
- Open Access
- 11 March 2026
- Published by Association for Computing Machinery (ACM)
- p. 52-59
Adaptive Risk Classification in Microservice Architectures: A GMM-Based Approach with Historical Data Normalization
- 11 March 2026
- Published by Association for Computing Machinery (ACM)
- p. 52-59
Open AccessAdaptive Risk Classification in Microservice Architectures: A GMM-Based Approach with Historical Data Normalization
- 16 April 2025
- Published by Springer Nature
- p. 108-121
Service Availability Ratio (SAR): An Availability Metric for Microservice
- 16 April 2025
- Published by Springer Nature
- p. 108-121
Service Availability Ratio (SAR): An Availability Metric for Microservice
- Open Access
- 30 March 2025
- Published by MDPI AG in Electronics
- Vol. 14 (7) , 1397
Systematic Mapping Study of Test Generation for Microservices: Approaches, Challenges, and Impact on System Quality
Software development underwent a significant shift with the adoption of microservice architecture. Such architecture offers modularity and scalability but introduces new testing challenges. This review aims to identify, categorize, and analyze key testing methods used in microservices-based systems, emphasizing how these methods address architectural challenges and affect overall system quality. The distributed nature and asynchronous communication patterns of microservices architecture create a pressing need for robust and adaptive testing approaches. We systematically reviewed relevant papers, categorized approaches, and analyzed their strengths, limitations, and impact on system reliability. Our findings reveal that contract testing, behavior-driven development, and automated regression testing are widely practiced, yet there is a notable shortage of dedicated test generation tools designed specifically for microservices (i.e., the automated creation of test cases and test scripts tailored to verify microservices’ functionality and interactions). Additionally, this study underscores the necessity of specialized tools and advocates mock services as a solution for stabilizing complex inter-service dependencies. This study offers insights that advance both research and practice, ultimately improving microservices system reliability.
- 30 March 2025
- Published by MDPI AG in Electronics
- Vol. 14 (7) , 1397
Open AccessSystematic Mapping Study of Test Generation for Microservices: Approaches, Challenges, and Impact on System Quality
Software development underwent a significant shift with the adoption of microservice architecture. Such architecture offers modularity and scalability but introduces new testing challenges. This review aims to identify, categorize, and analyze key testing methods used in microservices-based systems, emphasizing how these methods address architectural challenges and affect overall system quality. The distributed nature and asynchronous communication patterns of microservices architecture create a pressing need for robust and adaptive testing approaches. We systematically reviewed relevant papers, categorized approaches, and analyzed their strengths, limitations, and impact on system reliability. Our findings reveal that contract testing, behavior-driven development, and automated regression testing are widely practiced, yet there is a notable shortage of dedicated test generation tools designed specifically for microservices (i.e., the automated creation of test cases and test scripts tailored to verify microservices’ functionality and interactions). Additionally, this study underscores the necessity of specialized tools and advocates mock services as a solution for stabilizing complex inter-service dependencies. This study offers insights that advance both research and practice, ultimately improving microservices system reliability.