Towards API Testing Across Cloud and Edge
Samuel Ackerman, Sanjib Choudhury, Nirmit Desai, Eitan Farchi, Dan, Gisolfi, Andrew Hicks, Saritha Route, Diptikalyan Saha

TL;DR
This paper proposes DSTK, a distributed testing framework that combines combinatorial test design and AI-driven feedback loops to effectively test API compositions across hybrid cloud and edge environments, addressing functional and reliability challenges.
Contribution
Introduction of DSTK, a novel distributed test framework that integrates combinatorial testing with AI-based search for comprehensive API testing in complex environments.
Findings
DSTK effectively covers functional and reliability requirements.
AI-driven search improves test scenario generation.
Framework addresses challenges of hybrid cloud and edge API testing.
Abstract
API economy is driving the digital transformation of business applications across the hybrid Cloud and edge environments. For such transformations to succeed, end-to-end testing of the application API composition is required. Testing of API compositions, even in centralized Cloud environments, is challenging as it requires coverage of functional as well as reliability requirements. The combinatorial space of scenarios is huge, e.g., API input parameters, order of API execution, and network faults. Hybrid Cloud and edge environments exacerbate the challenge of API testing due to the need to coordinate test execution across dynamic wide-area networks, possibly across network boundaries. To handle this challenge, we envision a test framework named Distributed Software Test Kit (DSTK). The DSTK leverages Combinatorial Test Design (CTD) to cover the functional requirements and then…
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Taxonomy
TopicsScientific Computing and Data Management · Software System Performance and Reliability · Software Testing and Debugging Techniques
