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- W3090725421 abstract "Businesses running software applications are moving more towards vendor-agnostic approaches. Integration testing becoming more demanding and complex than ever. Determining integration testing requires a solid dependency pattern among different software applications. We would like to use here an NLP (Natural language processing) & Machine learning Classification model-based approach to identify the dependency graph between different component across applications. There are existing approaches eliciting about package dependencies and source code-based dependencies. In this paper, we would like to introduce an approach to understand the communication dependencies between products rather than just high-level package or install dependencies. The communication dependencies will be prioritized based on the frequency and criticality of usage. The prioritization helps us in determining the software inter-dependency patterns for Integration testing." @default.
- W3090725421 created "2020-10-08" @default.
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- W3090725421 date "2020-06-01" @default.
- W3090725421 modified "2023-09-25" @default.
- W3090725421 title "Determining Software Inter-Dependency Patterns for Integration Testing by applying Machine learning on Logs and Telemetry data" @default.
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- W3090725421 doi "https://doi.org/10.1109/icrito48877.2020.9197868" @default.
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