Spring Cloud Data Flow vs. Spring Framework vs. Testwell CTC++ vs. pygame Comparison Chart

Microservice-based streaming and batch data processing for Cloud Foundry and Kubernetes. Spring Cloud Data Flow provides tools to create complex topologies for streaming and batch data pipelines. The data pipelines consist of Spring Boot apps, built using the Spring Cloud Stream or Spring Cloud Task microservice frameworks. Spring Cloud Data Flow supports a range of data processing use cases, from ETL to import/export, event streaming, and predictive analytics. The Spring Cloud Data Flow server uses Spring Cloud Deployer, to deploy data pipelines made of Spring Cloud Stream or Spring Cloud Task applications onto modern platforms such as Cloud Foundry and Kubernetes. A selection of pre-built stream and task/batch starter apps for various data integration and processing scenarios facilitate learning and experimentation. Custom stream and task applications, targeting different middleware or data services, can be built using the familiar Spring Boot style programming model.

Testwell CTC++ is a powerful instrumentation-based code coverage and dynamic analysis tool for C and C++ code. With certain add-on components CTC++ can be used also on C#, Java and Objective-C code. Further, again with certain add-on components, CTC++ can be used to analyse code basically at any embedded target machines, also in very small ones (limited memory, no operating system). CTC++ provides Line Coverage, Statement Coverage, Function Coverage, Decision Coverage, Multicondition Coverage, Modified Condition/Decision Coverage (MC/DC), Condition Coverage. As a dynamic analysis tool, CTC++ shows the execution counters (how many times executed) in the code, i.e. more than a plain executed/not executed information. You can also use CTC++ to measure function execution costs (normally time) and to enable function entry/exit tracing at test time. CTC++ is easy to use.