Leveraging the wisdom of the crowd to build an ecosystem of software ecosystems in the context of polyglot microservices-based applications

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One of the major challenges in the software industry is how to develop large-scale systems, with high quality, low cost, and within schedule. Software reuse is a key factor that may significantly improve developers' productivity, as it helps developers save time and efforts. Large-scale systems, are rarely developed from scratch, they are generally built upon existing software artifacts so that developers can build on top of what others have already done. Moreover, automation is a key concern in software development and validation. It helps improve productivity while ensuring the quality of produced software. The fast pace of evolution in the IT industry and the staggering growth of new technologies around the new generation of, polyglot, containerized and microservices--based applications put an increasing pressure on software development and deployment practice to fully exploit this paradigm shift. In fact, for this architectural style, small and loosely coupled modules or microservices are developed, deployed, and scaled independently to compose cloud--native applications. Microservices are built around separate business functionalities. Microservices-based systems are extremely complex and are among the most elaborated systems produced by software engineers. It is unlikely that Non-experienced engineers have the knowledge required to understand, maintain, and evolve the components of such a system. And only some experts have the necessary expertise and knowledge to do it correctly and efficiently. As the development of microservices-based systems can only pass through the collective knowledge of several experts, the goal of our research program is to leverage the knowledge and expertise of this limited number of experts in a way that can benefit a larger number of software engineers. To this end, we propose to use examples of software artifacts elaborated by these experts to learn the necessary knowledge to enhance the automation and the supports of software engineering activities related to the development and validation of microservices-based systems. This proposal ties in with our long-standing goal to produce theories, empirical evidence, frameworks, and tools for the automation of software development and maintenance activities in general.