“…Over the past decades, software engineering research identified and attempted to solve a variety of issues pertaining to several phases of the software lifecycle. However, the fast pace of evolution in the IT industry and the staggering growth of new technologies [50] based on APIs [30,45,25], containers [48], microservices [40,1,41,29], cloud and virtualization, put an increasing pressure on software development [2] and deployment [49,47] practice to fully exploit this paradigm shift. This led to constant questioning of existing techniques [30] and results of software engineering research [36,35], leading to investigating the use of AI and ML-based techniques to solve software engineering problems in topics related to software reuse [16], recommendation systems [34], mining software repositories [36], software data analytics and patterns mining [38,19,37,31] , program analysis and visualization [39,33], testing in the cloud environment, Edge-Enabled systems [24], microservices architecture [43] and mobile applications.…”