{'fraction_non_alphanumeric': 0.016835016835016835, 'fraction_numerical': 0.0, 'mean_word_length': 5.2377622377622375, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Survey of Automation Practices in Model-Driven Development and Operations

Model-driven methods are gaining momentum in the industry to develop software intensive systems. To be effective in quality and efficient in productivity, they require a strong toolchain with seamless automation. The DevOps approach can help reach this by unifying software development and operations with a strong focus on automation and monitoring. The aim of this short paper is to review automation tasks that are specific to a model-driven context and to classify them according to a typical DevOps lifecycle covering design, code, testing, deployment and runtime activities. Tasks are identified based on different industry use cases experienced in our research centre or reported in the literature. Some challenges are identified and discussed, especially related to the use of bots in a model-driven context.