1st Workshop on Computational Intelligence and Software Engineering (CISE 2022)

In the last decades, despite the introduction of innovative approaches and paradigms useful in the SE (Software Engineering) field, their technological transfer on a larger scale has been very gradual and still almost limited. This is due to the critical aspects in SE with respect to other well-founded engineering disciplines since SE is strongly influenced by social aspects (i.e., human knowledge, skills, expertise, and interactions) that are highly context-driven, non-mechanical and strongly based on context and semantic knowledge. The rise of artificial intelligence (AI) has the potential to define effective approaches for improving software quality allowing a growth in the project success rates. AI can provide the capabilities to assist software teams in many aspects, from automating routine tasks to providing project analytics and actionable recommendations, and even making decisions where non-trivial context detection and information processing are needed. Recent works reported that several software engineering problems could effectively tackled using a combination of AI techniques such as NLP, machine learning, fuzzy logic, multi-objective search, metaheuristics, and clustering algorithms.