CISE 2022 - 1st Workshop on Computational Intelligence and Software Engineering

co-located with the 23rd International Conference on Focused Software Process Improvement - PROFES 2022

November 21, 2022, Jyväskylä (Finland)

News

Monday 14th November 2022: the CISE proceedings are now available on Springer
Thursday 20th October 2022: the Program is now available on the main conference web page or here
Tuesday 4th October 2022: Deadline camera-ready version (Springer format)
Sunday 18th October 2022: Papers notification
Tuesday 13th October 2022: Papers submission deadline

In the last decades, software systems become pervasive in almost all areas of society growing in size, complexity, and functionality. This continuous growth demands the study, development, and implementation of new Software Engineering (SE) methodologies and tools (e.g., software analysis and design, software portability, formal verification and validation, software measurement, and software maintenance) to build more reliable software. However, despite the introduction of innovative approaches and paradigms useful in the SE field, their technological transfer on a larger scale has been very gradual and still almost limited. This is due to the critical aspects of 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. Human factor characterizes many of the problems associated with SE, including those observed in development effort estimation, software quality and reliability prediction, software design, and software testing. The rise of artificial intelligence (AI) has the potential to define effective approaches for improving software quality allowing 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 be effectively tackled using a combination of AI techniques such as NLP, machine learning, fuzzy logic, multi-objective search, metaheuristics, and clustering algorithms.

Starting from the above considerations, the objective of this workshop is to foster the integration between SE and AI communities to improve research results, teaching and mentoring, and ultimately industrial practice.

The Workshop will be inserted in the PROFES conference and will become part of the whole proceedings.

Contact Email: pasquale.ardimento@uniba.it