Joint Conference of the 31st International Workshop on Software Measurement and 16th International Conference on Software Process and Product Measurement, IWSM-MENSURA 2022, İzmir, Turkey, 28 - 30 September 2022, vol.3272
© 2022 Copyright for this paper by its authors.Context: Artificial Intelligence (AI)-based software has gained increasing interest, especially in the last decade, due to advancements in underlying technologies and demands in varying business domains. With the proliferation to develop such software, there appears a need for developing methods and supporting tools/frameworks. Purpose: In this paper, we focus on tools/frameworks to automate AI-based software development process, from a holistic view. We review the scientific studies that were empirically validated and also evaluate their proposals with respect to basic characteristics including theme, research methods, types, domains, and a number of cases in empirical validations. Method: We elicit relevant studies (with the contribution type of tool or framework) from a larger set of primary studies identified by a systematic literature review on AI-based software development process. We select 14 primary studies in this context and analyze them with respect to the purposes of the proposals. Results: We review tools/frameworks that support AI-based software development process under four headings: software system development process, the development process of fair software, model development process, and model deployment and operation processes. We observe that domains of empirical validation are diverse while the number of empirical cases applied for validation is limited. Also, only half of the primary studies provide links to their proposals as open-source, which is very important for the repeatability of the empirical validations.