Generating executable robotic process automation scripts from unsegmented user interface logs

Robotic Process Automation (RPA) is an emerging automation technology in the field of Business Process Management (BPM) that creates software (SW) robots to partially or fully automate rule-based and repetitive tasks (or simply routines) performed by human users in their applications’ user interfaces (UIs). RPA tools are able to capture in dedicated UI logs the execution of many routines of interest. A UI log consists of user actions that are mixed in some order that reflects the particular order of their execution by the user, thus potentially belonging to different routines. Moreover, when considering state-of-the-art RPA technology, it becomes apparent that the current generation of RPA tools is driven by predefined rules and manual configurations made by expert users rather than automated techniques. Towards this direction, this thesis tries to mitigate the involvement of skilled human experts, throughout the development of (i) an interactive approach to the automated segmentation of UI logs (i.e., the challenge to automatically understand which user actions contribute to which routines inside a UI log), and (ii) the SmartRPA approach to the automated identification of the variation points of a routine, to enable the selection of the most suitable routine variants to be implemented with a SW robot directly from a UI log, thus skipping completely the manual modeling activity of the flowchart diagrams. Both the approaches are implemented and evaluated employing both synthetic and real-world datasets.