  Programming screencasts (e.g., video tutorials on Youtube or live coding
stream on Twitch) are important knowledge source for developers to learn
programming knowledge, especially the workflow of completing a programming
task. Nonetheless, the image nature of programming screencasts limits the
accessibility of screencast content and the workflow embedded in it, resulting
in a gap to access and interact with the content and workflow in programming
screencasts. Existing non-intrusive methods are limited to extract either
primitive human-computer interaction (HCI) actions or coarse-grained video
fragments.In this work, we leverage Computer Vision (CV) techniques to build a
programming screencast analysis tool which can automatically extract code-line
editing steps (enter text, delete text, edit text and select text) from
screencasts.Given a programming screencast, our approach outputs a sequence of
coding steps and code snippets involved in each step, which we refer to as
programming workflow. The proposed method is evaluated on 41 hours of tutorial
videos and live coding screencasts with diverse programming environments.The
results demonstrate our tool can extract code-line editing steps accurately and
the extracted workflow steps can be intuitively understood by developers.
