2017 · Conference paper
Rico: A Mobile App Dataset for Building Data-Driven Design Applications
Rico is a dataset of Android app designs and a runtime mining system that needs no access to or modification of app source code. Crowd workers used free Google Play apps through a web interface to a device farm, recording interaction traces. An automated crawler then replayed each trace and kept exploring, using a screenshot-and-resource-id similarity heuristic to identify new UI states. The paper reports 10,811 traces and 72,219 unique UIs from 9,772 apps in 27 categories. Each UI has a screenshot, augmented view hierarchy, explored interactions, transition animations and a 64-dimensional autoencoder layout vector.
Scope and limitations
A dataset and collection system, not a reconstruction method: the paper proposes UI code generation and interaction modeling as possible uses but does not generate code or reconstruct apps. It records UIs and interactions reached during human sessions capped at 10 minutes, each followed by one hour of automated crawling, not complete app behavior, backend logic or source code. Multimedia, productivity and personalization categories were excluded, and only free apps were mined. Coverage was evaluated on 10 popular apps by counting unique UIs, a measure that depends on the similarity heuristic (6% false-positive and 3% false-negative rates on 1,044 labeled pairs). The demonstrated application is autoencoder-based layout similarity search with qualitative examples. The 2017 snapshot will age as apps change.
Why it fits this collection
Adds a large runtime-mined corpus of Android screenshots, view hierarchies and interaction traces that the paper proposes for UI code generation and interaction modeling, complementing the collection's screenshot-to-code app reconstruction papers.
Publication and review details
- Venue
- UIST 2017
- Status
- Conference paper
- Publication / posting date
- October 20, 2017
- Date source
- ACM-deposited Crossref metadata gives 20 October 2017 for both online and print publication; this precedes the October 22–25 conference dates printed in the paper and is not inferred from them.
- DOI
- 10.1145/3126594.3126651
Crossref, the paper PDF and the project's BibTeX agree on the eight-author order, UIST ’17 proceedings and DOI; Crossref supplies pages 845–854. The author-hosted PDF is the 10-page ACM-formatted paper; no arXiv version was found. The paper's link interactionmining.org/rico now redirects to the archive page, while the older rico.html path returns 404. The archive page differs from the paper: its abstract and dataset description cite more than 9.3k apps and 66k unique UIs, so the released v0.1 files should not be assumed to match the paper's 9,772 apps and 72,219 UIs. Separate downloads include screenshots with view hierarchies (6 GB), traces (6 GB), animations (214 GB), metadata, layout vectors and later semantic annotations. The linked copyright notice says screenshots may contain copyrighted work and makes downloaders accept University of Illinois terms. These disclaim warranties, require the researcher to indemnify the Rico team and university, permit sharing with associates who accept the same terms, and bind a commercial employer. No separate code release is linked. Download links answered HEAD requests, but no dataset files were downloaded or analyzed.
Sources reviewed
Source review only; experiments were not rerun for this collection. Cite the original authors using the linked paper or BibTeX.