Embedding app-library graph for neural third party library recommendation

Bo Li, Qiang He, Feifei Chen, Xin Xia, Li Li, John Grundy, Yun Yang

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

16 Citations (Scopus)

Abstract

The mobile app marketplace has fierce competition for mobile app developers, who need to develop and update their apps as soon as possible to gain first mover advantage. Third-party libraries (TPLs) offer developers an easier way to enhance their apps with new features. However, how to find suitable candidates among the high number and fast-changing TPLs is a challenging problem. TPL recommendation is a promising solution, but unfortunately existing approaches suffer from low accuracy in recommendation results. To tackle this challenge, we propose GRec, a graph neural network (GNN) based approach, for recommending potentially useful TPLs for app development. GRec models mobile apps, TPLs, and their interactions into an app-library graph. It then distills app-library interaction information from the app-library graph to make more accurate TPL recommendations. To evaluate GRec's performance, we conduct comprehensive experiments based on a large-scale real-world Android app dataset containing 31,432 Android apps, 752 distinct TPLs, and 537,011 app-library usage records. Our experimental results illustrate that GRec can significantly increase the prediction accuracy and diversify the prediction results compared with state-of-the-art methods. A user study performed with app developers also confirms GRec's usefulness for real-world mobile app development.

Original languageEnglish
Title of host publicationProceedings of the 29th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering
EditorsDiomidis Spinellis, Georgios Gousios, Marsha Chechik, Massimiliano Di Penta
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages466-477
Number of pages12
ISBN (Electronic)9781450385626
DOIs
Publication statusPublished - 2021
EventJoint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering 2021 - Online, Athens, Greece
Duration: 23 Aug 202128 Aug 2021
Conference number: 29th
https://dl.acm.org/doi/proceedings/10.1145/3468264 (Proceedings)
https://2021.esec-fse.org (Website)

Conference

ConferenceJoint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering 2021
Abbreviated titleESEC/FSE 2021
Country/TerritoryGreece
CityAthens
Period23/08/2128/08/21
Internet address

Keywords

  • app-library graph
  • graph neural network
  • mobile app development
  • recommendation
  • third-party library

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