SNSF Project - SURF MobileAppsData

About SURF-MobileAppsData

The SURF-MobileAppsData project will investigate concepts, techniques, and tools for mining mobile apps data available in app stores to support software engineers in the maintenance and evolution activities for these apps. In particular, the goal of mining data of mobile apps is to build an analysis framework and a feedback-driven environment to help developers to build better mobile applications by supporting them to (i) shorten the development life cycle, and (ii) to accommodate actual user needs. Hence, the main purpose of the SURF-MobileAppsData project is to surf the large amount of data that characterizes any app in an app store with the aim of substantially advancing the current state-of-the-art in mining mobile apps in several novel directions: by providing a multi-level, multi-source feedback mechanism for developers and users; by devising means for multi-source interlinking of user requests and actual changes; and by better wiring up feature development and bug fixing.

Duration: September 2016 - August 2019

Funding: SNF (Total Costs: 349.926 CHF)

Publications, Tools and Datasets

 

2018

Ardoc

[C34]  G. Grano, A. Ciurumelea, S. Panichella, F. Palomba, H. Gall.: Exploring the Integration of User Feedback in Automated Testing of Android Applications. Proceedings of the IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER 2018) RANK: B.  

Ardoc

[C33] C. Vassallo, S. Panichella, F. Palomba, S. Proksch, A. Zaidman and H. Gall:  Context is King: The Develop er Persp ective on the Usage of Static Analysis Tools. Proceedings of the IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER 2018)RANK: B.   

2017

Ardoc

[C32]  G. Grano, A. Di Sorbo, F. Mercaldo, C. Visaggio, G. Canfora, S. Panichella: Android Apps and User Feedback: a Dataset for Software Evolution and Quality Improvement. Proceedings of the International Workshop on App Market Analytics (WAMA 2017). Pderborn, Germany.  

Ardoc

[C31] C. Vassallo, G. Schermann, F. Zampetti, D. Romano, P. Leitner, A. Zaidman, M. di Penta, S. Panichella: A Tale of CI Build Failures: an Open Source and a Financial Organization Perspective. Proceedings of the 33rd International Conference on Software Maintenance and Evolution (ICSME 2017). Shangai, Asia. RANK: A.   

Ardoc

[C28] F. Palomba, P. Salza,Adelina Ciurumelea,Sebastiano PanichellaHarald Gall, F. Ferrucci, A. De Lucia:   Recommending and Localizing Change Requests for Mobile Apps based on User Reviews. Proceedings of the 39th IEEE International Conference on Software Engineering (ICSE 2017). Buenos Aires, Argentina. RANK: A* 

Ardoc

[C29] Andrea Di Sorbo, Sebastiano PanichellaCarol Alexandru, Corrado A. Visaggio, Gerardo Canfora, Harald GallSURF: Summarizer of User Reviews Feedback. Proceedings of the 39th IEEE International Conference on Software Engineering (ICSE 2017). Buenos Aires, Argentina. RANK: A* 

Ardoc

[C27] Y. Zhou, R. Gu, T. Chen, Z. Huang, Sebastiano PanichellaHarald GallAnalyzing APIs Documentation and Code to Detect Directive Defects. Proceedings of the 39th IEEE International Conference on Software Engineering (ICSE 2017). Buenos Aires, Argentina. RANK: A* 

Ardoc

[C26] Adelina Ciurumelea, Andreas Schaufelbühl, Sebastiano Panichella and Harald GallAnalyzing Reviews and Code of Mobile Apps for better Release Planning. Proceedings of the 24th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2017). Klagenfurt, Austria. RANK: B   

 

 

2016

Ardoc

[C24] Sebastiano Panichella, Andrea Di Sorbo, Emitza Guzman, Corrado Aaron Visaggio, Gerardo Canfora and Harald GallARdoc: App Reviews Development Oriented Classifier. 24th ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE 2016). Seattle, WA, USA. RANK: A  

ApproachOverview

[C23] Andrea Di Sorbo, Sebastiano Panichella, Carol Alexandru, Junji Shimagaki, Aaron Visaggio, Gerardo Canfora and Harald Gall : What Would Users Change in My App? Summarizing App Reviews for Recommending Software Changes. 24th ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE 2016). Seattle, WA, USA. RANK: A   

 

Tools:

SURF-tool  

Datasets,  Replication Packages and Appendices:

SURF-Replication-Package  

Replication Package for: "Analyzing APIs Documentation and Code to Detect Directive Defects" 

Dataset of the paper: Android Apps and User Feedback: a Dataset for Software Evolution and Quality Improvement.

Recommending and Localizing Code Changes for Mobile Apps based on User Reviews: Online Appendix

- Replication Package for "Analyzing Reviews and Code of Mobile Apps for a better Release Planning Organization".

Replication Package for "What Would Users Change in My App? Summarizing App Reviews for Recommending Software Changes"