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MOBILESoft 2020
Mon 13 - Wed 15 July 2020
co-located with ICSE 2020
Tue 14 Jul 2020 00:10 - 00:20 at MobileSoft - Mining and Reviews Chair(s): Christoph Csallner

Energy inefficiency is a major issue for the application users and they express their concerns using user feedback or app-reviews. That is why developers consistently analyze user feedback to identify recently emerged issues.

We have submitted our work in ACM MobileSoft 2020 where the findings of elaborate empirical study on supervised text classification and topic modeling approaches were reported for isolating energy related reviews from the hoard of feedback and for identifying recently emerged issues. We empirically studied and compared the accuracy, F1-score and run time of 60 machine-learning models with relevant feature combinations and 30 Neural Network-based models developed using six neural network architectures and three word embedding. Furthermore, we experimented the most frequently used string matching with results obtained from applying two of the state-of-the-art topic modeling algorithms in order to compare the techniques and to help the developers investigate the emerging issues responsible for energy inefficiency of the apps.

The proposed interactive visualization tool make it easy for the developers to traverse through the extensive result set generated by the text classification and topic modeling approaches and help them to better comprehend the outcomes of implemented model feature combinations, algorithms used. The data structure used for the tool stores the outcomes of discussed approaches and cumulatively updates itself whenever new developer performs any of the given approaches with a new data-set. This tool also gives developers choices to illustrate the result set as a whole, as a chunk, or as a gradual step-by-step representation.

Tue 14 Jul

Displayed time zone: (UTC) Coordinated Universal Time change

00:00 - 01:30
Mining Lifetime Properties of Android ProjectsTool Demos and Mobile Apps
Tool Demos and Mobile Apps
Demetrio Guilardi University of Quebec at Chicoutimi, Bianca Minetto NapoleĆ£o University of Quebec at Chicoutimi, Jalves Nicacio University of Quebec at Chicoutimi, Fabio Petrillo University of Quebec at Chicoutimi
ReviewViz: Assisting Developers Perform Empirical Study on Energy Consumption Related Reviews for Mobile ApplicationsTool Demos and Mobile Apps
Tool Demos and Mobile Apps
Mohammad Abdul Hadi University of British Columbia, Fatemeh Hendijani Fard University of British Columbia
Embracing Mobile App Evolution via Continuous Ecosystem Mining and CharacterizationVisions
Haipeng Cai Washington State University, USA
Collaborative Earthquake Detection and Response using Smart DevicesStudent Research Competition
Student Research Competition
Irshad Khan Department of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea.
Q&A - Mining and Reviews
Paper Presentations

Discussion with Authors / Attendees
Paper Presentations