App store mining and analysis
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Yuanyuan Zhang | Mark Harman | Afnan A. Al-Subaihin | Anthony Finkelstein | Federica Sarro | Yue Jia | William J. Martin
[1] Fan Wu,et al. Genetic improvement for adaptive software engineering (keynote) , 2014, SEAMS 2014.
[2] Ahmed E. Hassan,et al. Studying the relationship between source code quality and mobile platform dependence , 2014, Software Quality Journal.
[3] A. Hassan,et al. What Do Mobile App Users Complain About ? A Study on Free iOS Apps , 2014 .
[4] Rachel Harrison,et al. Retrieving and analyzing mobile apps feature requests from online reviews , 2013, 2013 10th Working Conference on Mining Software Repositories (MSR).
[5] Ying Zou,et al. An Exploratory Study on the Relation between User Interface Complexity and the Perceived Quality , 2014, ICWE.
[6] Walid Maalej,et al. Bug report, feature request, or simply praise? On automatically classifying app reviews , 2015, 2015 IEEE 23rd International Requirements Engineering Conference (RE).
[7] Rajesh Vasa,et al. An Analysis of the Mobile App Review Landscape: Trends and Implications , 2013 .
[8] John A. Clark,et al. The GISMOE challenge: constructing the pareto program surface using genetic programming to find better programs (keynote paper) , 2012, 2012 Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering.
[9] Yuanyuan Zhang,et al. The App Sampling Problem for App Store Mining , 2015, 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories.
[10] Justyna Petke,et al. Reducing Energy Consumption Using Genetic Improvement , 2015, GECCO.
[11] Christos Faloutsos,et al. Why people hate your app: making sense of user feedback in a mobile app store , 2013, KDD.
[12] Mario Linares Vásquez,et al. Supporting evolution and maintenance of Android apps , 2014, ICSE Companion.
[13] Hammad Khalid. On identifying user complaints of iOS apps , 2013, 2013 35th International Conference on Software Engineering (ICSE).
[14] Walid Maalej,et al. User feedback in the appstore: An empirical study , 2013, 2013 21st IEEE International Requirements Engineering Conference (RE).
[15] Ahmed E. Hassan,et al. What Do Mobile App Users Complain About? , 2015, IEEE Software.
[16] Michele Lanza,et al. Software Analytics for Mobile Applications--Insights & Lessons Learned , 2013, 2013 17th European Conference on Software Maintenance and Reengineering.
[17] Mark Harman,et al. Ieee Transactions on Evolutionary Computation 1 , 2022 .
[18] Mario Linares Vásquez,et al. Revisiting Android reuse studies in the context of code obfuscation and library usages , 2014, MSR 2014.
[19] Walid Maalej,et al. How Do Users Like This Feature? A Fine Grained Sentiment Analysis of App Reviews , 2014, 2014 IEEE 22nd International Requirements Engineering Conference (RE).
[20] Tao Xie,et al. WHYPER: Towards Automating Risk Assessment of Mobile Applications , 2013, USENIX Security Symposium.
[21] Yuanyuan Zhang,et al. Search based software engineering for software product line engineering: a survey and directions for future work , 2014, SPLC.
[22] Yuanyuan Zhang,et al. App store mining and analysis: MSR for app stores , 2012, 2012 9th IEEE Working Conference on Mining Software Repositories (MSR).
[23] Tim Menzies. Beyond data mining; towards "idea engineering" , 2013, PROMISE.
[24] Peter J. Bentley,et al. Investigating app store ranking algorithms using a simulation of mobile app ecosystems , 2013, 2013 IEEE Congress on Evolutionary Computation.
[25] Alessandra Gorla,et al. Checking app behavior against app descriptions , 2014, ICSE.
[26] Yuanyuan Zhang,et al. Feature lifecycles as they spread, migrate, remain, and die in App Stores , 2015, 2015 IEEE 23rd International Requirements Engineering Conference (RE).