M. Stats, , 2018.

, Mobile App Retention Challenge, 2016.

, Android Lint, 2018.

S. Adolph, W. Hall, and P. Kruchten, Using grounded theory to study the experience of software development, Empirical Software Engineering, vol.16, pp.487-513, 2011.

N. Ayewah, D. Hovemeyer, D. Morgenthaler, J. Penix, and W. Pugh, Using static analysis to find bugs, IEEE software, vol.25, p.5, 2008.

C. Calcagno, D. Distefano, J. Dubreil, D. Gabi, P. Hooimeijer et al., Moving fast with software verification, NASA Formal Methods Symposium, pp.3-11, 2015.

A. Carette, M. Younes, and G. Hecht, Investigating the energy impact of android smells, 2017 IEEE 24th International Conference on. IEEE, pp.115-126, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01403485

M. Christakis and C. Bird, What developers want and need from program analysis: an empirical study, Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering, pp.332-343, 2016.

W. John, J. Creswell, and . Creswell, Research design: Qualitative, quantitative, and mixed methods approaches, 2017.

G. Barney, J. Glaser, and . Holton, Remodeling grounded theory, Historical Social Research/Historische Sozialforschung. Supplement, pp.47-68, 2007.

C. Guo, J. Zhang, J. Yan, Z. Zhang, and Y. Zhang, Characterizing and detecting resource leaks in Android applications, Proceedings of the 28th IEEE/ACM International Conference on Automated Software Engineering, pp.389-398, 2013.

S. Habchi, G. Hecht, R. Rouvoy, and N. Moha, Code Smells in iOS Apps: How do they compare to Android, Proceedings of the 4th International Conference on Mobile Software Engineering and Systems, pp.110-121, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01471294

G. Hecht, N. Moha, and R. Rouvoy, An empirical study of the performance impacts of android code smells, Proceedings of the International Workshop on Mobile Software Engineering and Systems, pp.59-69, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01276904

G. Hecht, B. Omar, and R. Rouvoy, Tracking the Software Quality of Android Applications along their Evolution, 30th IEEE/ACM International Conference on Automated Software Engineering, p.12, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01178734

E. Siw, B. Hove, and . Anda, Experiences from conducting semistructured interviews in empirical software engineering research, Software metrics, 2005. 11th ieee international symposium, p.10, 2005.

B. Johnson, Y. Song, E. Murphy-hill, and R. Bowdidge, Why don't software developers use static analysis tools to find bugs, Proceedings of the 2013 International Conference on Software Engineering, pp.672-681, 2013.

M. Linares-vásquez, G. Bavota, C. Bernal-cárdenas, and R. Oliveto, Mining energy-greedy api usage patterns in android apps: an empirical study, Proceedings of the 11th Working Conference on Mining Software Repositories. ACM, pp.2-11, 2014.

M. Linares-vásquez, C. Vendome, Q. Luo, and D. Poshyvanyk, How developers detect and fix performance bottlenecks in android apps, Software Maintenance and Evolution (ICSME), 2015 IEEE International Conference on. IEEE, pp.352-361, 2015.

Y. Liu, C. Xu, and S. Cheung, Where has my battery gone? Finding sensor related energy black holes in smartphone applications, Pervasive Computing and Communications (PerCom), 2013 IEEE International Conference on. IEEE, pp.2-10, 2013.

Y. Liu, C. Xu, and S. Cheung, Characterizing and detecting performance bugs for smartphone applications, Proceedings of the 36th International Conference on Software Engineering, pp.1013-1024, 2014.

A. Nistor and L. Ravindranath, Suncat: Helping developers understand and predict performance problems in smartphone applications, Proceedings of the 2014 International Symposium on Software Testing and Analysis, pp.282-292, 2014.

G. Daniel, J. M. Oliver, T. Serovich, and . Mason, Constraints and opportunities with interview transcription: Towards reflection in qualitative research, Social forces, vol.84, pp.1273-1289, 2005.

F. Palomba, D. D. Nucci, A. Panichella, A. Zaidman, and A. D. Lucia, Lightweight detection of Android-specific code smells: The aDoctor project, 2017 IEEE 24th International Conference on. IEEE, pp.487-491, 2017.

A. Pathak, C. Hu, and M. Zhang, Bootstrapping energy debugging on smartphones: a first look at energy bugs in mobile devices, Proceedings of the 10th ACM Workshop on Hot Topics in Networks, p.5, 2011.

A. Pathak, A. Jindal, C. Hu, and . Midkiff, What is keeping my phone awake?: characterizing and detecting no-sleep energy bugs in smartphone apps, Proceedings of the 10th international conference on Mobile systems, applications, and services, pp.267-280, 2012.

J. Reimann, M. Brylski, and U. Aßmann, A Tool-Supported Quality Smell Catalogue For Android Developers, Proc. of the conference Modellierung 2014 in the Workshop Modellbasierte und modellgetriebene Softwaremodernisierung-MMSM, 2014.

C. Sadowski, J. Van-gogh, C. Jaspan, E. Söderberg, and C. Winter, Tricorder: Building a Program Analysis Ecosystem, IEEE/ACM 37th IEEE International Conference on Software Engineering, vol.1, pp.598-608, 2015.

C. Schmidt, The analysis of semi-structured interviews. A companion to qualitative research, pp.253-258, 2004.

M. Kristín-fjóla-tómasdóttir, A. Aniche, and . Van-deursen, Why and how JavaScript developers use linters, Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering, pp.578-589, 2017.

P. Vekris, R. Jhala, S. Lerner, and Y. Agarwal, Towards Verifying Android Apps for the Absence of No-Sleep Energy Bugs, HotPower, 2012.

J. Zhang, A. Musa, and W. Le, A comparison of energy bugs for smartphone platforms, Engineering of Mobile-Enabled Systems (MOBS), pp.25-30, 2013.

L. Zhang, S. Mark, R. P. Gordon, M. Dick, P. Mao et al., Adel: An automatic detector of energy leaks for smartphone applications, Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis. ACM, pp.363-372, 2012.