M. Harman
F. Sarro
ABSTRACT
This talk presents results on analysis and testing of mobile apps and app stores, reviewing the work of the UCL App Analysis Group (UCLappA) on App Store Mining and Analysis. The talk also covers the work of the UCL CREST centre on Genetic Improvement, applicable to app improvement and optimisation.
- E. T. Barr, Y. Brun, P. Devanbu, M. Harman, and F. Sarro. The plastic surgery hypothesis. In 22nd ACM SIGSOFT International Symposium on the Foundations of Software Engineering (FSE 2014), pages 306--317, Hong Kong, China, November 2014. Google Scholar
Digital Library
- E. T. Barr, M. Harman, Y. Jia, A. Marginean, and J. Petke. Automated software transplantation. In Proceedings of the 2015 International Symposium on Software Testing and Analysis, ISSTA 2015, Baltimore, MD, USA, July 12-17, 2015, pages 257--269, 2015. Google ScholarDigital Library
- E. T. Barr, M. Harman, P. McMinn, M. Shahbaz, and S. Yoo. The oracle problem in software testing: A survey. IEEE Transactions on Software Engineering, 41(5):507--525, May 2015.Google ScholarDigital Library
- B. Bruce, J. Petke, and M. Harman. Reducing energy consumption using genetic improvement. In Genetic and evolutionary computation conference (GECCO 2015), pages 1327--1334, Madrid, Spain, July 2015. Google ScholarDigital Library
- M. Gabel and Z. Su. A study of the uniqueness of source code. In 18th ACM SIGSOFT international symposium on foundations of software engineering (FSE 2010), pages 147--156, Santa Fe, New Mexico, USA, 7-11 Nov. 2010. ACM. Google ScholarDigital Library
- A. Gorla, I. Tavecchia, F. Gross, and A. Zeller. Checking app behavior against app descriptions. In 36th International Conference on Software Engineering (ICSE 2014), pages 1025--1035, 2014. Google ScholarDigital Library
- E. Guzman and W. Maalej. How do users like this feature? a fine grained sentiment analysis of app reviews. In Requirements Engineering (RE 2014), pages 153--162, Aug 2014.Google ScholarCross Ref
- M. Harman, Y. Jia, W. B. Langdon, J. Petke, I. H. Moghadam, S. Yoo, and F. Wu. Genetic improvement for adaptive software engineering. In 9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2014), pages 1--4, New York, NY, USA, 2014. ACM. Google ScholarDigital Library
- M. Harman, Y. Jia, P. R. Mateo, and M. Polo. Angels and monsters: an empirical investigation of potential test effectiveness and efficiency improvement from strongly subsuming higher order mutation. In ACM/IEEE International Conference on Automated Software Engineering (ASE '14), pages 397--408, 2014. Google ScholarDigital Library
- M. Harman, Y. Jia, and Y. Zhang. App store mining and analysis: MSR for App Stores. In 9th Working Conference on Mining Software Repositories (MSR 2012), Zurich, Switzerland, 2-3 June 2012. Google ScholarDigital Library
- M. Harman, Y. Jia, and Y. Zhang. Achievements, open problems and challenges for search based software testing (keynote). In 8th IEEE International Conference on Software Testing, Verification and Validation (ICST 2014), Graz, Austria, April 2015.Google Scholar
- M. Harman, W. B. Langdon, and Y. Jia. Babel pidgin: SBSE can grow and graft entirely new functionality into a real world system. In SSBSE, 2014.Google ScholarCross Ref
- M. Harman, W. B. Langdon, Y. Jia, D. R. White, A. Arcuri, and J. A. Clark. The GISMOE challenge: Constructing the pareto program surface using genetic programming to find better programs (keynote paper). In 27th IEEE/ACM International Conference on Automated Software Engineering (ASE 2012), pages 1--14, Essen, Germany, September 2012. Google ScholarDigital Library
- M. Harman, W. B. Langdon, and W. Weimer. Genetic programming for reverse engineering (keynote paper). In R. Oliveto and R. Robbes, editors, 20th Working Conference on Reverse Engineering (WCRE 2013), Koblenz, Germany, 14-17 October 2013. IEEE.Google ScholarCross Ref
- A. E. Hassan. The Road Ahead for Mining Software Repositories. In Proceedings of the Interlational Conference on Frontiers of Software Maintenance (FoSM '08), pages 48--57, Beijing, China, 28 Sept.-4 Oct. 2008. IEEE.Google ScholarCross Ref
- C. Iacob and R. Harrison. Retrieving and Analyzing Mobile App Feature Requests from Online Reviews. In Proceedings of the 10th Working Conference on Mining Software Repositories (MSR '13), San Francisco, California, USA, 18-19 May 2013. Google ScholarDigital Library
- H. Khalid, E. Shihab, M. Nagappan, and A. Hassan. What do mobile app users complain about? A study on free iOS apps. IEEE Software, 32(3):70--77, 2014.Google ScholarCross Ref
- W. B. Langdon and M. Harman. Optimising existing software with genetic programming. IEEE Transactions on Evolutionary Computation (TEVC), 19(1):118--135, Feb 2015.Google ScholarCross Ref
- W. Martin. Causal impact for app store analysis. In ICSE Student Research Competition, 2016. Google ScholarDigital Library
- W. Martin, M. Harman, Y. Jia, F. Sarro, and Y. Zhang. The app sampling problem for app store mining. In 12th IEEE/ACM Working Conference on Mining Software Repositories, MSR 2015, Florence, Italy, May 16-17, 2015, pages 123--133, 2015. Google ScholarDigital Library
- W. Martin, F. Sarro, and M. Harman. Causal impact analysis applied to app releases in google play and windows phone store. Technical Report RN/15/07, UCL Computer Science Department, December 2015.Google Scholar
- W. Martin, F. Sarro, Y. Jia, Y. Zhang, and M. Harman. A survey of app store analysis for software engineering. Technical Report RN/16/02, UCL Computer Science Department, January 2016.Google Scholar
- E. Omar, S. Ghosh, and D. Whitley. Comparing search techniques for finding subtle higher order mutants. In Conference on Genetic and Evolutionary Computation (GECCO 2014), pages 1271--1278. ACM, 2014. Google ScholarDigital Library
- F. Sarro, A. A. Al-Subaihin, M. Harman, Y. Jia, W. Martin, and Y. Zhang. Feature lifecycles as they spread, migrate, remain, and die in app stores. In 23rd IEEE International Requirements Engineering Conference, RE 2015, Ottawa, ON, Canada, August 24-28, 2015, pages 76--85, 2015.Google ScholarCross Ref
- M. D. Syer, M. Nagappan, B. Adams, and A. E. Hassan. Studying the relationship between source code quality and mobile platform dependence. Software Quality Journal, 2014. To appear; available online. Google ScholarDigital Library
- D. R. White, J. Clark, J. Jacob, and S. Poulding. Searching for resource-efficient programs: Low-power pseudorandom number generators. In 2008 Genetic and Evolutionary Computation Conference (GECCO 2008), pages 1775--1782, Atlanta, USA, July 2008. Google ScholarDigital Library
- F. Wu, M. Harman, Y. Jia, J. Krinke, and W. Weimer. Deep parameter optimisation. In Genetic and evolutionary computation conference (GECCO 2015), pages 1375--1382, Madrid, Spain, July 2015. Google ScholarDigital Library
Index Terms
- Mobile app and app store analysis, testing and optimisation
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