If you made any changes in Pure these will be visible here soon.

Fingerprint Dive into the research topics where Lei Ma is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 6 Similar Profiles
Testing Engineering & Materials Science
Learning systems Engineering & Materials Science
Application programming interfaces (API) Engineering & Materials Science
Navigation Engineering & Materials Science
Robots Engineering & Materials Science
Visibility Engineering & Materials Science
Application programs Engineering & Materials Science
Software testing Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2012 2020

  • 183 Citations
  • 7 h-Index
  • 31 Conference contribution
  • 6 Article
  • 2 Editorial

CDA: Characterising Deprecated Android APIs

Li, L., Gao, J., Bissyandé, T. F., Ma, L., Xia, X. & Klein, J., Jan 1 2020, (Accepted/In press) In : Empirical Software Engineering.

Research output: Contribution to journalArticle

Application programming interfaces (API)
Application programs
Maintainability
Ecosystems
2 Citations (Scopus)

Automated Cross-Platform GUI Code Generation for Mobile Apps

Chen, S., Fan, L., Su, T., Ma, L., Liu, Y. & Xu, L., Mar 21 2019, AI4Mobile 2019 - 2019 IEEE 1st International Workshop on Artificial Intelligence for Mobile. Liu, Y., Xue, M., Ma, L. & Li, L. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 13-16 4 p. 8672718. (AI4Mobile 2019 - 2019 IEEE 1st International Workshop on Artificial Intelligence for Mobile).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Graphical user interfaces
Application programs
Image processing
Code generation
Costs
7 Citations (Scopus)

DeepCT: Tomographic Combinatorial Testing for Deep Learning Systems

Ma, L., Juefei-Xu, F., Xue, M., Li, B., Li, L., Liu, Y. & Zhao, J., Mar 15 2019, SANER 2019 - Proceedings of the 2019 IEEE 26th International Conference on Software Analysis, Evolution, and Reengineering. Shihab, E., Lo, D. & Wang, X. (eds.). Institute of Electrical and Electronics Engineers Inc., p. 614-618 5 p. 8668044. (SANER 2019 - Proceedings of the 2019 IEEE 26th International Conference on Software Analysis, Evolution, and Reengineering).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Learning systems
Testing
Deep learning
7 Citations (Scopus)

Deephunter: A coverage-guided fuzz testing framework for deep neural networks

Xie, X., Ma, L., Juefei-Xu, F., Xue, M., Chen, H., Liu, Y., Zhao, J., Li, B., Yin, J. & See, S., Jul 10 2019, ISSTA 2019 - Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis. Zhang, D. & Moller, A. (eds.). Association for Computing Machinery, Inc, p. 158-168 11 p. (ISSTA 2019 - Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Seed
Testing
Defects
Deep neural networks
Accidents
5 Citations (Scopus)

DeepStellar: Model-based quantitative analysis of stateful deep learning systems

Du, X., Xie, X., Li, Y., Ma, L., Liu, Y. & Zhao, J., Aug 12 2019, ESEC/FSE 2019 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. Apel, S., Dumas, M., Russo, A. & Pfahl, D. (eds.). Association for Computing Machinery, Inc, p. 477-487 11 p. (ESEC/FSE 2019 - Proceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Recurrent neural networks
Learning systems
Chemical analysis
Image classification
Speech recognition