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Fingerprint Lei Maが取り組む研究トピックをご確認ください。これらのトピックラベルは、この人物の研究に基づいています。これらを共に使用することで、固有の認識が可能になります。

  • 1 同様のプロファイル
Testing Engineering & Materials Science
Learning systems Engineering & Materials Science
Application programming interfaces (API) Engineering & Materials Science
Dynamic analysis Engineering & Materials Science
Application programs Engineering & Materials Science
Static analysis Engineering & Materials Science
Software engineering Engineering & Materials Science
Software testing Engineering & Materials Science

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研究成果 2012 2019

  • 79 引用
  • 5 h指数
  • 31 会議での発言
  • 5 記事
  • 2 編集
1 引用 (Scopus)

Automated Cross-Platform GUI Code Generation for Mobile Apps

Chen, S., Fan, L., Su, T., Ma, L., Liu, Y. & Xu, L., 3 21 2019, AI4Mobile 2019 - 2019 IEEE 1st International Workshop on Artificial Intelligence for Mobile. Liu, Y., Xue, M., Ma, L. & Li, L. (版). 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).

研究成果: 著書/レポートタイプへの貢献会議での発言

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

DeepCT: Tomographic Combinatorial Testing for Deep Learning Systems

Ma, L., Juefei-Xu, F., Xue, M., Li, B., Li, L., Liu, Y. & Zhao, J., 3 15 2019, SANER 2019 - Proceedings of the 2019 IEEE 26th International Conference on Software Analysis, Evolution, and Reengineering. Shihab, E., Lo, D. & Wang, X. (版). 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).

研究成果: 著書/レポートタイプへの貢献会議での発言

Learning systems
Testing
Deep learning
7 引用 (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., 7 10 2019, ISSTA 2019 - Proceedings of the 28th ACM SIGSOFT International Symposium on Software Testing and Analysis. Zhang, D. & Moller, A. (版). 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).

研究成果: 著書/レポートタイプへの貢献会議での発言

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

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

Du, X., Xie, X., Li, Y., Ma, L., Liu, Y. & Zhao, J., 8 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. (版). 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).

研究成果: 著書/レポートタイプへの貢献会議での発言

Recurrent neural networks
Learning systems
Chemical analysis
Image classification
Speech recognition

DeepVisual: A visual programming tool for deep learning systems

Xie, C., Qi, H., Ma, L. & Zhao, J., 5 2019, Proceedings - 2019 IEEE/ACM 27th International Conference on Program Comprehension, ICPC 2019. IEEE Computer Society, p. 130-134 5 p. 8813295. (IEEE International Conference on Program Comprehension; 巻数 2019-May).

研究成果: 著書/レポートタイプへの貢献会議での発言

Computer programming
Learning systems
Neural networks
Network architecture
Drag