Collaborated with:S.Chen F.Gao D.Cui Chao Shen 0001 Q.Feng Y.Cai R.Kazman H.Fang Y.Qu J.Chi Y.Jin A.He Q.Zheng Yadong Zhou Xukun Wang Z.Xu Ying Su X.Guan H.Wang X.Xie S.Lin Y.L.0001 Y.Li S.Qin Y.L.0003 Jianting Ji Hongyu Wu Wenyi Liu Man Su Zhanpei Jia
Talks about:model (3) softwar (2) predict (2) analysi (2) defect (2) ordinari (1) behavior (1) approach (1) wearabl (1) thermal (1)
Person: Ting Liu 0002
DBLP: 0002:Ting_Liu
Contributed to:
20182019
2019
201620172019Wrote 6 papers:
- ASE-2018-QuLCJCHZ #2d #fault #named #network #predict #using
- node2defect: using network embedding to improve software defect prediction (YQ, TL0, JC, YJ, DC, AH, QZ), pp. 844–849.
- ASE-2019-FengCKC0F #evolution #monitoring
- Active Hotspot: An Issue-Oriented Model to Monitor Software Evolution and Degradation (QF, YC, RK, DC, TL0, HF), pp. 986–997.
- ESEC-FSE-2019-WangXLLLQLL #layout #memory management
- Locating vulnerabilities in binaries via memory layout recovering (HW, XX, SWL, YL0, YL, SQ, YL0, TL0), pp. 718–728.
- CASE-2016-JiLSWLSCJ #analysis #behaviour #smarttech
- A human-centered smart home system with wearable-sensor behavior analysis (JJ, TL0, CS0, HW, WL, MS, SC, ZJ), pp. 1112–1117.
- CASE-2017-ChenGL #analysis #identification #markov #online #performance
- Load identification based on Factorial Hidden Markov Model and online performance analysis (SC, FG, TL0), pp. 1249–1253.
- CASE-2019-ZhouWXS00G #approach #learning #modelling #personalisation #predict
- A Model-Driven Learning Approach for Predicting the Personalized Dynamic Thermal Comfort in Ordinary Office Environment (YZ, XW, ZX, YS, TL0, CS0, XG), pp. 739–744.