BibSLEIGH — Yang_Liu

Collaborated with:

X.Xie H.Hu L.M.0003 B.C.0001 J.Zhao Yuan Zhou 0005 S.Lin Y.Li Y.Xue T.Su G.Meng Y.L.0008 N.Du H.Chen X.Li S.Chen M.Chandramohan X.Du Z.Xing L.Fan L.Xu C.Chen J.S.0001 Q.Hu X.P.0001 W.Zhao G.Pu H.Wang Y.Yang Junyao Hou X.Wang Y.L.0001 M.Xue W.Le Y.Huang T.Lin Z.Xu C.Y.Cho H.B.K.Tan H.Xiao D.Sanán H.Hansen A.Tiu L.Zou B.Yu K.Huang D.Zhou Y.Wang X.Wu C.Zhang S.Qin T.L.0002 J.S.Dong Y.Chen K.Wu W.Yang Y.Yao Z.Su Q.Guo H.Liu Y.Zheng C.Fan J.Hao Z.Meng R.Shen Y.Chen F.Juefei-Xu F.Zhang J.Sun B.L.0026 L.L.0029 Y.Wang

Talks about:

deep (8) system (6) learn (5) framework (4) analysi (4) petri (4) test (4) fuzz (4) net (4) manufactur (3)

Person: Yang Liu 0003

DBLP: 0003:Yang_Liu

Contributed to:

2016

2017

2018

2019

2016

2017

Wrote 25 papers:

FSE-2016-ChandramohanXXL #architecture #named: BinGo: cross-architecture cross-OS binary search (MC, YX, ZX, YL0, CYC, HBKT), pp. 678–689.
FSE-2016-XieCLLL #analysis #dependence #named #summary: Proteus: computing disjunctive loop summary via path dependency analysis (XX, BC0, YL0, WL, XL), pp. 61–72.
ASE-2017-LinMXXSPLZD #design #mining #reuse: Mining implicit design templates for actionable code reuse (YL0, GM, YX, ZX, JS0, XP0, YL0, WZ, JSD), pp. 394–404.
ASE-2017-LinSXLSH #invariant #named: FiB: squeezing loop invariants by interpolation between Forward/Backward predicate transformers (SWL, JS0, HX, YL0, DS, HH), pp. 793–803.
ESEC-FSE-2017-LiCCLLT #fuzzing #named: Steelix: program-state based binary fuzzing (YL, BC0, MC, SWL, YL0, AT), pp. 627–637.
ESEC-FSE-2017-SuMCWYYPLS #android #modelling #probability #testing #user interface: Guided, stochastic model-based GUI testing of Android apps (TS, GM, YC, KW, WY, YY, GP, YL0, ZS), pp. 245–256.
ESEC-FSE-2017-XieCZLLL #analysis #named #termination: Loopster: static loop termination analysis (XX, BC0, LZ, SWL, YL0, XL), pp. 84–94.
ASE-2018-FanSCMLXP #android #fault #programming: Efficiently manifesting asynchronous programming errors in Android apps (LF, TS, SC, GM, YL0, LX, GP), pp. 486–497.
ASE-2018-HuangCPZWLZ #difference #generative #named: ClDiff: generating concise linked code differences (KH, BC0, XP0, DZ, YW, YL0, WZ), pp. 679–690.
ASE-2018-HuangCXLL #comparison #difference: Tell them apart: distilling technology differences from crowd-scale comparison discussions (YH, CC, ZX, TL, YL0), pp. 214–224.
ASE-2018-MaJZSXLCSLLZW #learning #multi #named #testing: DeepGauge: multi-granularity testing criteria for deep learning systems (LM0, FJX, FZ, JS, MX, BL0, CC, TS, LL0, YL0, JZ, YW), pp. 120–131.
ESEC-FSE-2018-ChenLCXL #configuration management #framework #fuzzing #named: FOT: a versatile, configurable, extensible fuzzing framework (HC, YL, BC0, YX, YL0), pp. 867–870.
ESEC-FSE-2018-ChenSFMXLX #mobile #question #what: Are mobile banking apps secure? what can be improved? (SC, TS, LF, GM, MX, YL0, LX), pp. 797–802.
ASE-2019-DuX000Z #analysis #framework #network: A Quantitative Analysis Framework for Recurrent Neural Network (XD, XX, YL0, LM0, YL0, JZ), pp. 1062–1065.
ASE-2019-GuoCXMHLLZL #deployment #development #empirical #framework #learning #platform #towards: An Empirical Study Towards Characterizing Deep Learning Development and Deployment Across Different Frameworks and Platforms (QG, SC, XX, LM0, QH, HL, YL0, JZ, XL), pp. 810–822.
ASE-2019-Hu0XY0Z #framework #learning #mutation testing #testing: DeepMutation++: A Mutation Testing Framework for Deep Learning Systems (QH, LM0, XX, BY, YL0, JZ), pp. 1158–1161.
ASE-2019-XieCLM0Z #fuzzing #network: Coverage-Guided Fuzzing for Feedforward Neural Networks (XX, HC, YL0, LM0, YL0, JZ), pp. 1162–1165.
ASE-2019-ZhengFXS0HMLSC #automation #game studies #learning #named #online #testing #using: Wuji: Automatic Online Combat Game Testing Using Evolutionary Deep Reinforcement Learning (YZ, CF, XX, TS, LM0, JH, ZM, YL0, RS, YC), pp. 772–784.
ESEC-FSE-2019-DuXLM0Z #analysis #learning #modelling #named: DeepStellar: model-based quantitative analysis of stateful deep learning systems (XD, XX, YL0, LM0, YL0, JZ), pp. 477–487.
ESEC-FSE-2019-LiXCWZXWL #adaptation #detection #effectiveness #fuzzing #named: Cerebro: context-aware adaptive fuzzing for effective vulnerability detection (YL, YX, HC, XW, CZ, XX, HW, YL0), pp. 533–544.
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-HuYLD #automation #identification #petri net #scalability: Critical stages and their identification in large scale automated manufacturing systems via Petri nets (HH, YY, YL0, ND), pp. 413–420.
CASE-2017-DuHZL #automation #petri net #robust #using: Robust control of automated manufacturing systems with complex structures using Petri Nets (ND, HH, YZ0, YL0), pp. 364–369.
CASE-2017-HouH0L #constraints #distributed #petri net: Decentralized supervisory control of Generalized Mutual Exclusion Constraints in Petri Nets (JH, HH, YZ0, YL0), pp. 358–363.
CASE-2017-WangHZL #approach #automation #petri net #robust: A robust control approach to automated manufacturing systems allowing failures and reworks with Petri nets (XW, HH, YZ0, YL0), pp. 370–375.