BibSLEIGH — Jiaguang

Travelled to:

1 × Brazil
1 × Korea
1 × Portugal
1 × Russia
1 × USA

Collaborated with:

Y.J.0001 J.Wang M.G.0001 H.Liu Y.Liu X.Song M.Z.0001 J.Gao Y.Fu Y.Wang X.Yang C.Liu W.Zhao Y.Lu L.Zhang Y.Jiang H.Zhang M.Gu H.Shi M.Wang Z.Lin G.Ding M.Hu X.Cheng J.Guo Y.Zhao Q.Chen G.Chen Y.Yang J.Liang Y.Chen C.Zhou Z.Yang Z.Li Y.Deng W.N.N.Hung R.Wang X.Shi X.Jiao H.Song

Talks about:

semant (5) learn (5) seeker (4) fuzz (4) analysi (3) system (3) optim (3) base (3) use (3) workflow (2)

Person: Jiaguang Sun

DBLP: Sun:Jiaguang

Contributed to:

2013

2012

2008

2007

2017

2018

2019

Wrote 17 papers:

ESEC-FSE-2013-JiangLZDSGS #design #embedded #multi #optimisation #using: Design and optimization of multi-clocked embedded systems using formal technique (YJ, ZL, HZ, YD, XS, MG, JS), pp. 703–706.
ESEC-FSE-2013-JiangZLSHGS #analysis #reliability #runtime: System reliability calculation based on the run-time analysis of ladder program (YJ, HZ, HL, XS, WNNH, MG, JS), pp. 695–698.
CIKM-2012-LinDH0S #automation #image #random #using #visual notation: Automatic image annotation using tag-related random search over visual neighbors (ZL, GD, MH, JW, JS), pp. 1784–1788.
SAC-2008-LuZS #semantics #towards: Towards trace semantics for WS-CDL with alignments (YL, LZ, JS), pp. 95–99.
ICEIS-AIDSS-2007-YingboJJ #learning #predict #process #using #workflow: Using Decision Tree Learning to Predict Workflow Activity Time Consumption (YL, JW, JS), pp. 69–75.
SAC-2007-YingboJJ #approach #machine learning #workflow: A machine learning approach to semi-automating workflow staff assignment (YL, JW, JS), pp. 340–345.
ASE-2017-ChengZS0S #automation #fault #integer #named #type inference: IntPTI: automatic integer error repair with proper-type inference (XC, MZ0, XS, MG0, JS), pp. 996–1001.
ASE-2017-WangZJS0S #optimisation #reachability #static analysis: A static analysis tool with optimizations for reachability determination (YW, MZ0, YJ0, XS, MG0, JS), pp. 925–930.
ASE-2017-YangJ0SGL: A language model for statements of software code (YY, YJ0, MG0, JS, JG, HL), pp. 682–687.
ASE-2018-GaoYFJS #learning #named #platform #semantics: VulSeeker: a semantic learning based vulnerability seeker for cross-platform binary (JG, XY, YF, YJ0, JS), pp. 896–899.
ASE-2018-LiuLZJS #contract #named #security #semantics #towards: S-gram: towards semantic-aware security auditing for Ethereum smart contracts (HL, CL, WZ, YJ0, JS), pp. 814–819.
ESEC-FSE-2018-GaoYFJSS #learning #named #semantics: VulSeeker-pro: enhanced semantic learning based binary vulnerability seeker with emulation (JG, XY, YF, YJ0, HS, JS), pp. 803–808.
ESEC-FSE-2018-GuoJZCS #difference #fuzzing #learning #named #testing: DLFuzz: differential fuzzing testing of deep learning systems (JG, YJ0, YZ, QC, JS), pp. 739–743.
ESEC-FSE-2018-LiangJCWZS #fuzzing #industrial #named #optimisation #parallel: PAFL: extend fuzzing optimizations of single mode to industrial parallel mode (JL, YJ0, YC, MW, CZ, JS), pp. 809–814.
ESEC-FSE-2018-LiuYLJZS #clone detection #detection #named #semantics #sketching #transaction: EClone: detect semantic clones in Ethereum via symbolic transaction sketch (HL, ZY, CL, YJ0, WZ, JS), pp. 900–903.
ASE-2019-WangC00S #analysis #fault #memory management #named #pointer: TsmartGP: A Tool for Finding Memory Defects with Pointer Analysis (YW, GC, MZ0, MG0, JS), pp. 1170–1173.
ESEC-FSE-2019-ShiWFWSJSJS #enterprise #fuzzing #industrial #kernel #linux: Industry practice of coverage-guided enterprise Linux kernel fuzzing (HS, RW, YF, MW, XS, XJ, HS, YJ0, JS), pp. 986–995.