Travelled to:1 × China
1 × Germany
1 × Switzerland
2 × USA
Collaborated with:D.Zhang T.Xie H.Zhang S.Han Q.Lin Y.Tao S.Kim R.Wu P.Nobel S.Ge X.He R.Ding Q.Wang Q.Fu H.Zhang J.Wang K.Chen X.Wang L.Zhang E.Lan H.Mei H.Z.0002 Y.Xu J.Lou R.Yao M.Chintalapati J.Chen D.Hao F.Gao Z.Xu K.Hsieh K.Sui C.Li Y.Wu X.Zhang B.Qiao C.Xie X.Yang Q.Cheng Z.Li J.C.0003 F.Shen
Talks about:larg (3) code (3) softwar (2) cluster (2) system (2) servic (2) stack (2) scale (2) mine (2) data (2)
Person: Yingnong Dang
DBLP: Dang:Yingnong
Contributed to:
2015
2013
2012
2012
2012
2012
201820192019Wrote 10 papers:
- VLDB-2015-DingWDFZZ #clustering #named #performance #scalability
- YADING: Fast Clustering of Large-Scale Time Series Data (RD, QW, YD, QF, HZ, DZ), pp. 473–484.
- MSR-2013-WangDZCXZ #api #mining #source code
- Mining succinct and high-coverage API usage patterns from source code (JW, YD, HZ, KC, TX, DZ), pp. 319–328.
- ASE-2012-WangD0ZLM #question
- Can I clone this piece of code here? (XW, YD, LZ, DZ, EL, HM), pp. 170–179.
- CSEET-2012-ZhangDHX #education
- Teaching and Training for Software Analytics (DZ, YD, SH, TX), p. 92.
- FSE-2012-TaoDXZK #case study #how #industrial
- How do software engineers understand code changes?: an exploratory study in industry (YT, YD, TX, DZ, SK), p. 51.
- ICSE-2012-DangWZZN #clustering #named #similarity #stack
- ReBucket: A method for clustering duplicate crash reports based on call stack similarity (YD, RW, HZ, DZ, PN), pp. 1084–1093.
- ICSE-2012-HanDGZX #debugging #in the large #mining #performance #stack
- Performance debugging in the large via mining millions of stack traces (SH, YD, SG, DZ, TX), pp. 145–155.
- ESEC-FSE-2018-LinHDZSXLLWYCZ #predict
- Predicting Node failure in cloud service systems (QL, KH, YD, HZ0, KS, YX, JGL, CL, YW, RY, MC, DZ), pp. 480–490.
- ASE-2019-ChenHLZHGXDZ #online #scalability
- Continuous Incident Triage for Large-Scale Online Service Systems (JC, XH, QL, HZ, DH, FG, ZX, YD, DZ), pp. 364–375.
- ESEC-FSE-2019-ZhangXLQZDXYCLC #detection #robust
- Robust log-based anomaly detection on unstable log data (XZ, YX, QL, BQ, HZ0, YD, CX, XY, QC, ZL, JC0, XH, RY, JGL, MC, FS, DZ), pp. 807–817.