Travelled to:1 × China
1 × France
1 × Italy
1 × USA
Collaborated with:C.A.Sutton E.T.Barr C.Bird ∅ S.K.Dash D.Tarlow A.D.Gordon Y.Wei V.J.Hellendoorn J.Lacomis P.Yin E.J.Schwartz C.L.Goues G.Neubig B.Vasilescu
Talks about:code (7) sourc (3) model (3) learn (3) type (3) name (3) languag (2) natur (2) mine (2) use (2)
♂ Person: Miltiadis Allamanis
DBLP: Allamanis:Miltiadis
Facilitated 0 volumes:
Contributed to:
2015
2015
2014
20132018
2019
2019Wrote 10 papers:
- ESEC-FSE-2015-AllamanisBBS
- Suggesting accurate method and class names (MA, ETB, CB, CAS), pp. 38–49.
- ICML-2015-AllamanisTGW #modelling #natural language #source code
- Bimodal Modelling of Source Code and Natural Language (MA, DT, ADG, YW), pp. 2123–2132.
- FSE-2014-AllamanisBBS #learning
- Learning natural coding conventions (MA, ETB, CB, CAS), pp. 281–293.
- FSE-2014-AllamanisS #mining #source code
- Mining idioms from source code (MA, CAS), pp. 472–483.
- MSR-2013-AllamanisS #stack overflow #topic #what #why
- Why, when, and what: analyzing stack overflow questions by topic, type, and code (MA, CAS), pp. 53–56.
- MSR-2013-AllamanisS13a #mining #modelling #repository #source code #using
- Mining source code repositories at massive scale using language modeling (MA, CAS), pp. 207–216.
- ESEC-FSE-2018-DashAB #named #using
- RefiNym: using names to refine types (SKD, MA, ETB), pp. 107–117.
- ESEC-FSE-2018-HellendoornBBA #learning #type inference
- Deep learning type inference (VJH, CB, ETB, MA), pp. 152–162.
- ASE-2019-LacomisYSAGNV #approach #identifier #named
- DIRE: A Neural Approach to Decompiled Identifier Naming (JL, PY, EJS, MA, CLG, GN, BV), pp. 628–639.
- Onward-2019-Allamanis #machine learning #modelling
- The adverse effects of code duplication in machine learning models of code (MA), pp. 143–153.