Travelled to:1 × Cyprus
1 × France
1 × Germany
1 × India
1 × Portugal
1 × South Africa
1 × Switzerland
1 × The Netherlands
2 × Italy
3 × Canada
6 × USA
Collaborated with:M.Lanza M.D'Ambros A.A.Sawant L.Ponzanelli F.Palomba A.v.Deursen R.Robbes C.Bird ∅ M.Castelluccio A.Guzzi A.Mocci L.Hattori M.Duijn A.Kucera S.Ercan Q.Stokkink V.Hellendoorn P.T.Devanbu R.Slag M.d.Waard V.Humpa V.Kovalenko D.Spadini M.F.Aniche Y.Riche J.Goderie B.M.Georgsson B.v.Graafeiland M.Beller A.Zaidman E.Jürgens T.D.Sasso A.Cleve M.Lungu C.Vassallo H.C.Gall A.Ram M.Eck M.Dias G.Gousios D.Cassou S.Ducasse D.Fullerton F.Rigotti M.Pinzger L.Cerulo M.D.Penta M.Ceccarelli G.Canfora S.Oosterwaal R.Coelho E.Hill D.Binkley B.Dit D.Lawrie R.Oliveto
Talks about:code (16) overflow (7) stack (7) develop (5) review (5) sourc (5) mail (5) softwar (4) qualiti (4) chang (4)
♂ Person: Alberto Bacchelli
DBLP: Bacchelli:Alberto
Facilitated 8 volumes:
PrCo
PrCoPrCoPrCoChaCh
PrCoWebChChaCoContributed to:
201520152015
20142014
2013
2013
201320132013
20152012
2011
201120112011
2010201020102009
20162018
20182019Wrote 33 papers:
- CSCW-2015-GuzziBRD #coordination #developer #ide
- Supporting Developers’ Coordination in the IDE (AG, AB, YR, AvD), pp. 518–532.
- MSR-2015-DuijnKB #quality #stack overflow
- Quality Questions Need Quality Code: Classifying Code Fragments on Stack Overflow (MD, AK, AB), pp. 410–413.
- MSR-2015-ErcanSB #automation #predict #stack overflow
- Automatic Assessments of Code Explanations: Predicting Answering Times on Stack Overflow (SE, QS, AB), pp. 442–445.
- MSR-2015-GoderieGGB #named #predict #stack overflow
- ETA: Estimated Time of Answer Predicting Response Time in Stack Overflow (JG, BMG, BvG, AB), pp. 414–417.
- MSR-2015-HellendoornDB #modelling
- Will They Like This? Evaluating Code Contributions with Language Models (VH, PTD, AB), pp. 157–167.
- MSR-2015-SawantB #api #dataset
- A Dataset for API Usage (AAS, AB), pp. 506–509.
- MSR-2015-SlagWB #stack overflow #why
- One-Day Flies on StackOverflow — Why the Vast Majority of StackOverflow Users Only Posts Once (RS, MdW, AB), pp. 458–461.
- SANER-2015-DiasBGCD #fine-grained
- Untangling fine-grained code changes (MD, AB, GG, DC, SD), pp. 341–350.
- ICSME-2014-PonzanelliMBLF #detection #quality #stack overflow
- Improving Low Quality Stack Overflow Post Detection (LP, AM, AB, ML, DF), pp. 541–544.
- MSR-2014-BellerBZJ #code review #open source #problem #question
- Modern code reviews in open-source projects: which problems do they fix? (MB, AB, AZ, EJ), pp. 202–211.
- CSMR-2013-PonzanelliBL #comprehension #development
- Leveraging Crowd Knowledge for Software Comprehension and Development (LP, AB, ML), pp. 57–66.
- ICPC-2013-LanzaDBHR #named #process #realtime #visual notation
- Manhattan: Supporting real-time visual team activity awareness (ML, MD, AB, LH, FR), pp. 207–210.
- ICSE-2013-BacchelliB #challenge #code review #overview #perspective
- Expectations, outcomes, and challenges of modern code review (AB, CB), pp. 712–721.
- ICSE-2013-PonzanelliBL #ide #named #stack overflow
- Seahawk: stack overflow in the IDE (LP, AB, ML), pp. 1295–1298.
- ICSM-2013-HillBBDLO #feature model #question
- Which Feature Location Technique is Better? (EH, AB, DB, BD, DL, RO), pp. 408–411.
- MSR-2013-GuzziBLPD #communication #development #open source
- Communication in open source software development mailing lists (AG, AB, ML, MP, AvD), pp. 277–286.
- SCAM-J-2013-CeruloPBCC15 #detection #markov #named
- Irish: A Hidden Markov Model to detect coded information islands in free text (LC, MDP, AB, MC, GC), pp. 26–43.
- ICSE-2012-BacchelliSDL #classification #development #email
- Content classification of development emails (AB, TDS, MD, ML), pp. 375–385.
- ASE-2011-BacchelliCLM #documentation #natural language #semiparsing
- Extracting structured data from natural language documents with island parsing (AB, AC, ML, AM), pp. 476–479.
- CSEET-2011-HattoriBLL #game studies #learning
- Erase and rewind — Learning by replaying examples (LH, AB, ML, ML), p. 558.
- CSMR-2011-BacchelliLH #comprehension
- RTFM (Read the Factual Mails) — Augmenting Program Comprehension with Remail (AB, ML, VH), pp. 15–24.
- ICSE-2011-Bacchelli #email #re-engineering
- Exploring, exposing, and exploiting emails to include human factors in software engineering (AB), pp. 1074–1077.
- ICSE-2011-BacchelliLD #email #named #tool support
- Miler: a toolset for exploring email data (AB, ML, MD), pp. 1025–1027.
- FASE-2010-BacchelliDL #fault #question
- Are Popular Classes More Defect Prone? (AB, MD, ML), pp. 59–73.
- ICPC-2010-BacchelliDL #source code
- Extracting Source Code from E-Mails (AB, MD, ML), pp. 24–33.
- ICSE-2010-BacchelliLR #source code
- Linking e-mails and source code artifacts (AB, ML, RR), pp. 375–384.
- WCRE-1999-BacchelliDLR99a #benchmark #lightweight #metric #source code
- Benchmarking Lightweight Techniques to Link E-Mails and Source Code (AB, MD, ML, RR), pp. 205–214.
- FSE-2016-OosterwaalDCSB #code review #overview #perspective #visualisation
- Visualizing code and coverage changes for code review (SO, AvD, RC, AAS, AB), pp. 1038–1041.
- ASE-2018-KovalenkoPB #branch #mining #question
- Mining file histories: should we consider branches? (VK, FP, AB), pp. 202–213.
- ASE-2018-VassalloPBG #quality #question
- Continuous code quality: are we (really) doing that? (CV, FP, AB, HCG), pp. 790–795.
- ESEC-FSE-2018-RamSCB #empirical #overview #what
- What makes a code change easier to review: an empirical investigation on code change reviewability (AR, AAS, MC, AB), pp. 201–212.
- ESEC-FSE-2018-SpadiniAB #framework #mining #named #python #repository
- PyDriller: Python framework for mining software repositories (DS, MFA, AB), pp. 908–911.
- ESEC-FSE-2019-EckPCB #comprehension #developer #perspective #testing
- Understanding flaky tests: the developer's perspective (ME, FP, MC, AB), pp. 830–840.