Travelled to:1 × Austria
1 × Canada
1 × Hungary
1 × India
1 × South Africa
1 × Spain
1 × The Netherlands
1 × United Kingdom
2 × China
2 × France
2 × Switzerland
3 × Germany
4 × Italy
6 × USA
Collaborated with:T.Zimmermann B.Murphy C.Bird T.Ball ∅ P.J.Guo K.Herzig Thomas Zimmermann 0001 H.Gall E.R.Murphy-Hill L.A.Williams D.Lo J.Czerwonka P.T.Devanbu M.Kim M.Pinzger V.R.Basili G.S.Walia J.C.Carver A.Zeller C.S.Maddila C.Bansal G.K.Cheung Ryan Cooper Dan Greenawalt Tyson Solberg K.Muslu A.Hindle K.Hullett E.Schuh J.Hopson M.Sherriff M.A.Vouk P.S.Kochhar F.Thung B.Ray M.Nagappan J.Huang C.Harrison B.C.Phillips E.Kocaguneli T.Menzies R.Das A.Tarvo A.Teterev R.Premraj L.Williams E.Giger L.Layman S.Guckenheimer J.Beehler A.Begel P.L.Li R.Kivett Z.Zhan S.Jeon A.J.Ko Thomas Debeauvais Kevin Carter E.Harpstead Jose J. Guajardo
Talks about:softwar (11) predict (10) develop (9) studi (8) empir (7) defect (6) analysi (5) data (5) bug (5) qualiti (4)
♂ Person: Nachiappan Nagappan
DBLP: Nagappan:Nachiappan
Facilitated 2 volumes:
PrCoPrCoContributed to:
2015
2015
201520152014
20132013
20122012
20122012
201120112011201120102010
2010200920092008200820082006
2005200520042019
2014
20142015Wrote 39 papers:
- ESEC-FSE-2015-LoNZ #how #re-engineering #research
- How practitioners perceive the relevance of software engineering research (DL, NN, TZ), pp. 415–425.
- ICSE-v2-2015-HerzigN #detection #empirical #using
- Empirically Detecting False Test Alarms Using Association Rules (KH, NN), pp. 39–48.
- ICST-2015-KochharTNZL #automation #comprehension #developer #testing
- Understanding the Test Automation Culture of App Developers (PSK, FT, NN, TZ, DL), pp. 1–10.
- MSR-2015-RayNBNZ
- The Uniqueness of Changes: Characteristics and Applications (BR, MN, CB, NN, TZ), pp. 34–44.
- ICSE-2014-Murphy-HillZN #development #game studies #how #quality #question #video
- Cowboys, ankle sprains, and keepers of quality: how is video game development different from software development? (ERMH, TZ, NN), pp. 1–11.
- ICSE-2014-MusluBNC #case study #distributed #version control
- Transition from centralized to decentralized version control systems: a case study on reasons, barriers, and outcomes (KM, CB, NN, JC), pp. 334–344.
- CHI-2013-HuangZNHP #how
- Mastering the art of war: how patterns of gameplay influence skill in Halo (JH, TZ, NN, CH, BCP), pp. 695–704.
- ICSE-2013-KocaguneliZBNM #development #distributed #harmful #question
- Distributed development considered harmful? (EK, TZ, CB, NN, TM), pp. 882–890.
- ICSE-2013-Murphy-HillZBN #debugging #design
- The design of bug fixes (ERMH, TZ, CB, NN), pp. 332–341.
- FSE-2012-KimZN #case study #challenge #refactoring
- A field study of refactoring challenges and benefits (MK, TZ, NN), p. 50.
- ICSE-2012-ZimmermannNGM #debugging #predict
- Characterizing and predicting which bugs get reopened (TZ, NN, PJG, BM), pp. 1074–1083.
- ICSM-2012-HindleBZN #analysis #developer #implementation #question #requirements #topic
- Relating requirements to implementation via topic analysis: Do topics extracted from requirements make sense to managers and developers? (AH, CB, TZ, NN), pp. 243–252.
- MSR-2012-BirdN #development #distributed #open source #scalability #what
- Who? Where? What? Examining distributed development in two large open source projects (CB, NN), pp. 237–246.
- CSCW-2011-BirdMNZ #empirical #re-engineering #research
- Empirical software engineering at Microsoft Research (CB, BM, NN, TZ), pp. 143–150.
- CSCW-2011-GuoZNM #debugging #exclamation
- “Not my bug!” and other reasons for software bug report reassignments (PJG, TZ, NN, BM), pp. 395–404.
- ESEC-FSE-2011-BirdNMGD #exclamation #quality
- Don’t touch my code!: examining the effects of ownership on software quality (CB, NN, BM, HG, PTD), pp. 4–14.
- ICSE-2011-HullettNSH #data analysis #development #game studies
- Data analytics for game development (KH, NN, ES, JH), pp. 940–943.
- ICSE-2011-LiKZJNMK #difference
- Characterizing the differences between pre- and post- release versions of software (PLL, RK, ZZ, SeJ, NN, BM, AJK), pp. 716–725.
- ICST-2011-CzerwonkaDNTT #analysis #case study #experience #named #predict
- CRANE: Failure Prediction, Change Analysis and Test Prioritization in Practice — Experiences from Windows (JC, RD, NN, AT, AT), pp. 357–366.
- ICST-2011-ZimmermannNHPW #dependence #empirical
- An Empirical Study on the Relation between Dependency Neighborhoods and Failures (TZ, NN, KH, RP, LW), pp. 347–356.
- ICSE-2010-GuoZNM #debugging #empirical #predict
- Characterizing and predicting which bugs get fixed: an empirical study of Microsoft Windows (PJG, TZ, NN, BM), pp. 495–504.
- ICST-2010-ZimmermannNW #predict #security
- Searching for a Needle in a Haystack: Predicting Security Vulnerabilities for Windows Vista (TZ, NN, LAW), pp. 421–428.
- TAP-2010-Nagappan #re-engineering
- Myths in Software Engineering: From the Other Side (NN), pp. 3–5.
- ESEC-FSE-2009-ZimmermannNGGM #empirical #fault #predict #process #scalability
- Cross-project defect prediction: a large scale experiment on data vs. domain vs. process (TZ, NN, HG, EG, BM), pp. 91–100.
- ICSE-2009-BirdNDGM #case study #development #distributed #empirical #quality
- Does distributed development affect software quality? An empirical case study of Windows Vista (CB, NN, PTD, HG, BM), pp. 518–528.
- FSE-2008-PinzgerNM #developer #network #predict #question
- Can developer-module networks predict failures? (MP, NN, BM), pp. 2–12.
- ICSE-2008-NagappanMB #case study #empirical #quality
- The influence of organizational structure on software quality: an empirical case study (NN, BM, VRB), pp. 521–530.
- ICSE-2008-WaliaCN #fault #modelling
- The effect of the number of inspectors on the defect estimates produced by capture-recapture models (GSW, JCC, NN), pp. 331–340.
- ICSE-2008-ZimmermannN #analysis #dependence #fault #graph #network #predict #using
- Predicting defects using network analysis on dependency graphs (TZ, NN), pp. 531–540.
- MSR-2008-LaymanNGBB #analysis #mining #visual notation
- Mining software effort data: preliminary analysis of visual studio team system data (LL, NN, SG, JB, AB), pp. 43–46.
- ICSE-2006-NagappanBZ #component #metric #mining #predict
- Mining metrics to predict component failures (NN, TB, AZ), pp. 452–461.
- A-MOST-2005-SherriffNWV #estimation #fault #haskell #metric #using
- Early estimation of defect density using an in-process Haskell metrics model (MS, NN, LAW, MAV), pp. 64–69.
- ICSE-2005-NagappanB #fault #metric #predict #using
- Use of relative code churn measures to predict system defect density (NN, TB), pp. 284–292.
- ICSE-2005-NagappanB05a #fault #static analysis #tool support
- Static analysis tools as early indicators of pre-release defect density (NN, TB), pp. 580–586.
- ICSE-2004-Nagappan #metric #reliability #testing #towards
- Toward a Software Testing and Reliability Early Warning Metric Suite (NN), pp. 60–62.
- ESEC-FSE-2019-MaddilaBN #case study #predict #scalability
- Predicting pull request completion time: a case study on large scale cloud services (CSM, CB, NN), pp. 874–882.
- CHI-PLAY-2014-CheungZN #experience #game studies #how
- The first hour experience: how the initial play can engage (or lose) new players (GKC, TZ0, NN), pp. 57–66.
- FDG-2014-Debeauvais0NCCG #empirical
- Off with their assists: An empirical study of driving skill in Forza Motorsport 4 (TD, TZ0, NN, KC, RC, DG, TS).
- CHI-PLAY-2015-HarpsteadZNGCSG #game studies #people #what
- What Drives People: Creating Engagement Profiles of Players from Game Log Data (EH, TZ0, NN, JJG, RC, TS, DG), pp. 369–379.