BibSLEIGH
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Used together with:
code (7)
predict (6)
peer (4)
impact (3)
applic (3)

Stem churn$ (all stems)

16 papers:

SIGMODSIGMOD-2015-HuangZYDLND0Z #big data #predict
Telco Churn Prediction with Big Data (YH, FZ, MY, KD, YL, BN, WD, QY, JZ), pp. 607–618.
SANERSANER-2015-GuerroujAR #stack overflow
The influence of App churn on App success and StackOverflow discussions (LG, SA, PCR), pp. 321–330.
SCAMSCAM-2015-FaragoHF #cumulative #maintenance
Cumulative code churn: Impact on maintainability (CF, PH, RF), pp. 141–150.
RecSysRecSys-2015-SifaOB #analysis #migration
User Churn Migration Analysis with DEDICOM (RS, CO, CB), pp. 321–324.
HCIDUXU-DI-2014-GencerBZV #detection #machine learning #mobile
Detection of Churned and Retained Users with Machine Learning Methods for Mobile Applications (MG, GB, ÖZ, TV), pp. 234–245.
ICEISICEIS-v1-2014-MamcenkoG #mobile #predict #using
Customer Churn Prediction in Mobile Operator Using Combined Model (JM, JG), pp. 233–240.
ICSMEICSM-2012-DuseauDS #approach #named #visual notation
Vasco: A visual approach to explore object churn in framework-intensive applications (FD, BD, HAS), pp. 15–24.
MSRMSR-2011-GigerPG #debugging #fine-grained #predict #source code
Comparing fine-grained source code changes and code churn for bug prediction (EG, MP, HCG), pp. 83–92.
SACSAC-2011-KimPHC #adaptation #network #peer-to-peer
Adaptive link recovery scheme for structured peer-to-peer networks under churn (SK, GP, JH, YC), pp. 611–615.
FSEFSE-2010-FisherFMR #named
HI-C: diagnosing object churn in framework-based applications (MFI, LM, BGR), pp. 379–380.
SACSAC-2009-XuLQ #predict #privacy
Privacy preserving churn prediction (SX, SL, MQ), pp. 1610–1614.
OOPSLAOOPSLA-2008-ShankarAB #dynamic analysis #lightweight #named
Jolt: lightweight dynamic analysis and removal of object churn (AS, MA, RB), pp. 127–142.
SACSAC-2008-AtallaMAGA #behaviour #peer-to-peer #quality #web
Analyzing the impact of churn and malicious behavior on the quality of peer-to-peer web search (FA, DM, JMA, MAG, VA), pp. 1137–1144.
ICSEICSE-2005-NagappanB #fault #metric #predict
Use of relative code churn measures to predict system defect density (NN, TB), pp. 284–292.
ICSMEICSM-1998-MunsonE #impact analysis
Code Churn: A Measure for Estimating the Impact of Code Change (JCM, SGE), p. 24–?.
ICSMEICSM-1994-KhoshgoftaarS #maintenance #predict
Improving Code Churn Predictions During the System Test and Maintenance Phases (TMK, RMS), pp. 58–67.

Bibliography of Software Language Engineering in Generated Hypertext (BibSLEIGH) is created and maintained by Dr. Vadim Zaytsev.
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