Stem prone$ (all stems)

58 papers:

ICSME-2015-MondalRS #case study #comparative

A comparative study on the bug-proneness of different types of code clones (MM, CKR, KAS), pp. 91–100.

SANER-2015-OyetoyanFDJ #dependence #empirical

Circular dependencies and change-proneness: An empirical study (TDO, JRF, JD, KJ), pp. 241–250.

SEKE-2015-Murillo-MoreraJ #algorithm #approach #framework #learning #predict #search-based #using

A Software Defect-Proneness Prediction Framework: A new approach using genetic algorithms to generate learning schemes (JMM, MJ), pp. 445–450.

SEKE-2015-WangCMCX #empirical #python

An empirical study on the impact of Python dynamic features on change-proneness (BW, LC, WM, ZC, BX), pp. 134–139.

ASPLOS-2015-YetimMM #communication #execution #fault #named #parallel

CommGuard: Mitigating Communication Errors in Error-Prone Parallel Execution (YY, SM, MM), pp. 311–323.

CSMR-WCRE-2014-XieKZK #empirical #migration

An empirical study on the fault-proneness of clone migration in clone genealogies (SX, FK, YZ, IK), pp. 94–103.

ICPC-2014-HossenKP #maintenance #source code

Amalgamating source code authors, maintainers, and change proneness to triage change requests (KH, HHK, DP), pp. 130–141.

SEKE-2014-YangWSFC #analysis #debugging #fault

Bug Inducing Analysis to Prevent Fault Prone Bug Fixes (HY, CW, QS, YF, ZC), pp. 620–625.

DATE-2013-YetimMM #streaming

Extracting useful computation from error-prone processors for streaming applications (YY, MM, SM), pp. 202–207.

DRR-2013-Nagy #documentation #fault #image #preprocessor

Preprocessing document images by resampling is error prone and unnecessary (GN).

CSMR-2013-JaafarHGHA #empirical #evolution #on the

On the Relationship between Program Evolution and Fault-Proneness: An Empirical Study (FJ, SH, YGG, SH, BA), pp. 15–24.

ICSM-2013-OyetoyanCC #component #question #refactoring

Can Refactoring Cyclic Dependent Components Reduce Defect-Proneness? (TDO, DSC, RC), pp. 420–423.

MSR-2013-XieKZ #empirical #migration

An empirical study of the fault-proneness of clone mutation and clone migration (SX, FK, YZ), pp. 149–158.

WCRE-2013-JaafarGHK #anti #dependence #mining

Mining the relationship between anti-patterns dependencies and fault-proneness (FJ, YGG, SH, FK), pp. 351–360.

ICEIS-J-2013-LiL13a #object-oriented #predict

Bayesian Prediction of Fault-Proneness of Agile-Developed Object-Oriented System (LL, HL), pp. 209–225.

ICEIS-v2-2013-LiL #agile #network #object-oriented #predict #process #using

Predicting Fault-proneness of Object-Oriented System Developed with Agile Process using Learned Bayesian Network (LL, HL), pp. 5–16.

ESEC-FSE-2013-VasquezBBPOP #android #api #fault

API change and fault proneness: a threat to the success of Android apps (MLV, GB, CBC, MDP, RO, DP), pp. 477–487.

ICSE-2013-Romano #industrial #perspective

Analyzing the change-proneness of service-oriented systems from an industrial perspective (DR), pp. 1365–1368.

LCTES-2013-StilkerichSEHLSS #embedded #virtual machine

A JVM for soft-error-prone embedded systems (IS, MS, CE, MH, DL, FS, WSP), pp. 21–32.

CSMR-2012-Izquierdo-Cortazar #comprehension #debugging #distributed #process

Global and Geographically Distributed Work Teams: Understanding the Bug Fixing Process and Potentially Bug-prone Activity Patterns (DIC), pp. 505–508.

WCRE-2012-RomanoRPK #fine-grained #source code #using

Analyzing the Impact of Antipatterns on Change-Proneness Using Fine-Grained Source Code Changes (DR, PR, MP, FK), pp. 437–446.

SAC-2012-DestefanisTCM #analysis #anti #java #scalability

An analysis of anti-micro-patterns effects on fault-proneness in large Java systems (GD, RT, GC, MM), pp. 1251–1253.

HPCA-2012-AwasthiSSRBS #performance

Efficient scrub mechanisms for error-prone emerging memories (MA, MS, KS, BR, RB, VS), pp. 15–26.

DATE-2011-FerreiraBCMM #algorithm #process

Impact of process variation on endurance algorithms for wear-prone memories (APF, SB, BRC, RGM, DM), pp. 962–967.

ICSM-2011-RomanoP #interface #java #metric #predict #source code #using

Using source code metrics to predict change-prone Java interfaces (DR, MP), pp. 303–312.

SCAM-2011-MarinescuM #fault #question

Are the Clients of Flawed Classes (Also) Defect Prone? (RM, CM), pp. 65–74.

FASE-2010-BacchelliDL #fault #question

Are Popular Classes More Defect Prone? (AB, MD, ML), pp. 59–73.

FASE-2010-XiaoOWL #development #scheduling

Dynamic Resource Scheduling in Disruption-Prone Software Development Environments (JX, LJO, QW, ML), pp. 107–122.

ICSM-2010-ArnaoudovaEOGA #concept #fault #identifier #metric #physics

Physical and conceptual identifier dispersion: Measures and relation to fault proneness (VA, LME, RO, YGG, GA), pp. 1–5.

MSR-2010-NugrohoCA #design #java #metric #predict #uml

Assessing UML design metrics for predicting fault-prone classes in a Java system (AN, MRVC, EA), pp. 21–30.

STOC-2010-DuanP #graph

Connectivity oracles for failure prone graphs (RD, SP), pp. 465–474.

SEKE-2010-AlhassanCB #analysis #fault #network #people #social

Do More People Make the Code More Defect Prone?: Social Network Analysis in OSS Projects (SA, BC, ABB), pp. 93–98.

ICSE-2010-FerrariBLGFCLTSSRMBM #aspect-oriented #case study #evolution #source code

An exploratory study of fault-proneness in evolving aspect-oriented programs (FCF, RB, OALL, AG, EF, NC, FL, NT, LS, SS, AR, PCM, TVB, JCM), pp. 65–74.

WCRE-1999-GatrellCH99a #c# #design pattern #replication #using

Design Patterns and Change Proneness: A Replication Using Proprietary C# Software (MG, SC, TH), pp. 160–164.

WCRE-1999-KhomhPG99a #case study #smell

An Exploratory Study of the Impact of Code Smells on Software Change-proneness (FK, MDP, YGG), pp. 75–84.

ICST-2009-GegickRW #component #predict

Predicting Attack-prone Components (MG, PR, LAW), pp. 181–190.

ICSM-2008-PentaCGA #design pattern #empirical

An empirical study of the relationships between design pattern roles and class change proneness (MDP, LC, YGG, GA), pp. 217–226.

MSR-2008-HataMK #precise #using

An extension of fault-prone filtering using precise training and a dynamic threshold (HH, OM, TK), pp. 89–98.

ICPR-2008-WangYS #statistics

Matching colonic polyps from prone and supine CT colonography scans based on statistical curvature information (SW, JY, RMS), pp. 1–4.

SEKE-2008-KhoshgoftaarSD #knowledge-based #modelling #on the #quality

On the Rarity of Fault-prone Modules in Knowledge-based Software Quality Modeling (TMK, NS, DJD), pp. 279–284.

MSR-2007-MizunoINK #approach

Spam Filter Based Approach for Finding Fault-Prone Software Modules (OM, SI, SN, TK), p. 4.

ESEC-FSE-2007-MizunoK #detection #empirical #fault

Training on errors experiment to detect fault-prone software modules by spam filter (OM, TK), pp. 405–414.

ISSTA-2007-OstrandWB #algorithm #automation #identification

Automating algorithms for the identification of fault-prone files (TJO, EJW, RMB), pp. 219–227.

MSR-2006-WeissgerberD #question #refactoring

Are refactorings less error-prone than other changes? (PW, SD), pp. 112–118.

CASE-2005-WangCL #capacity #robust #using

Using shared resource capacity for robust control of failure prone manufacturing systems (SW, SFC, MAL), pp. 369–374.

DAC-2005-ZykovMJVS #architecture #novel #performance #trade-off

High performance computing on fault-prone nanotechnologies: novel microarchitecture techniques exploiting reliability-delay trade-offs (AVZ, EM, MFJ, GdV, AS), pp. 270–273.

ASE-2003-GuoCS #fault #network #predict

Predicting Fault Prone Modules by the Dempster-Shafer Belief Networks (LG, BC, HS), pp. 249–252.

IWPC-2003-BiemanAY #comprehension #object-oriented #visualisation

Understanding Change-Proneness in OO Software through Visualization (JMB, AAA, HJY), pp. 44–53.

CSMR-2002-YuSM #case study #industrial #metric #object-oriented #predict #using

Predicting Fault-Proneness using OO Metrics: An Industrial Case Study (PY, TS, HAM), pp. 99–107.

SEKE-2002-DenaroMP #modelling

Deriving models of software fault-proneness (GD, SM, MP), pp. 361–368.

ICSE-2002-DenaroP #empirical #evaluation #modelling

An empirical evaluation of fault-proneness models (GD, MP), pp. 241–251.

CSMR-2001-FioravantiN #case study #detection #object-oriented

A Study on Fault-Proneness Detection of Object-Oriented Systems (FF, PN), pp. 121–130.

ICSE-2000-Denaro #process #testing

Estimating software fault-proneness for tuning testing activities (GD), pp. 704–706.

CSMR-1998-HongK #empirical #fault #identification

Identifying Fault Prone Modules: An Empirical Study in Telecommunication System (SH, KK), pp. 179–184.

CSMR-1997-Michael #constraints #evolution #using

Using evolution constraints to assess the failure-proneness of evolving software (CCM), pp. 48–53.

ICSM-1996-KhoshgoftaarAHT #detection #lifecycle

Detection of Fault-Prone Software Modules During a Spiral Life Cycle (TMK, EBA, RH, GPT), pp. 69–76.

SEKE-1995-LanubileLV #component #identification #modelling

Comparing models for identifying fault-prone software components (FL, AL, GV), pp. 312–319.

AdaEurope-1993-BundyM #ada #exception #scalability

Error-Prone Exception Handling in Large Ada Systems (GNB, DEM), pp. 153–170.