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Network Versus Code Metrics to Predict Defects: A Replication Study

Rahul Premraj, Kim Herzig
2011 2011 International Symposium on Empirical Software Engineering and Measurement  
Several defect prediction models have been proposed to identify which entities in a software system are likely to have defects before its release.  ...  However, when we evaluated the metrics using setups more suited for industrial use -forward-release and cross-project prediction -we found network metrics to offer no vantage over code metrics.  ...  Cross-project prediction setup (RQ3) The cross prediction setup entails using data from a release of one project to identify defect-prone entities in a release from another project.  ... 
doi:10.1109/esem.2011.30 dblp:conf/esem/PremrajH11 fatcat:bftx24i5ivdeldq5j7eo5l2dbi

Local versus Global Models for Just-In-Time Software Defect Prediction

Xingguang Yang, Huiqun Yu, Guisheng Fan, Kai Shi, Liqiong Chen
2019 Scientific Programming  
To this end, we compare the performance of local and global models through a large-scale empirical study based on six open-source projects with 227417 changes.  ...  However, local models have significantly better effort-aware prediction performance than global models in the cross-validation and cross-project-validation scenarios.  ...  vs. global models in the cross-project-validation scenario.  ... 
doi:10.1155/2019/2384706 fatcat:ovxwz5hgrfb4faxnhnxv7eghwq

File-Level Defect Prediction: Unsupervised vs. Supervised Models

Meng Yan, Yicheng Fang, David Lo, Xin Xia, Xiaohong Zhang
2017 2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)  
s study on PROMISE dataset with totally ten projects. We compare the effectiveness of unsupervised and supervised prediction models for effort-aware file-level defect prediction.  ...  Results: We find that the conclusion of Yang et al. [1] does not hold under within-project but holds under cross-project setting for file-level defect prediction.  ...  ., LOC) used as proxy of effort in defect prediction. Mezouar et al. [33] compare local and global effortaware defect prediction models. Recently, Yang et al.  ... 
doi:10.1109/esem.2017.48 dblp:conf/esem/YanFLXZ17 fatcat:uornp5rbv5amxpf6e5ozymqalm

Bayesian hierarchical modelling for tailoring metric thresholds

Neil A. Ernst
2018 Proceedings of the 15th International Conference on Mining Software Repositories - MSR '18  
A key research challenge is to construct locally accurate prediction models that are informed by global characteristics and data volumes.  ...  This paper applies a simpler approach known as Bayesian hierarchical modeling. We show that hierarchical modeling supports cross-project comparisons, while preserving local context.  ...  ACKNOWLEDGEMENTS We are grateful to the authors of [7] , who made their well-packaged and documented data and code available for others.  ... 
doi:10.1145/3196398.3196443 dblp:conf/msr/Ernst08 fatcat:inyabw7jc5flhd4pqxneo63q5y

Recalling the "imprecision" of cross-project defect prediction

Foyzur Rahman, Daryl Posnett, Premkumar Devanbu
2012 Proceedings of the ACM SIGSOFT 20th International Symposium on the Foundations of Software Engineering - FSE '12  
Thus, we argue that measures based on a variety of tradeoffs, viz., 5%, 10% or 20% of files tested/inspected would be more suitable. We study cross-project defect prediction from this perspective.  ...  Since most new projects don't have historical data, there is interest in cross-project prediction: using data from one project to predict defects in another.  ...  Moreover, conclusions from local models are typically superior and more insightful than global models. He et al. [10] sought the "empirical ceiling" of cross-project defect prediction performance.  ... 
doi:10.1145/2393596.2393669 dblp:conf/sigsoft/RahmanPD12 fatcat:l2ywfzdn4vdwrnejhanq7h3una

Defect prediction as a multiobjective optimization problem

Gerardo Canfora, Andrea De Lucia, Massimiliano Di Penta, Rocco Oliveto, Annibale Panichella, Sebastiano Panichella
2015 Software testing, verification & reliability  
Also, MODEP outperforms an alternative approach for cross-project prediction, based on local prediction upon clusters of similar classes.  ...  In this paper we formalize the defect prediction problem as a multi-objective optimization problem.  ...  For this reason, they proposed a "local prediction" that could be applied to perform cross-project or within-project defect prediction.  ... 
doi:10.1002/stvr.1570 fatcat:h2lpci2kxra3njfd6km3whvobe

Think locally, act globally: Improving defect and effort prediction models

N. Bettenburg, M. Nagappan, A. E. Hassan
2012 2012 9th IEEE Working Conference on Mining Software Repositories (MSR)  
Last, we build a global model that takes into account local characteristics of the data. We evaluate the performance of these three approaches in a case study on two defect and two effort datasets.  ...  We find that for both types of data, local models show a significantly increased fit to the data compared to global models.  ...  repository under http://sailhome.cs. queensu.ca/replication/local-vs-global/.  ... 
doi:10.1109/msr.2012.6224300 dblp:conf/msr/BettenburgNH12 fatcat:lf3nnqhs75annbhosqspuc2gza

Local versus Global Lessons for Defect Prediction and Effort Estimation

Tim Menzies, Andrew Butcher, David Cok, Andrian Marcus, Lucas Layman, Forrest Shull, Burak Turhan, Thomas Zimmermann
2013 IEEE Transactions on Software Engineering  
This paper aims to comparatively evaluate local vs. global lessons learned for effort estimation and defect prediction.  ...  Existing research is unclear on how to generate lessons learned for defect prediction and effort estimation.  ...  MacDonell and Shepperd [43] also performed a review on the value of local vs. global effort estimation models through a replication of [42] .  ... 
doi:10.1109/tse.2012.83 fatcat:7eznmqvkfjetpjpwt4soylpdli

Supplemental Material: Instantiation of the Proposed Template in the multiple-case studies and References of the Related Work [article]

Anonymous
2021 Zenodo  
Paper: A model–based approach for specifying changes in replicationsof controlled experiments using templates and patterns.  ...  Supplemental Material: Instantiation of the Proposed Template in the multiple-case studies and References of the Related Work.  ...  ., TRAUTSCB, A., AND GRABOWSKI, J. Global vs. local models for cross-project defect prediction: A replication study.  ... 
doi:10.5281/zenodo.4739781 fatcat:32xiuiwtdbhozgwjrkbl3fhs2i

Supplemental Material: Instantiation of the Proposed Template in the multiple-case studies and References of the Related Work [article]

Anonymous
2021 Zenodo  
Paper: A model–based approach for specifying changes in replicationsof controlled experiments using templates and patterns.  ...  Supplemental Material: Instantiation of the Proposed Template in the multiple-case studies and References of the Related Work.  ...  ., TRAUTSCB, A., AND GRABOWSKI, J. Global vs. local models for cross-project defect prediction: A replication study.  ... 
doi:10.5281/zenodo.4739780 fatcat:drus3koqezawfjnxvvjxs7xagy

Supplemental Material: Instantiation of the Proposed Template in the multiple-case studies and References of the Related Work [article]

Anonymous
2021 Zenodo  
Paper: Using tem plates and patterns to specify changes in replications of controlled experiments.  ...  Supplemental Material: Instantiation of the Proposed Template in the multiple-case studies and References of the Related Work.  ...  ., TRAUTSCB, A., AND GRABOWSKI, J. Global vs. local models for cross-project defect prediction: A replication study.  ... 
doi:10.5281/zenodo.4739226 fatcat:slsxszxxz5ciplxshpmdkqrwua

An empirical study of just-in-time defect prediction using cross-project models

Takafumi Fukushima, Yasutaka Kamei, Shane McIntosh, Kazuhiro Yamashita, Naoyasu Ubayashi
2014 Proceedings of the 11th Working Conference on Mining Software Repositories - MSR 2014  
Our findings empirically confirm that JIT cross-project models learned using other projects are a viable solution for projects with little historical data.  ...  Through a case study on 11 open source projects, we find that in a JIT cross-project context: (1) high performance within-project models rarely perform well; (2) models trained on projects that have similar  ...  [20] comparatively evaluate local (withinproject) vs. global (cross-project) lessons learned for defect prediction.  ... 
doi:10.1145/2597073.2597075 dblp:conf/msr/FukushimaKMYU14 fatcat:557zxvnxdjdlrcqqtakzqczun4

Revisiting Heterogeneous Defect Prediction: How Far Are We? [article]

Xiang Chen, Yanzhou Mu, Chao Ni, Zhanqi Cui
2019 arXiv   pre-print
The above empirical results implicate there is still a long way for heterogeneous defect prediction to go.  ...  In this article, we perform a replication study to have a holistic look in this issue. In particular, we compare state-of-the-art five HDP methods with five unsupervised methods.  ...  the related work for cross-project defect prediction, including heterogeneous defect prediction studied in our study.  ... 
arXiv:1908.06560v1 fatcat:ocx47kcftbckvd6a66ppfl2e2i

Towards improving statistical modeling of software engineering data: think locally, act globally!

Nicolas Bettenburg, Meiyappan Nagappan, Ahmed E. Hassan
2014 Empirical Software Engineering  
For example, our case study on social data shows no advantage of local over global modeling, as clustering fails to derive appropriate subsets.  ...  Our case study on a variety of SE datasets demonstrates that such local models can significantly outperform traditional models with respect to model fit and predictive performance.  ...  /replication/local-vs-global-emse/.  ... 
doi:10.1007/s10664-013-9292-6 fatcat:b7qsfrf27vdu3e27akcgawaeqq

Class level fault prediction using software clustering

Giuseppe Scanniello, Carmine Gravino, Andrian Marcus, Tim Menzies
2013 2013 28th IEEE/ACM International Conference on Automated Software Engineering (ASE)  
Defect prediction approaches use software metrics and fault data to learn which software properties associate with faults in classes.  ...  Existing techniques predict fault-prone classes in the same release (intra) or in a subsequent releases (inter) of a subject software system.  ...  Special thanks are due to Alex-Cyrille Ngonga Ngomo for his support with BorderFlow clustering algorithm.  ... 
doi:10.1109/ase.2013.6693126 dblp:conf/kbse/ScannielloGMM13 fatcat:2fkvmxqnlfgpdd433yl2pbenxm
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