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Predicting Bug severity using Classification on Clustered Bugs Data

Rajalakshmi R, Dhanya PM
2016 International Journal of Advanced Research  
Algorithm Steps:-1) Initially assume random assignment of bug instances to different bug severity categories. 2) Learn an initial probabilistic model by estimating model parameters from this randomly labelled  ...  Bug repository is a kind of repository which handles software bugs. Bug triage, an important step for bug fixing, is to assign a new bug to a relevant developer for further handling.  ...  1312 The approach used here can be extended to other classification and clustering algorithms with other types of data.  ... 
doi:10.21474/ijar01/1331 fatcat:5nkzswdomrh7zimepuxdngaqnu

Learning Tractable Probabilistic Models for Fault Localization [article]

Aniruddh Nath, Pedro Domingos
2015 arXiv   pre-print
However, most existing probabilistic debugging systems use relatively simple statistical models, and fail to generalize across multiple programs.  ...  In this work, we propose Tractable Fault Localization Models (TFLMs) that can be learned from data, and probabilistically infer the location of the bug.  ...  The model predicts the buggy attribute, using the TARANTULA score and a bias term as features.  ... 
arXiv:1507.01698v1 fatcat:hiresn5jwreofbvpvfiyjv2cw4

Where Should We Fix This Bug? A Two-Phase Recommendation Model

Dongsun Kim, Yida Tao, Sunghun Kim, Andreas Zeller
2013 IEEE Transactions on Software Engineering  
To support developers in debugging and locating bugs, we propose a two-phase prediction model that uses bug reports' contents to suggest the files likely to be fixed.  ...  If so, the model proceeds to predict files to be fixed, based on the content of the bug report.  ...  This observation motivates us to propose a twophase model where we first check whether a bug report is "predictable" and only if it is "predictable" do we proceed to predict a fix location; otherwise,  ... 
doi:10.1109/tse.2013.24 fatcat:rwgk4pu67nd3hf37i5xol7awoa

Software Analysis, Evolution, and Reengineering, and ICT Sustainability

Jeffrey Carver, Birgit Penzenstadler, Alexander Serebrenik
2018 IEEE Software  
In "Using a Probabilistic Model to Predict Bug Fixes," Mauricio Soto and Claire Le Goues analyze and classify an extensive body of bug-fixing commits (the 100 most recent from 500 of the most popular Java  ...  "Re-evaluating Method-Level Bug Prediction," by Luca Pascarella and his colleagues, describes a replication of prior research on methodlevel bug prediction. 1 The authors applied the metrics used in  ... 
doi:10.1109/ms.2018.2801553 fatcat:iw45lhhltjbcpmyknfsxi4zdmi

CODIT: Code Editing with Tree-Based Neural Models [article]

Saikat Chakraborty, Yangruibo Ding, Miltiadis Allamanis, Baishakhi Ray
2020 arXiv   pre-print
CODIT can also learn specific bug fix pattern from bug fixing patches and can fix 25 bugs out of 80 bugs in Defects4J.  ...  The way developers edit day-to-day code tends to be repetitive, often using existing code elements.  ...  Moreover, bug fixing patterns are numerous and highly dependent on the bug context and the bug type, so a single pre-trained model may only have the power to fix certain kinds of bugs and miss the others  ... 
arXiv:1810.00314v3 fatcat:jt4ihvprijevnm5iwnoo34f5pa

Repairing Deep Neural Networks: Fix Patterns and Challenges [article]

Md Johirul Islam, Rangeet Pan, Giang Nguyen, Hridesh Rajan
2020 arXiv   pre-print
bug fixes have the potential to introduce adversarial vulnerabilities; DNN bug fixes frequently introduce new bugs; and DNN bug localization, reuse of trained model, and coping with frequent releases  ...  Which repair patterns should be assigned a higher priority for building automated bug repair tools? This work presents a comprehensive study of bug fix patterns to address these questions.  ...  We do not find any evidence of other bug fix strategies in DNN and that has inspired us to derive a classification scheme using the open coding approach to classify the DNN bug fix patterns.  ... 
arXiv:2005.00972v1 fatcat:ecmsf2ega5f6ziueujpsurcskm

Source Code Retrieval for Bug Localization Using Latent Dirichlet Allocation

Stacy K. Lukins, Nicholas A. Kraft, Letha H. Etzkorn
2008 2008 15th Working Conference on Reverse Engineering  
In bug localization, a developer uses information about a bug to locate the portion of the source code to modify to correct the bug. Developers expend considerable effort performing this task.  ...  (LDA), a modular and extensible IR model, has significant advantages over both LSI and probabilistic LSI (pLSI).  ...  Latent Dirichlet allocation (LDA) is a probabilistic and fully generative topic model that is used to extract the latent, or hidden, topics present in a collection of documents and to model each document  ... 
doi:10.1109/wcre.2008.33 dblp:conf/wcre/LukinsKE08 fatcat:7onwkx5cqrhx7gkvopnh2hqasu

An Approach for Predicting Bug Triage using Data Reduction Methods

ShanthiPriya Duraisamy, Laxmi Raja, KalaiSelvi Kandaswamy
2017 International Journal of Computer Applications  
Predictive model is used to determine the order of reduction techniques for a new bug data set, i.e., to choose between FS to IS or IS to FS.  ...  To decrease the manual and time cost, text classification techniques are applied to accomplish automatic bug triage approach aims to precisely predict the developer to solve or fix the new bug report.  ...  A Predictive model is used to determine the order of applying reduction order, i.e., FS to IS or IS to FS. The proposed system performance is verified using Mozilla bug data set.  ... 
doi:10.5120/ijca2017915748 fatcat:yfmigdrxired5p7gk7zg7uzuju

Where is bug resolution knowledge stored?

Gerardo Canfora, Luigi Cerulo
2006 Proceedings of the 2006 international workshop on Mining software repositories - MSR '06  
This relationship reveals useful to predict code entities impacted by a new bug report.  ...  A common practice is to reference source code changes resolving a bug stored in Bugzilla by inserting the id number of the bug in the CVS commit notes.  ...  The similarity between descriptors is computed by using a probabilistic model that assumes that each term is associated with a topic, and that a document may be about the topic, or not [5] .  ... 
doi:10.1145/1137983.1138032 dblp:conf/msr/CanforaC06a fatcat:kucjyzxowjeepduhqi2oqqj5zm

Improving bug fix-time prediction model by filtering out outliers

W. AbdelMoez, Mohamed Kholief, Fayrouz M. Elsalmy
2013 2013 The International Conference on Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE)  
Bug fix time prediction models have been used to predict the fix-time of newly reported bugs in order to help out the developer during the triaging process by prioritizing which bugs to fix first.  ...  For example, conspicuous bugs are those taking less than a few minutes to get fixed. Also, there are other bugs that take years to get fixed.  ...  Also, we would like to thank Dr. Emanuel Giger and Dr. Ahmed lamkanfi for all their help and support.  ... 
doi:10.1109/taeece.2013.6557301 fatcat:r6naifft2ff4zc2ar5ificojde

A Comparative Analysis of Open Source Software Reliability

Cobra Rahmani, Azad Azadmanesh, Lotfi Najjar
2010 Journal of Software  
The purpose of this study is to compare the fitting (goodness-of-fit) and prediction capabilities of three reliability models using the failure data of five popular open source software (OSS) products.  ...  Prediction is accomplished by estimating the models parameters based on partial failure history and then applying the estimates to the entire time span for which failure data is collected.  ...  But the failure pattern can be used as a simple way to decide on some models believed to provide a decent prediction. The three models, i.e.  ... 
doi:10.4304/jsw.5.12.1384-1394 fatcat:od73sron5zdnljgdbsila4tga4

Mining Co-location Relationships among Bug Reports to Localize Fault-Prone Modules

Ing-Xiang CHEN, Chien-Hung LI, Cheng-Zen YANG
2010 IEICE transactions on information and systems  
In our approach, the colocation relationships among bug reports are explored to improve the prediction accuracy of a state-of-the-art learning method.  ...  In this paper, we propose a reactive approach which considers only bug report information and historical revision logs.  ...  Acknowledgments The authors would like to express many thanks to the anonymous reviewers for their precious suggestions and the National Science Council of the Republic of China, Taiwan, for supporting  ... 
doi:10.1587/transinf.e93.d.1154 fatcat:xdzq5s2j2nfy5p57lolyrxifau

Automated, highly-accurate, bug assignment using machine learning and tossing graphs

Pamela Bhattacharya, Iulian Neamtiu, Christian R. Shelton
2012 Journal of Systems and Software  
To redress this situation, in this paper we employ a comprehensive set of machine learning tools and a probabilistic graph-based model (bug tossing graphs) that lead to highly-accurate predictions, and  ...  Prior work has used machine learning techniques to automate bug assignment but has employed a narrow band of tools which can be ineffective in large, longlived software projects.  ...  A Bayesian Network [21] is a probabilistic model that is used to represent a set of random variables and their conditional dependencies by using a directed acyclic graph (DAG).  ... 
doi:10.1016/j.jss.2012.04.053 fatcat:cnldgcrbvzf3ne6e6h3miaukki

Diagnosis of Subtraction Bugs Using Bayesian Networks

Jihyun Lee, James E. Corter
2010 Applied Psychological Measurement  
This study addresses this problem by proposing and evaluating a probability-based approach to the diagnosis of bugs in children's multicolumn subtraction performance using Bayesian networks.  ...  Prediction is best with the most complex network (bug and subskill nodes, diagnostic use of specific wrong answers), for which the correct diagnosis rate reaches 99%.  ...  without using a modeling sample to estimate the cut points.  ... 
doi:10.1177/0146621610377079 fatcat:7g3plb6gsffend4ohlhjwhxnie

A Survey of Machine Learning for Big Code and Naturalness

Miltiadis Allamanis, Earl T. Barr, Premkumar Devanbu, Charles Sutton
2018 ACM Computing Surveys  
We present a taxonomy based on the underlying design principles of each model and use it to navigate the literature.  ...  We contrast programming languages against natural languages and discuss how these similarities and differences drive the design of probabilistic models.  ...  [199] use traces for statistical bug isolation. Kremenek et al. [108] learn factor graphs (structured prediction) to model resource-specific bugs by modeling resource usage specifications.  ... 
doi:10.1145/3212695 fatcat:iuuocyctg5adjmobhc2zw23rfu
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