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Dynamic Bug Triage System with Data Classification Techniques

Swapnil Pasarkar, Neha Bagal, Shilpa Nair, Kshitija Godse
2015 International Journal of Engineering Research and  
In proposed approach we are performing data reduction on bug data set which will reduce the scale of the data as well as increase the quality of the data and then apply k-NN and Support Vector Machine  ...  The goal of bug triaging is to assign potentially experienced developers to newcoming bug reports. We balance the load between developers based on their experience and past history.  ...  S.B.Ingle and Nelsoft Technologies for their valuable guidance and support in simulation and implementation of project idea.  ... 
doi:10.17577/ijertv4is110538 fatcat:sxa6gszsrvea3pmumknvlph2xi

A Survey Paper on Efficient Approach of Data Reduction Techniques for Bug Triaging System

2015 International Journal of Science and Research (IJSR)  
For bug triage data reduction techniques is used to build a small scale and high quality set of bug data by removing bug reports and words which are redundant or noninformative.  ...  Bug Triaging is an important part of testing process in software development organizations. It is process of assigning a correct developer for fixing a bug.  ...  This approach trains a classifier with a fraction of labeled bug reports.  ... 
doi:10.21275/v4i12.nov152369 fatcat:mhee4zip65hq3kvudbvy3ormb4

A Survey on Bug Triaging- Software Data Reduction Techniques

2015 International Journal of Science and Research (IJSR)  
The goal of effective bug triaging package is to assign doubtless intimate developers to new-coming bug reports to cut back time and price of bug triaging, An automatic approach is planned during this  ...  paper that predicts a developer with relevant expertise to resolve or fix the new returning bug report during this paper, the five term choice strategies on the accuracy of bug assignment square measure  ...  As a result, 70% words and 50% bug reports are removed after the training set reduction.  ... 
doi:10.21275/v4i12.nov152110 fatcat:mny2wkz36jc57jlgysblopyf3m

A Novel Approach on Towards Effective Bug Triage and Improve the Quality of Bug Data

G Praveen, V. Sridhar Reddy, Shaik Abdul Nabi
2017 International Journal of Advanced Research in Computer Science and Software Engineering  
It is practically scrutinized the enactment of data reduction on totally 600,000 bug reports of two large open source projects, namely Eclipse and Mozilla.  ...  In this scheme, it is addressed the problem of data reduction for bug triage, to reduce the scale and progress the reputation of bug data.  ...  Data reduction based on FSS Input: training set T with n words and m bug reports, reduction order FSS final number nF of words, final number mI of bug reports, Output: reduced data set T FI for bug triage  ... 
doi:10.23956/ijarcsse.v7i9.402 fatcat:2drjw6fd3bgv7lxpzl2xpzrm64

Analysis of Bug Triage using Data Preprocessing (Reduction) Techniques

G. Parthasarathy, D.C. Tomar, Blessy John
2015 International Journal of Computer Applications  
In the bug triage we have an unavoidable step of fixing the bugs which helps in correctly assigning a developer to a new bug.  ...  We address the problem of data reduction and hence we combine the instance selection and the feature selection algorithms to simultaneously reduce the data scale and enhance the accuracy of the bug reports  ...  The quality of bug triage can be measured with the accuracy of bug triage, which is defined as Accuracy k = # correctly assigned bug reports in k candidates # all bug reports in the test set Table 2 .  ... 
doi:10.5120/ijca2015903002 fatcat:7z42wpfjh5f6tibzkladoiq27u

A Technique to Combine Feature Selection with Instance Selection for Effective Bug Triage

2015 International Journal of Science and Research (IJSR)  
Software organizations spend more than 45 percent of expense in managing Software bugs. An unavoidable step of altering bugs is bug triage, which plans to accurately allot a developer to another bug.  ...  In this undertaking, we address the issue of data reduction for bug triage, i.e., how to diminish the scale and improve the nature of bug data.  ...  Before training a classifier with a bug data set, we add a phase of data reduction, in (b), which combines the techniques of instance selection and feature selection to reduce the scale of bug data.  ... 
doi:10.21275/v4i11.nov151607 fatcat:rdx2vl6zojfildmgtnchfgchtm

Domain Specific Automated Triaging System for Bug Classification

Heena Singla, Gitika Sharma, Sumit Sharma
2016 Indian Journal of Science and Technology  
The objective of this paper is to analyze and identify domain specific priority classification of bug reports.  ...  Jifeng Xuan, He Jiang 7 combined the feature selection and instance techniques which helps to reduction of data set and enhance the quality of the bug data.  ...  Particle Swam Optimization (PSO) 24 is instance based method which is used to reduces the instances of the bug reports Training and Testing Linear Discriminant Analysis (LDA) and Naive Bayes (NB) are  ... 
doi:10.17485/ijst/2016/v9i33/97891 fatcat:xe2yzxpynna4vawxt3jjaeznla

High-Dimensional Hybrid Data Reduction for Effective Bug Triage

Xin Ge, Shengjie Zheng, Jiahui Wang, Hui Li
2020 Mathematical Problems in Engineering  
To overcome these two challenges, we propose a high-dimensional hybrid data reduction method that combines feature selection with instance selection to build a small-scale and high-quality dataset of bug  ...  However, there are two challenges in bug triage: low quality of bug reports and engagement of developers.  ...  In the search process, our method first uses the training set for training and the verification set for examining to find the optimal solution results with FS, IS, and FS + IS.  ... 
doi:10.1155/2020/5102897 fatcat:g7l4yugmpbc3lmj7dk3uvs44ze

Bug Triage Using Dimensionality Reduction Technique And PSO Algorithm

S. Amritha, A.Jennifer Sagaya Rani
2016 International Journal Of Engineering And Computer Science  
To reduce time and cost of bug triaging, an automated approach is developed to predict a developer with relevant experience to solve the new coming report.  ...  The process of fixing bug is bug triage that aims to properly assign a developer to a new bug. Software companies pay out most of their expenses in dealing with these bugs.  ...  [22] propose an identical bug detection method by enhancing a recovery function on multiple features. To enhance the quality of bug reports, Breu et al.  ... 
doi:10.18535/ijecs/v5i6.12 fatcat:7a3h5zeburevxn5eckqm5bqlhm

A survey on bug-report analysis

Jie Zhang, XiaoYin Wang, Dan Hao, Bing Xie, Lu Zhang, Hong Mei
2015 Science China Information Sciences  
Lately, due to the availability of a large number of bug reports, a considerable amount of research has been carried out on bug-report analysis, such as automatically checking duplication of bug reports  ...  To review the work on bug-report analysis, this paper presents an exhaustive survey on the existing work on bug-report analysis.  ...  Feature selection is an important component of machine learning, which may facilitate training-set reduction. Zou et al.  ... 
doi:10.1007/s11432-014-5241-2 fatcat:nkopbdht6nbjrbmniorrnovc2m

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

Pamela Bhattacharya, Iulian Neamtiu, Christian R. Shelton
2012 Journal of Systems and Software  
Our work is the first to examine the impact of multiple machine learning dimensions (classifiers, attributes, and training history) along with bug tossing graphs on prediction accuracy in bug assignment  ...  Next, we perform an ablative analysis by unilaterally varying classifiers, features, and learning model to show their relative importance of on bug assignment accuracy.  ...  The optimal set of techniques we report can change with changes in data sets for the same project or across other projects, or with changes in the underlying supervised learning algorithm and we address  ... 
doi:10.1016/j.jss.2012.04.053 fatcat:cnldgcrbvzf3ne6e6h3miaukki

A Particle Swarm Optimized Learning Model of Fault Classification in Web-Apps

Deepak Kumar Jain, Akshi Kumar, Saurabh Raj Sangwan, Gia Nhu Nguyen, Prayag Tiwari
2019 IEEE Access  
In this paper, an empirical study is conducted to classify faults in bug reports of three open-source web-apps (qaManager, bitWeaver, and WebCalendar) and reviews of two play store web-apps (Dineout: Reserve  ...  The empirical analysis validates that the particle swarm optimization for feature selection in fault classification task outperforms the tf-idf filter-based classifiers with an average accuracy gain of  ...  Each word is assigned with an integer in a range of polarity from −5 up to +5, negative to positive.  ... 
doi:10.1109/access.2019.2894871 fatcat:72plppp2d5fr3dlnqxbbzcjvhm

Automatic Fine-Grained Issue Report Reclassification

Pavneet Singh Kochhar, Ferdian Thung, David Lo
2014 2014 19th International Conference on Engineering of Complex Computer Systems  
Among issue reports that are marked as bugs, more than 30% of them are not bug reports.  ...  To address this problem, in this paper we propose an automated technique that reclassifies an issue report into an appropriate category.  ...  ACKNOWLEDGEMENT We would like to thank Kim Herzig, Sascha Just, and Andreas Zeller for making their issue report datasets publicly available.  ... 
doi:10.1109/iceccs.2014.25 dblp:conf/iceccs/KochharTL14 fatcat:22yne2hxfrfk3likml3a4we2by

Identify High-Impact Bug Reports by Combining the Data Reduction and Imbalanced Learning Strategies

Shikai Guo, Miaomiao Wei, Siwen Wang, Rong Chen, Chen Guo, Hui Li, Tingting Li
2019 Applied Sciences  
In the data reduction phase, we combine feature selection with the instance selection method to build a small-scale and high-quality set of bug reports by removing the bug reports and words that are redundant  ...  To address these two challenges, we propose an approach to identify high-impact bug reports that combines the data reduction and imbalanced learning strategies.  ...  Furthermore, most of the bug reports are not high impact bug reports; in other words, the training set often has an imbalanced distribution.  ... 
doi:10.3390/app9183663 fatcat:ulr2fprznzd2ngrww3wmqwge4a

Automated Classification of Unstructured Bilingual Software Bug Reports: An Industrial Case Study Research

Ömer Köksal, Bedir Tekinerdogan
2021 Applied Sciences  
Furthermore, classification enables a fast and appropriate reaction to software bugs. However, for large-scale projects, one must deal with a broad set of bugs from multiple types.  ...  Software bug report classification is a critical process to understand the nature, implications, and causes of software failures.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app12010338 fatcat:korcuynyfrevflckq366wtjcti
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