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Automatic Unsupervised Bug Report Categorization

Nachai Limsettho, Hideaki Hata, Akito Monden, Kenichi Matsumoto
2014 2014 6th International Workshop on Empirical Software Engineering in Practice  
In categorizing bug reports study, not many researches try using unsupervised learning approach. Clustering, one of unsupervised learning is mostly only used for bug triaging.  ...  Experiment2: Categorizing bug reports in each project into Bug and Other Requests We evaluate performance in separating bug reports of the same project in this experiment.  ... 
doi:10.1109/iwesep.2014.8 dblp:conf/iwesep/LimsetthoHMM14 fatcat:zlyxf4y3iverpgxnicikvweuki

Unsupervised Bug Report Categorization Using Clustering and Labeling Algorithm

Nachai Limsettho, Hideaki Hata, Akito Monden, Kenichi Matsumoto
2016 International journal of software engineering and knowledge engineering  
Conclusion: Our framework can be used to automatically categorize the incoming bug reports without any prior knowledge, as an automated labeling suggestion system or as a tool for obtaining knowledge about  ...  Method: Our framework categorizes bug reports according to their text similarity using topic modeling and a clustering algorithm.  ...  In that paper, an almost fully automatic framework was proposed to categorize bug reports, according to their textual contents .  ... 
doi:10.1142/s0218194016500352 fatcat:5rwxiajifvempeituwsoxu6r6m


Som Gupta, Gupta S.K
2019 Indian Journal of Computer Science and Engineering  
Many researchers have done research on bug report summarization using various techniques like supervised approaches, unsupervised approaches, deep learning approach, feature-based approach.  ...  Summarization is one application on bug reports which helps solve a lot of interesting issues of bug reports like bug triaging and bug duplicate detection.  ...  Searching for an appropriate bug report is a challenging task. Automatic summarization of bug reports help search the relevant bug report quickly.  ... 
doi:10.21817/indjcse/2019/v10i6/191006041 fatcat:si2jeudqbrafpfcnxnkn2ch5ju

Automatic Keyword and Sentence based Text Summarization for Software Bug Reports

Shubhra Goyal Jindal, Arvinder Kaur
2020 IEEE Access  
INDEX TERMS Text summarization, rapid automatic keyword extraction, fuzzy c-means, hierarchical clustering, bug reports, rule engine.  ...  The objective of the proposed, unsupervised approach is to summarize bug reports (software artefacts) with complete content and diversified information.  ...  In literature, several supervised [19] - [21] and unsupervised [22] , [23] approaches have been proposed to summarize bug reports automatically.  ... 
doi:10.1109/access.2020.2985222 fatcat:vcfq6bpq25f3lnmu3x5akq765a

CaPBug -A Framework for Automatic Bug Categorization and Prioritization Using NLP and Machine Learning Algorithms

Hafiza Anisa Ahmed, Narmeen Zakaria Bawany, Jawwad Ahmed Shamsi
2021 IEEE Access  
automatic bug categorization.  ...  BUG CATEGORIZATION Bug categorization is the process of automatically labeling bug reports with its relevant category. N. Limsettho et al.  ... 
doi:10.1109/access.2021.3069248 fatcat:beamjsygknhwlas43pnz53pzlq


Ferdian Thung, Pavneet Singh Kochhar, David Lo
2014 Proceedings of the 29th ACM/IEEE international conference on Automated software engineering - ASE '14  
In this paper, we propose a tool named DupFinder, which implements the state-of-theart unsupervised duplicate bug report approach by Runeson et al., as a Bugzilla extension.  ...  Such bug reports are duplicate of each other and these duplicate bug reports need to be identified.  ...  These techniques can be categorized into two families: unsupervised and supervised. Runeson et al.  ... 
doi:10.1145/2642937.2648627 dblp:conf/kbse/ThungKL14 fatcat:4upk44e4azgi7isj4kem6ybf5e

A Literature Review of Research in Bug Resolution: Tasks, Challenges and Future Directions

Tao Zhang, He Jiang, Xiapu Luo, Alvin T.S. Chan
2015 Computer journal  
., bug report, source code and change history) in bug repositories to complete the bug resolution task. However, a mountain of submitted bug reports every day increase the developers' workload.  ...  Our investigation concerns the most important phases in bug resolution, including bug understanding, bug triage and bug fixing. Moreover, we present the advantages and disadvantages of each study.  ...  Note that [5, 6] utilized unsupervised approaches to automatically generate summaries of bug reports.  ... 
doi:10.1093/comjnl/bxv114 fatcat:r4t6kgzqi5cq7nlwuanednwkhq

Can Automated Program Repair Refine Fault Localization? [article]

Yiling Lou, Ali Ghanbari, Xia Li, Lingming Zhang, Dan Hao, Lu Zhang
2019 arXiv   pre-print
In this way,we not only open a new dimension for more powerful fault localization, but also extend the application scope of program repair to all possible bugs (not only the bugs that can be directly automatically  ...  Lastly, we show that ProFL can further boost state-of-the-art fault localization via both unsupervised and supervised learning.  ...  manual repair even for the bugs that are hard to fix automatically.  ... 
arXiv:1910.01270v1 fatcat:iuj4uouxkbgv7euj2tq3wrxuem

Summarization of Software Artifacts : A Review

Som Gupta, Gupta S.K
2017 International Journal of Computer Science & Information Technology (IJCSIT)  
reports detection, traceability link recovery, etc.  ...  of research among the software engineering community due to the benefits that summarization provides like saving of time and efforts in various software engineering tasks like code search, duplicate bug  ...  [4] proposed unsupervised bug report summarization to facilitate the bug reports digestion.  ... 
doi:10.5121/ijcsit.2017.9512 fatcat:4unydg54tbh6ji7hstvixyfrsm

Mining Software Repositories for Defect Categorization

Sakthi Kumaresh, Ramachandran Baskaran
2015 Journal of Communications Software and Systems  
Categorizing bugs based on their characteristics helps the Software Development team take appropriate actions to reduce similar defects that might get reported in future releases.  ...  Therefore, the need of automatic classification of software defect is high.This work attempts to categorize defects by proposing an algorithm called Software Defect CLustering (SDCL).  ...  An approach to automatically identify the duplicate bug reports in the software bug repositories is proposed by Jalbert and Weimer [1] .  ... 
doi:10.24138/jcomss.v11i1.115 fatcat:wfoncxndxfafbjcvjr2v5tesy4

Does bug report summarization help in enhancing the accuracy of bug severity classification?

Ashima Kukkar, Rajni Mohana, Yugal Kumar
2020 Procedia Computer Science  
The programmer cannot write a program without any bug. A large numbers of bugs are deposited into the bug tracking system through bug reports.  ...  A large numbers of bugs are deposited into the bug tracking system through bug reports. To find the root cause of a bug, a meaningful and huge conversation happens between the developer and reporter.  ...  Proposed Model The problem of automatic bug report summarization is described as unsupervised algorithm whereas severity classification is illustrated as the supervised classification algorithm.  ... 
doi:10.1016/j.procs.2020.03.345 fatcat:5vrsfkjywnaf7l3uv2otuc26ne

Automatic clustering of bug reports

Maen Hammad, Ruba Alzyoudi, Ahmed Fawzi Otoom
2018 International Journal of Advanced Computer Research  
This paper proposes an automated technique to identify related previous change requests stored in bug reports. The technique is based on clustering bug reports based on their textual similarities.  ...  The result of the clustering is disjoint clusters of related bug reports that have common issues, topic or feature.  ...  Textual information is automatically extracted and preprocessed from bug reports, automatically clustered, and tags are automatically extracted.  ... 
doi:10.19101/ijacr.2018.839013 fatcat:5idduf6iljgrljdus4ll44v5su

A Survey on Data Reduction Techniques of Bug Triage

2017 International Journal of Modern Trends in Engineering & Research  
Finally, relying on heavy-weight mechanisms to obtain provable redundant bug report.  ...  We have to prevent redundant bug in the repository. We introduce novel alternative that provides significantly-improved bug report.  ...  The technique generates tests automatically, runs the tests capturing logical constraints on inputs, and minimizes the conditions on the inputs to failing tests so that the resulting bug reports are small  ... 
doi:10.21884/ijmter.2017.4139.zi5uf fatcat:ngbjsirmuja2jmmgg25ym5pfna

Harvesting Fix Hints in the History of Bugs [article]

Tegawendé F. Bissyandé
2015 arXiv   pre-print
In our approach, once a bug is reported, it is automatically compared to all previously fixed bugs using information retrieval techniques and machine learning classification.  ...  We build on the assumption that bugs, and the associated user bug reports, are repetitive and propose a new approach of fix recommendations based on the history of bugs and their associated fixes.  ...  build SVM classifiers for categorizing new bug reports in those categories.  ... 
arXiv:1507.05742v1 fatcat:sjj3cb7sjffirjeaq2p26x5sqe

Early Detection of Security-Relevant Bug Reports using Machine Learning: How Far Are We? [article]

Arthur D. Sawadogo, Quentin Guimard, Tegawendé F. Bissyandé, Abdoul Kader Kaboré, Jacques Klein, Naouel Moha
2021 arXiv   pre-print
Bug reports are common artefacts in software development.  ...  To support practitioners in triaging bug reports, the research community has proposed a number of approaches for the detection of security-relevant bug reports.  ...  Security-relevant bug reports can be categorized as Hidden Impact Bugs [5] : the bugs are often only identified as vulnerabilities long after they have been made public.  ... 
arXiv:2112.10123v1 fatcat:a622vvcrwrhnbh2b5ues6cirjq
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