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Descriptions of issues and comments for predicting issue success in software projects

Sandra L. Ramírez-Mora, Hanna Oktaba, Helena Gómez-Adorno
2020 Journal of Systems and Software  
The results provided evidence that descriptions of issues and comments are useful for predicting issue success with more than 85% of accuracy and precision, and that the predictions of issue success vary  ...  This work studies the usefulness of textual descriptions of issues and comments for predicting whether issues will be resolved successfully or not.  ...  Are textual descriptions of issues and comments from Jira ITSs useful to predict issue success in software projects?  ... 
doi:10.1016/j.jss.2020.110663 fatcat:zovzss64wzawhm4srw34s5gamy

Empirical validation of human factors in predicting issue lead time in open source projects

Nguyen Duc Anh, Daniela S. Cruzes, Reidar Conradi, Claudia Ayala
2011 Proceedings of the 7th International Conference on Predictive Models in Software Engineering - Promise '11  
Classification or prediction of issue lead time is useful for prioritizing evolution issues and supporting human resources allocation in software maintenance.  ...  Correlation analysis confirms the effectiveness of collaboration measures, such as the number of stakeholders and number of comments, in prediction models.  ...  There are many issues which have empty parts of descriptions while the main informative descriptions lie in the issue titles and are further explored in comments on the issue.  ... 
doi:10.1145/2020390.2020403 dblp:conf/promise/AnhCCA11 fatcat:u6gmjvpfgrf65hkiqzhv3dav6m

Who Cares About My Feature Request? [chapter]

Lukas Heppler, Remo Eckert, Matthias Stuermer
2016 IFIP Advances in Information and Communication Technology  
This study examines if there is any difference between requests of the IBM developer community and other sources in terms of the likelihood of successful implementation.  ...  Previous studies on issue tracking systems for open source software (OSS) focused mainly on requests for bug fixes.  ...  description (in 100 chars) 5.62 4.69 5.76 5.73 (12.70) (7.63) (11.84) (14.09) Table 2 . 2 Summary for Logistic Regression Analysis for variables predicting success of a feature request  ... 
doi:10.1007/978-3-319-39225-7_7 fatcat:xreletv5ancibjya3lfhg3iaxi

Characterization and Prediction of Issue-Related Risks in Software Projects

Morakot Choetkiertikul, Hoa Khanh Dam, Truyen Tran, Aditya Ghose
2015 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories  
Identifying risks relevant to a software project and planning measures to deal with them are critical to the success of the project.  ...  A set of risk factors characterizing "risky" software tasks (in the form of issues) were extracted from five open source projects: Apache, Duraspace, JBoss, Moodle, and Spring.  ...  planning, which is crucial for project success.  ... 
doi:10.1109/msr.2015.33 dblp:conf/msr/ChoetkiertikulD15 fatcat:b4cmybw2urg7jii6l2sqjxomqi

Predicting the Objective and Priority of Issue Reports in Software Repositories [article]

Maliheh Izadi, Kiana Akbari, Abbas Heydarnoori
2021 arXiv   pre-print
Proper documentation plays an important role in successful software management and maintenance.  ...  To the best of our knowledge, we are the first to fine-tune a Transformer for issue classification. We train and evaluate our models in both project-based and cross-project settings.  ...  For instance, for the "Most Comments" baseline, we calculate the median number of comments for issues.  ... 
arXiv:2012.10951v3 fatcat:mlhv4cs4wfdgbjja2ugg4bynby

"Won't We Fix this Issue?" Qualitative Characterization and Automated Identification of Wontfix Issues on GitHub [article]

Andrea Di Sorbo, Gerardo Canfora, Sebastiano Panichella
2021 arXiv   pre-print
Context: Addressing user requests in the form of bug reports and Github issues represents a crucial task of any successful software project.  ...  Furthermore, we experiment with approaches enabling the prediction of wontfix issues by analyzing the titles and descriptions of reported issues when submitted.  ...  or enhancements, reported in the form of bug reports [3, 4] and Github issues [5] , are crucial tasks for the success of any software project [6, 7, 32] .  ... 
arXiv:1904.02414v3 fatcat:p2rct7ufzjeahmhpbaz3wk4tyq

Revisiting reopened bugs in open source software systems [article]

Ankur Tagra, Haoxiang Zhang, Gopi Krishnan Rajbahadur, Ahmed E. Hassan
2022 arXiv   pre-print
, that is, technical (i.e., patch/integration issues), documentation, human (i.e., due to incorrect bug assessment), and reasons not shown in the bug reports. 3) In projects with an acceptable AUC, 94%  ...  Moreover, reopened bugs also lead to a loss of trust in the end-users regarding the quality of the software.  ...  Numeric The number of words in the description Description text Description text Text The text of the description of a bug report Number of comments Number of comments Numeric The number of comments in  ... 
arXiv:2202.08701v1 fatcat:bf7qbfon3vdcvp6cslhakvgnjm

Label it be! A large-scale study of issue labeling in modern open-source repositories [article]

Joselito Júnior and Gláucya Boechat and Ivan Machado
2021 arXiv   pre-print
Some issue trackers use a structure in which the issue's title and description are the key information.  ...  Using issue trackers in their projects should encompass an infrastructure capable of hosting the project source code and community participation.  ...  This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior -Brasil (CAPES) -Finance Code 001, and FAPESB grant JCB0060/2016.  ... 
arXiv:2110.01328v1 fatcat:ucld66o6yfbvdlfmqxemcvxjlm

Bug Localization Using Revision Log Analysis and Open Bug Repository Text Categorization [chapter]

Amir H. Moin, Mohammad Khansari
2010 IFIP Advances in Information and Communication Technology  
Our approach employs textual information in summary and description of bugs reported to the bug repository, in order to form machine learning features.  ...  Given an unseen bug instance, the trained classifier can predict which part of the software source file hierarchy (revision path) is more likely to be related to this issue.  ...  We have used Support Vector Machines (SVMs) for predicting the file path which is more likely to be related to a given software bug report, using its summary and description.  ... 
doi:10.1007/978-3-642-13244-5_15 fatcat:6p5fw3bbfzcvniszxrojmyvuhm

An Alternative Issue Tracking Dataset of Public Jira Repositories [article]

Lloyd Montgomery, Clara Lüders, Walid Maalej
2022 arXiv   pre-print
Organisations use issue tracking systems (ITSs) to track and document their projects' work in units called issues.  ...  With this paper, we release a dataset of 16 public Jiras with 1822 projects, spanning 2.7 million issues with a combined total of 32 million changes, 9 million comments, and 1 million issue links.  ...  Issue Field Description Content summary A brief one-line summary of the issue. description A detailed description of the issue. comments Community discussion on each issue.  ... 
arXiv:2201.08368v2 fatcat:chssbepfh5h7bjflgl4wsauimi

DeepSoft: A vision for a deep model of software [article]

Hoa Khanh Dam, Truyen Tran, John Grundy, Aditya Ghose
2016 arXiv   pre-print
Such deep learned patterns of software can be used to address a range of challenging problems such as code and task recommendation and prediction.  ...  We present a vision for DeepSoft, an end-to-end generic framework for modeling software and its development process to predict future risks and recommend interventions.  ...  The diagnosis of an issue is typically in the form of natural language text capturing its description, the discussion around it (e.g. comments), and optionally some attributes (e.g. type, priority, etc  ... 
arXiv:1608.00092v1 fatcat:bgdsqzstxnhdjkyorh5cvtxcea

DeepSoft: a vision for a deep model of software

Hoa Khanh Dam, Truyen Tran, John Grundy, Aditya Ghose
2016 Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering - FSE 2016  
Such deep learned patterns of software can be used to address a range of challenging problems such as code and task recommendation and prediction.  ...  We present a vision for DeepSoft, an endto-end generic framework for modeling software and its development process to predict future risks and recommend interventions.  ...  The diagnosis of an issue is typically in the form of natural language text capturing its description, the discussion around it (e.g. comments), and optionally some attributes (e.g. type, priority, etc  ... 
doi:10.1145/2950290.2983985 dblp:conf/sigsoft/DamTGG16 fatcat:hrj52fgyfvgbxnfsqf2hvdv45a

How Long Will It Take to Fix This Bug?

Cathrin Weiss, Rahul Premraj, Thomas Zimmermann, Andreas Zeller
2007 Fourth International Workshop on Mining Software Repositories (MSR'07:ICSE Workshops 2007)  
Predicting the time and effort for a software problem has long been a difficult task.  ...  Our approach thus allows for early effort estimation, helping in assigning issues and scheduling stable releases. We evaluated our approach using effort data from the JBoss project.  ...  We are grateful to the JBoss team members who responded to our questions regarding their data and to the reviewers for their valuable comments.  ... 
doi:10.1109/msr.2007.13 dblp:conf/msr/WeissPZZ07 fatcat:ruhqbxxtxbdixi4v743qzqu4i4

Mining Software Metrics from Jazz

Jacqui Finlay, Andy Connor, Russel Pears
2011 2011 Ninth International Conference on Software Engineering Research, Management and Applications  
In this paper, we describe the extraction of source code metrics from the Jazz repository and the application of data mining techniques to identify the most useful of those metrics for predicting the success  ...  The results indicate that only a relatively small number of the available software metrics that we considered have any significance for predicting the outcome of a build.  ...  Finally, we conclude our paper with a discussion of the limitations of the current work and a plan for addressing these issues in future work.  ... 
doi:10.1109/sera.2011.40 dblp:conf/sera/FinlayCP11 fatcat:vwxontzptnfy5et3d6vv43cc44

Mining Software Metrics from Jazz [article]

Jacqui Finlay, Andy M. Connor, Russel Pears
2014 arXiv   pre-print
In this paper, we describe the extraction of source code metrics from the Jazz repository and the application of data mining techniques to identify the most useful of those metrics for predicting the success  ...  The results indicate that only a relatively small number of the available software metrics that we considered have any significance for predicting the outcome of a build.  ...  Finally, we conclude our paper with a discussion of the limitations of the current work and a plan for addressing these issues in future work.  ... 
arXiv:1407.2541v1 fatcat:uzodrbzoarcpvfde6ldmf4zkwq
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