Filters








7,365 Hits in 7.7 sec

On the feasibility of automated prediction of bug and non-bug issues

Steffen Herbold, Alexander Trautsch, Fabian Trautsch
2020 Empirical Software Engineering  
Objective We want to understand the overall maturity of the state of the art of issue type prediction with the goal to predict if issues are bugs and evaluate if we can improve existing models by incorporating  ...  Conclusions Issue type prediction can be a useful tool if the use case allows either for a certain amount of missed bug reports or the prediction of too many issues as bug is acceptable.  ...  as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons Empirical Software Engineering (2020) 25:5333-5369  ... 
doi:10.1007/s10664-020-09885-w fatcat:34fb4yabqrgqdb33js3yu6uzji

On the Feasibility of Automated Issue Type Prediction [article]

Steffen Herbold, Alexander Trautsch, Fabian Trautsch
2020 arXiv   pre-print
Objective: We want to understand the overall maturity of the state of the art of issue type prediction with the goal to predict if issues are bugs and evaluate if we can improve existing models by incorporating  ...  Conclusions: Issue type prediction can be a useful tool if the use case allows either for a certain amount of missed bug reports or the prediction of too many issues as bug is acceptable.  ...  Within this article, we analyzed the state of the art of automated issue type prediction with machine learning and focused on the prediction of whether an issue describes a bug or not.  ... 
arXiv:2003.05357v2 fatcat:swsxlft755fwxdspnd2d2uf7v4

Correction to: On the feasibility of automated prediction of bug and non-bug issues

Steffen Herbold, Alexander Trautsch, Fabian Trautsch
2020 Empirical Software Engineering  
The original version of this article unfortunately contained mistakes. Figures 8, 9 and 10 were incorrectly captured.  ...  Somehow, the plots in Fig. 8 were replaced with those from Fig. 9 and the original Fig. 8 was lost.  ...  Fig. 8 Results of leave-one-project-out cross validation with the CV ALL data.  ... 
doi:10.1007/s10664-020-09888-7 fatcat:iki32h22bjbrpii7fac47cy2ei

On the feasibility of automated prediction of bug and non-bug issues

Steffen Herbold, A. Trautsch, F. Trautsch
2020
Objective We want to understand the overall maturity of the state of the art of issue type prediction with the goal to predict if issues are bugs and evaluate if we can improve existing models by incorporating  ...  Conclusions Issue type prediction can be a useful tool if the use case allows either for a certain amount of missed bug reports or the prediction of too many issues as bug is acceptable.  ...  as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons Empirical Software Engineering licence, and indicate if changes were made.  ... 
doi:10.5445/ir/1000125241 fatcat:hokeiewwhvdk3mnt4prorvyymq

Correction to: On the feasibility of automated prediction of bug and non-bug issues

Steffen Herbold, Alexander Trautsch, Fabian Trautsch
2020
Publisher's note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.  ...  Fig. 8 Results of leave-one-project-out cross validation with the CV ALL data.  ...  with the CV BUG data.  ... 
doi:10.5445/ir/1000126903 fatcat:lc4d76anofb2hitrzariz7da2q

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

Ömer Köksal, Bedir Tekinerdogan
2021 Applied Sciences  
Software bug report classification is a critical process to understand the nature, implications, and causes of software failures.  ...  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.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app12010338 fatcat:korcuynyfrevflckq366wtjcti

Automated bug assignment: Ensemble-based machine learning in large scale industrial contexts

Leif Jonsson, Markus Borg, David Broman, Kristian Sandahl, Sigrid Eldh, Per Runeson
2015 Empirical Software Engineering  
We implement automated bug assignment 2 Leif Jonsson et al. and evaluate the performance in a set of controlled experiments.  ...  Objective: The goal of this study is to evaluate automated bug assignment techniques that are based on machine learning classication.  ...  Acknowledgements This work was supported in part by the Industrial Excellence Center EASE Embedded Applications Software Engineering 9 .  ... 
doi:10.1007/s10664-015-9401-9 fatcat:oemqchszfvdb7eus6w2zgmumoi

Identification of Security Related Bug Reports via Text Mining Using Supervised and Unsupervised Classification

Katerina Goseva-Popstojanova, Jacob Tyo
2018 2018 IEEE International Conference on Software Quality, Reliability and Security (QRS)  
This paper is focused on automated classification of software bug reports to security and non-security related, using both supervised and unsupervised approaches.  ...  Both supervised and unsupervised learning can be used for identification of security bug reports; the former slightly outperforms the latter at the expense of labeling the testing set.  ...  The authors thank the following NASA personnel for their support: Brandon Bailey, Craig Burget, and Dan Painter. The authors also thank Tanner Gantzer for his assistance.  ... 
doi:10.1109/qrs.2018.00047 dblp:conf/qrs/Goseva-Popstojanova18 fatcat:jkpn4jkn2rdqhcapma7uyztbeu

How Practitioners Perceive Automated Bug Report Management Techniques

Weiqin Zou, David Lo, Zhenyu Chen, Xin Xia, Yang Feng, Baowen Xu
2018 IEEE Transactions on Software Engineering  
To reduce the burden of bug report managers and facilitate the process of bug fixing, a great amount of software engineering research has been invested toward automated bug report management techniques  ...  Through the survey and the interviews, we gained a better understanding of the perceived usefulness (or its lack) of different categories of automated bug report management techniques.  ...  ACKNOWLEDGEMENT We are grateful for the survey and interview participants who answered our survey questions and provided many insightful comments.  ... 
doi:10.1109/tse.2018.2870414 fatcat:l5ivzcyw2rfabeigyy6unsv4qm

Predicting the severity of a reported bug

Ahmed Lamkanfi, Serge Demeyer, Emanuel Giger, Bart Goethals
2010 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)  
Unfortunately, while clear guidelines exist on how to assign the severity of a bug, it remains an inherent manual process left to the person reporting the bug.  ...  to predict the severity with a reasonable accuracy (both precision and recall vary between 0.65-0.75 with Mozilla and Eclipse; 0.70-0.85 in the case of GNOME).  ...  ACKNOWLEDGMENTS We would like to thank Andre Klapper who is an experienced bug triager for the interesting discussions we had during this study. We would also like to thank Sandro Boccuzzo, Giacomo  ... 
doi:10.1109/msr.2010.5463284 dblp:conf/msr/LamkanfiDGG10 fatcat:djppo3omjfgc5ah7uxnxe6qrc4

Patching as Translation: the Data and the Metaphor [article]

Yangruibo Ding, Baishakhi Ray, Premkumar Devanbu, Vincent J. Hellendoorn
2020 arXiv   pre-print
Our findings also lend strong support to the recent trend towards synthesizing edits of code conditional on the buggy context, to repair bugs.  ...  in accuracy; it can also help innovate on these models to raise the state-of-the-art further.  ...  On the other hand, our results shed light on the feasibility of another competing approach: repairing bugs by synthesizing edits of code conditional on the buggy context [8, 29, 31] .  ... 
arXiv:2008.10707v1 fatcat:naybnampxjcajn7d3gklejpnuu

BEST: A symbolic testing tool for predicting multi-threaded program failures

Malay K. Ganai, Nipun Arora, Chao Wang, Aarti Gupta, Gogul Balakrishnan
2011 2011 26th IEEE/ACM International Conference on Automated Software Engineering (ASE 2011)  
from an observed run of a multi-threaded program, and use precise modeling and constraint-based symbolic (non-enumerative) search to find feasible violating schedules in a generalization of the observed  ...  We specifically focus on tool scalability by devising POR-based simplification steps to reduce the formula and the search space by several orders-of-magnitude.  ...  Each atomic region should satisfy the following: • there should be at least one shared access on a nonsynchronization variable, and the first and/or last shared accesses should be on non-synchronization  ... 
doi:10.1109/ase.2011.6100134 dblp:conf/kbse/GanaiAWGB11 fatcat:cz5mnessjbagrbs2s5nqah6e5y

Identifying security bug reports via text mining: An industrial case study

Michael Gegick, Pete Rotella, Tao Xie
2010 2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)  
Security engineers can use the model to automate the classification of BRs from large bug databases to reduce the time that they spend on searching for SBRs.  ...  and predicted their classification as SBRs with a probability of at least 0.98.  ...  Cubranic and Murphy [6] use a Bayesian learning algorithm to predict which developer should fix a bug. Their automated technique can reduce the time required by manual analyses to triage BRs.  ... 
doi:10.1109/msr.2010.5463340 dblp:conf/msr/GegickRX10 fatcat:ms655jgtizbi5nza5t2t7ql47a

Predicting the Number of Reported Bugs in a Software Repository [chapter]

Hadi Jahanshahi, Mucahit Cevik, Ayşe Başar
2020 Lecture Notes in Computer Science  
The dataset is originally mined from Bugzilla and contains the number of bugs for the project between Jan 2010 and Dec 2019.  ...  We analyze the quality of long-term prediction for each model based on different performance metrics. The assessment is conducted on Mozilla, which is a large open-source software application.  ...  Not all models are able to predict more than one step ahead. Hence, we investigate the feasibility and sensitivity of different models to long-term prediction.  ... 
doi:10.1007/978-3-030-47358-7_31 fatcat:uo7i2iz4rbaufi36catghjtx4q

GLIB: Towards Automated Test Oracle for Graphically-Rich Applications [article]

Ke Chen, Yufei Li, Yingfeng Chen, Changjie Fan, Zhipeng Hu, Wei Yang
2021 arXiv   pre-print
However, various types of graphical glitches may arise from such GUI complexity and have become one of the main component of software compatibility issues.  ...  We perform an evaluation of on 20 real-world game apps (with bug reports available) and the result shows that can achieve 100% precision and 99.5% recall in detecting non-crashing bugs such as game GUI  ...  Moreover, we hope to find a tight connection between bugs and the characteristic of UI glitches so that we can predict the bug code given a screenshot with UI display issues.  ... 
arXiv:2106.10507v1 fatcat:xsbkovo3v5hnfpuszz6p2657g4
« Previous Showing results 1 — 15 out of 7,365 results