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Learning to Describe Solutions for Bug Reports Based on Developer Discussions [article]

Sheena Panthaplackel, Junyi Jessy Li, Milos Gligoric, Raymond J. Mooney
2022 arXiv   pre-print
When a software bug is reported, developers engage in a discussion to collaboratively resolve it.  ...  We build a corpus for this task using a novel technique for obtaining noisy supervision from repository changes linked to bug reports, with which we establish benchmarks.  ...  Acknowledgements We would like to thank Tanya Goyal, Prasoon Goyal, Adrian Benton, and Eunsol Choi for early feedback on this work.  ... 
arXiv:2110.04353v2 fatcat:mesfaxszpbbc7by453kvg2uude

Learning to Describe Solutions for Bug Reports Based on Developer Discussions

Sheena Panthaplackel, Junyi Jessy Li, Milos Gligoric, Ray Mooney
2022 Findings of the Association for Computational Linguistics: ACL 2022   unpublished
When a software bug is reported, developers engage in a discussion to collaboratively resolve it.  ...  We build a corpus for this task using a novel technique for obtaining noisy supervision from repository changes linked to bug reports, with which we establish benchmarks.  ...  Acknowledgements We would like to thank Tanya Goyal, Prasoon Goyal, Adrian Benton, and Eunsol Choi for early feedback on this work.  ... 
doi:10.18653/v1/2022.findings-acl.231 fatcat:ehtowbv4p5bu3pkqflkomi6yqm

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.  ...  Different classification algorithms namely-Linear Discriminant Analysis (LDA), Naive Bayes (NB) to predict the performance measures are used.  ...  Shadi et al. 19 discussed that bug triage system based on machine learning experience from low estimation accuracy.  ... 
doi:10.17485/ijst/2016/v9i33/97891 fatcat:xe2yzxpynna4vawxt3jjaeznla

Detecting problems in the database access code of large scale systems

Tse-Hsun Chen, Weiyi Shang, Ahmed E. Hassan, Mohamed Nasser, Parminder Flora
2016 Proceedings of the 38th International Conference on Software Engineering Companion - ICSE '16  
We discuss the challenges that we encountered and the day-to-day lessons that we learned during integrating our tool into the development processes.  ...  Thus, it is important for developers to write code that can access DBMS correctly and efficiently.  ...  Acknowledgments We are grateful to BlackBerry for providing access to many of the enterprise systems that we used in our case study.  ... 
doi:10.1145/2889160.2889228 dblp:conf/icse/ChenSHNF16 fatcat:72kelmgdurchrornnas3ftnc4q

Empirical Evaluation of Bug Linking

T. F. Bissyande, F. Thung, Shaowei Wang, D. Lo, Lingxiao Jiang, L. Reveillere
2013 2013 17th European Conference on Software Maintenance and Reengineering  
Finally, we apply this benchmark on ReLink to report the strengths and limitations of this bug linking tool.  ...  To collect software bugs found by users, development teams often setup bug trackers using systems such as Bugzilla.  ...  report comments where developers discuss the fix.  ... 
doi:10.1109/csmr.2013.19 dblp:conf/csmr/BissyandeTWLJR13 fatcat:cddnxl3ombhbdas5to2h7kamui

Adopting Automated Bug Assignment in Practice – A Registered Report of an Industrial Case Study [article]

Markus Borg, Leif Jonsson, Emelie Engström, Béla Bartalos, Attila Szabo
2021 arXiv   pre-print
Inspired by contemporary work on mining software repositories, we designed a prototype bug assignment solution based on machine learning in 2011-2016.  ...  [Background/Context] The continuous inflow of bug reports is a considerable challenge in large development projects.  ...  , use ensemble-based machine learning to automate bug assignment.  ... 
arXiv:2109.13635v1 fatcat:x5kf4kvc7zcspgz3qxfdqrhezi

Recommending relevant classes for bug reports using multi-objective search

Rafi Almhana, Wiem Mkaouer, Marouane Kessentini, Ali Ouni
2016 Proceedings of the 31st IEEE/ACM International Conference on Automated Software Engineering - ASE 2016  
Learning-to-rank (LR) [7] technique ranks classes using a machine learning technique to learn from the history of previous bug reports.  ...  Thus, a solution is defined as a sequence of classes to recommend for inspection by the developer to locate the bug.  ... 
doi:10.1145/2970276.2970344 dblp:conf/kbse/AlmhanaMK016 fatcat:e4omk4ahz5bsznh4up6jcku3xq

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

Ömer Köksal, Bedir Tekinerdogan
2021 Applied Sciences  
In contrast to earlier studies, our study is applied to a commercial software system based on unstructured bilingual bug reports written in English and Turkish.  ...  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.  ...  Hence, machine learning focuses on developing computer programs that can access data and use it to learn for themselves.  ... 
doi:10.3390/app12010338 fatcat:korcuynyfrevflckq366wtjcti

A Review on Bug Report Assignment

2018 International Journal of Software Engineering and Its Applications  
This paper provides a study for the bug reports to inspire the necessity for the work on bug report assignment and the existing work that has been performed on bug report assignment with possible problems  ...  Also, the practical analysis using various machine learning algorithm has been performed on the basis of a number of attributes and number of classes on Eclipse project containing 10,000 bug reports.  ...  Literature Review This section presents several relevant papers to describe the significant machine learning algorithms for bug report assignment.  ... 
doi:10.21742/ijseia.2018.12.1.01 fatcat:6cyifknsrze7vletdvdp626k2y

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  
Objective: The goal of this study is to evaluate automated bug assignment techniques that are based on machine learning classication.  ...  In particular, incorrect assignments of bug reports to development teams can be very expensive in large software development projects.  ...  Developers are then connected to bug reports based on multi-label learning using ML-KNN.  ... 
doi:10.1007/s10664-015-9401-9 fatcat:oemqchszfvdb7eus6w2zgmumoi

Software Development Bug Tracking: "Tool Isn't User Friendly" or "User Isn't Process Friendly" [chapter]

Leah Goldin, Lilach Rochell
2002 Lecture Notes in Computer Science  
In this article we describe the implementation of software development bug tracking via WebPT/Continuus, in a development organization of about 200 developers, testers and managers of various ranks.  ...  We emphasize the interplay of technology, procedures and human nature, and describe our experiences and lessons on how this interplay affects the continuous quality improvement process.  ...  Early work reported on bug or defect tracking mainly focus on measuring defects and collecting defect statistics as a criterion for software quality.  ... 
doi:10.1007/3-540-47984-8_26 fatcat:cwhwhtggcvdvrcsqvpxyimkemy

A survey on bug-report analysis

Jie Zhang, XiaoYin Wang, Dan Hao, Bing Xie, Lu Zhang, Hong Mei
2015 Science China Information Sciences  
and localizing bugs based on bug reports.  ...  In particular, this paper first presents some background for bug reports and gives a small empirical study on the bug reports on Bugzilla to motivate the necessity for work on bug-report analysis.  ...  [7] proposed to apply a recently developed supervised machining learning technique called Learn To Rank (LTR) to rank candidate bug reports based on a series of features.  ... 
doi:10.1007/s11432-014-5241-2 fatcat:nkopbdht6nbjrbmniorrnovc2m

Software Component Prediction for Bug Reports

Wei Zhang, Chris Challis
2019 Asian Conference on Machine Learning  
In this paper, we present a machine learning based solution for the bug assignment problem.  ...  In a software life cycle, bugs could happen at any time. Assigning bugs to relevant components/developers is a crucial task for software development. It is also a tough and resource consuming job.  ...  Therefore, we propose a machine learning based solution to alleviate the human burden and speed up the process. Problem Definition We use JIRA to track bug reports.  ... 
dblp:conf/acml/ZhangC19 fatcat:ieqhafnq3nfxvipbszntxqmqru

Development Emails Content Analyzer: Intention Mining in Developer Discussions (T)

Andrea Di Sorbo, Sebastiano Panichella, Corrado A. Visaggio, Massimiliano Di Penta, Gerardo Canfora, Harald C. Gall
2015 2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)  
A study based on data from Qt and Ubuntu, highlights a high precision (90%) and recall (70%) of DECA in classifying email content, outperforming traditional machine learning strategies.  ...  A study based on data from Qt and Ubuntu, highlights a high precision (90%) and recall (70%) of DECA in classifying email content, outperforming traditional machine learning strategies.  ...  We also thank the reviewers of this paper for the very insightful comments useful to improve our research work.  ... 
doi:10.1109/ase.2015.12 dblp:conf/kbse/SorboPVPCG15 fatcat:b6xvvb3mnjd3nhntv7xeqgxlf4

Who Writes What Checkers? - Learning from Bug Repositories

Takeshi Yoshimura, Kenji Kono
2014 Hot Topics in System Dependability  
This paper explores the use of machine learning to help extract bug patterns from bug repositories.  ...  Our preliminary work with this approach is encouraging: by investigating one of the 66 clusters, we were able to identify typical bug patterns in PCI device drivers and developed static code checkers to  ...  Acknoledgements We thank the anonymous reviewers for their helpful feedback.  ... 
dblp:conf/hotdep/YoshimuraK14 fatcat:flgyh63xszdzrflor7val4vixu
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