A Survey on Recommendation system for bug analyzer
Abstract & Details
Research Area
computer engineering
Keywords
Mining software repositories
prediction and reduction technique
application of data preprocessing
data management in bug repositories
bug data reduction
feature selection
instance selection
bug triage.
Abstract
We primarily focus the bug reduction system in this project with an assumption that the
communication channel between developer and the bug reduction is maintained. We have to prevent redundant bug
in the repository. We introduce novel alternative that provides significantly-improved bug report. Users dislike the
redundancy of same bug frequently in the bug data, and assign appropriate developer to resolve bug issues. The
second approach allows the associated developer to resolve them according to bug classification. This is a tedious
assumption, since private data can be exposed by either software bugs or configuration errors at the trusted servers
or by malicious administrators. Finally, relying on heavy-weight mechanisms to obtain provable redundant bug
report.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | mahesh mantri | MMIT college,Lohegaon,pune |
| 2 | nikhil amrutkar | MMIT college,Lohegaon,pune |
| 3 | tejasvini mirge | MMIT college,Lohegaon,pune |
| 4 | sujit bende | MMIT college,Lohegaon,pune |
How to Cite
Use the following formats to cite this article in your research.
APA Style
mantri, mahesh, amrutkar, nikhil, mirge, tejasvini, & bende, sujit (2017). A Survey on Recommendation system for bug analyzer. International Journal of Advance Research and Innovative Ideas In Education, 3(1), 1232-1236.
MLA Style
mantri, mahesh, et al. "A Survey on Recommendation system for bug analyzer." International Journal of Advance Research and Innovative Ideas In Education, vol. 3, no. 1, 2017, pp. 1232-1236.
IEEE Style
mahesh mantri, nikhil amrutkar, tejasvini mirge, and sujit bende, "A Survey on Recommendation system for bug analyzer," International Journal of Advance Research and Innovative Ideas In Education, vol. 3, no. 1, pp. 1232-1236, 2017.
Vancouver Style
mantri mahesh, amrutkar nikhil, mirge tejasvini, bende sujit. A Survey on Recommendation system for bug analyzer. International Journal of Advance Research and Innovative Ideas In Education. 2017;3(1):1232-1236.
Harvard Style
mantri, mahesh, amrutkar, nikhil, mirge, tejasvini, & bende, sujit (2017) 'A Survey on Recommendation system for bug analyzer', International Journal of Advance Research and Innovative Ideas In Education, 3(1), pp. 1232-1236.
Chicago Style
mantri, mahesh, et al. "A Survey on Recommendation system for bug analyzer." International Journal of Advance Research and Innovative Ideas In Education 3, no. 1 (2017): 1232-1236.
Turabian Style
mantri, mahesh, et al. "A Survey on Recommendation system for bug analyzer." International Journal of Advance Research and Innovative Ideas In Education 3, no. 1 (2017): 1232-1236.
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