Utilizing code change information for better automated debugging

Author(s):  
Ming Wen
2012 ◽  
Vol 433-440 ◽  
pp. 5601-5606
Author(s):  
Jian Ping Ma ◽  
Bing Wang

This paper presents a method of automated testing inflexion of OCXO by computer. It has been greatly reduced the debugging process and production time of OCXO through the configuration consisted by computer software and AVR single chip designing. All the advantages mentioned above contribute to the mass production of OCXO


Author(s):  
Shaopeng Xu ◽  
Chenyu Zhou ◽  
Zhiwei Gu ◽  
Guoquan Wu ◽  
Wei Chen ◽  
...  

2016 ◽  
Vol 113 (35) ◽  
pp. 9882-9887 ◽  
Author(s):  
Robert Riley ◽  
Sajeet Haridas ◽  
Kenneth H. Wolfe ◽  
Mariana R. Lopes ◽  
Chris Todd Hittinger ◽  
...  

Ascomycete yeasts are metabolically diverse, with great potential for biotechnology. Here, we report the comparative genome analysis of 29 taxonomically and biotechnologically important yeasts, including 16 newly sequenced. We identify a genetic code change, CUG-Ala, in Pachysolen tannophilus in the clade sister to the known CUG-Ser clade. Our well-resolved yeast phylogeny shows that some traits, such as methylotrophy, are restricted to single clades, whereas others, such as l-rhamnose utilization, have patchy phylogenetic distributions. Gene clusters, with variable organization and distribution, encode many pathways of interest. Genomics can predict some biochemical traits precisely, but the genomic basis of others, such as xylose utilization, remains unresolved. Our data also provide insight into early evolution of ascomycetes. We document the loss of H3K9me2/3 heterochromatin, the origin of ascomycete mating-type switching, and panascomycete synteny at the MAT locus. These data and analyses will facilitate the engineering of efficient biosynthetic and degradative pathways and gateways for genomic manipulation.


2020 ◽  
Vol 30 (11n12) ◽  
pp. 1779-1800
Author(s):  
Zengyang Li ◽  
Peng Liang ◽  
Dengwei Li ◽  
Ran Mo ◽  
Bing Li

Both complexity of code change for bug fixing and bug severity play an important role in release planning when considering which bugs should be fixed in a specific release under certain constraints. This work investigates whether there are significant differences between bugs of different severity levels regarding the complexity of code change for fixing the bugs. Code change complexity is measured by the number of modified lines of code, source files, and packages, as well as the entropy of code change. We performed a case study on 20 Apache open source software (OSS) projects using commit records and bug reports. The study results show that (1) for bugs of high severity levels (i.e. Blocker, Critical and Major in JIRA), there is no significant difference on the complexity of code change for fixing bugs of different severity levels for most projects, while (2) for bugs of low severity levels (i.e. Major, Minor and Trivial in JIRA), fixing bugs of a higher severity level needs significantly more complex code change than fixing bugs of a lower severity level for most projects. These findings provide useful and practical insights for effort estimation and release planning of OSS development.


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