Hi Matthias - sounds good.  We'll plan to submit a proposal and are looking 
forward to attending the conference again this year.

On Tuesday, January 23, 2018 at 1:44:43 PM UTC-7, Matthias Bussonnier wrote:
>
> Hi Dave and the NbGallery team.
>
> I'll add this on our to-read list ! I think that this might be of interest 
> for JupyteCon, the Call for Proposal was opened last week:
> https://blog.jupyter.org/jupytercon-2018-call-for-proposal-87986014ee0b
>
> Happy to also see some ruby notebooks !
>
> Nice work! Thanks,
> -- 
> Matthias
>
> On 23 January 2018 at 12:06, Dave <[email protected] <javascript:>> 
> wrote:
>
>> Hi All,
>>
>> I wanted to share the following white paper 
>> <https://nbgallery.github.io/health_paper.html> (abstract below) which 
>> details our team's work to systematically measure the code health of 
>> Jupyter notebooks from within an nbgallery instance.  As background, 
>> nbgallery 
>> <https://github.com/nbgallery/nbgallery>is an enterprise Jupyter 
>> notebook sharing and collaboration platform developed within the Department 
>> of Defense.  Our team operates in a unique environment which requires us to 
>> take some interesting and unconventional approaches to evaluating code 
>> health.  For instance, traditional unit testing in our environment is a 
>> challenge since we use dynamic data sets with row-level security (so the 
>> data landscape shifts by the day and by the user), and many of our notebook 
>> contributors are not typical software developers with experience or 
>> interest in developing unit tests.  We think some of our practical 
>> approaches arising from evaluating code health in a complex notebook 
>> environment might extend to projects like JupyterHub and Binder.
>>
>> Please check out the paper 
>> <https://nbgallery.github.io/health_paper.html> and let us know if you 
>> have any questions/comments.
>>
>> Thanks!
>>
>> Dave
>>
>> *Systems that support user-developed code are faced with a key challenge: 
>> understanding the health of that code, which we define as the expectation 
>> that existing code will function properly in the current environment. The 
>> growing popularity of Jupyter notebooks has led to the development of 
>> publishing and execution platforms such as the open-source nbgallery 
>> <https://github.com/nbgallery/nbgallery> project. Users of nbgallery would 
>> like to understand when they can expect a notebook to work, and notebook 
>> authors may wish to monitor the execution of their code and be informed of 
>> errors. This paper describes our initial efforts to measure code health in 
>> a corpus of notebooks within an instance of nbgallery. Our vision is that 
>> this work will help address problems that arise from user-developed code 
>> and motivate further study in systems beyond Jupyter and nbgallery.*
>>
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