OPER 782 Analytic Deployment Review

07 January 2019

Part of the analytic development process is ensuring that the algorithms you develop will be reproducible and portable for an end-user. Often an end-user’s machine is not configured in the same way as the developer’s – leading to unexpected side effects or errors. To ensure that your methods are reproducible & portable, your analytic data products will be reviewed on multiple ‘new’ machines representing those used by potential end-users. In lieu of a final exam, each student will be tasked to review two analytic projects developed by students in the course. Using the information presented in the GitHub repository README file and any documentation files provided with the analytic, the reviewer will review the analytic in these areas:

• Accuracy

  • Are the results accurate?
  • Is it clear how the results were computed?

• Compilation

  • Did the analytic work? (i.e. install correctly, startup correctly)
  • Were errors encountered when executing code according to the documentation?

• Ease of use

  • Is it clear how to use the analytic? (i.e. is the documentation clear)
  • Are the visualizations/plots interpretable?

Reviewers will capture their findings by (1) generating an issue on the analytic project’s Github page for each finding and (2) present all findings in a final report (.Rmd file – html_document). Both the report and the Github issues should include a brief discussion of the problem with one or more reproducible examples.

After reviewing the analytic, the reviewer will then assign it one of the following grades. Note: I will perform a second review on all projects to ensure that grades are assigned fairly. If my final grade differs greatly from the grade provided by the reviewer – it will be an indication of poor engagement by the reviewer.

• Outstanding – ready to publish/deploy (50 pts)

  • All proposal tasks completed
  • Documentation is thorough and clear
  • No errors or warnings during build/use

• Excellent – very little rework required (45 pts)

  • Few proposal tasks incomplete
  • Documentation is clear and mostly complete
  • Minor errors or warnings during build/use

• Satisfactory – extensive rework required (40 pts)

  • Several proposal tasks incomplete
  • Documentation is limited and/or poorly written
  • Severe errors during build or in use

• Unsatisfactory – complete restart required (35 pts)

  • Little progress made on proposal tasks
  • Little to no documentation
  • Cannot be compiled, unusable

The table below lists each developer, the URL of their respective project, and the assigned reviewers.

Developer	Git_URL	Reviewer1	Reviewer2
Uhorchak	https://github.com/nuhorchak/RClean	Trigo	Johnson
Munson	https://github.com/evan-l-munson/SAoTD	Kalhoff	Meyer
Ramirez	https://github.com/RachelRamirez/NPS	Gallagher	Elliott
Smith	https://github.com/JSmith146/CoRpEx	Stuntz	Munson
Trigo	https://github.com/citation891/MCAC	Sevier	Smith
Kalhoff	https://github.com/AFIT-R/instaExtract	Meyer	Ramirez
Butt	https://github.com/SpencerButt/IDPS-LAAD	Elliott	Trigo
Elliott	https://github.com/jtelliott/attrition-forecast	Johnson	Sevier
Johnson	https://github.com/slackliner33/Yahoo_DFS_Optimizer	Butt	Small
Sevier	https://github.com/williamcsevier/TextML	Small	Stuntz
Small	https://github.com/msmall318/Boots	Munson	Uhorchak
Gallagher	https://github.com/gallagherj2008/SWAT	Uhorchak	Kalhoff
Stuntz		Smith	Gallagher
Meyer	https://github.com/AFIT-R/MODA	Ramirez	Butt

List of developers, projects, and assigned reviewers for OPER782 (Winter 2018)

The assigned reviewers are to:

1. Download the project using devtools::install_github('devname/projectname')

2. Review the documentation provided

3. Test out the project in accordance with the documentation

4. Write a one-page review of the project using the rubric provided above.

5. Fork the project repository

6. Add your review to the inst/ directory of the project

7. Submit a pull request to the project developer to have them include the review as part of their project.