"Put your geek hat on," said hackathon advisor and participant Daniel Koo, dismissing teams to the breakout conference rooms.
Competitors downed energy drinks, breakfast, lunch and dinner. They drew visualizations on white boards and supersized post it notes. All were working on enhancements, new features or products, and/or code improvements to DataGen, a Java library
testing tool currently used by several high profile FINRA applications. DataGen tests software using specification and dependency modeling to produce relevant data sets. It systematically produces big data - terabytes within hours.
Team HHack, comprised of FINRA colleagues Michael Chao, the defending FINRA hackathon champ, Uyen-Truc Nguyen, and Han Xiao and University of Maryland student Mauricio Silva, narrowly edged Team TBD for the grand prize ($1024). HHack’s submission:
- Created a modeling engine based on Apache Hive Data Definition Language(Hive DDL);
- Developed a working interactive DataGen user interface (UI);
- Improved the DataGen code by addressing coding style issues and
- Designed an Android mobile notification application to alert users upon completion of a DataGen job.
“ It could take a long time to generate the data.”
"It could take a long time to generate the data," said Chao who presented the HHack demo. “It could take hours or days. It is a nice add-on to get notification when it is ready.” Both Chao and Silva received notifications on their cell phones
during the demo. HHack also won Best Code Quality Improvement ($128) and Practical Problem Solved using the DataGenerator ($128).
Contestants were judged on implementation, creativity and presentation. Seven teams presented enhancements and solutions ranging from a program that analyzed retirement stock options and generated a yearly analysis of the highest producing
funds to an entry that minimized human manipulation of the code and increased testing efficiency.
We asked competitors to think outside of the box. Creativity was essential. We were not disappointed. Team TBD fell one point below the grand prize winners. The group consisted of University of Maryland students, Brendan Good and Anna Skorodumova and
FINRA cohorts Marshall Peters and Michael Thomas. Team TBD submitted a preprocessing compiler for an alternative search logic plugin based on a Constraint Satisfaction Problem (CSP) solver. This was a different model from the State Chart
Extensible Markup Language (SCXML) engine currently used by DataGen.
Lone Python programmer Timothy Marcinowski paired with FINRA colleague Daniel Koo to form Productivity Engineering Team (PET). The duo created a functioning website with the DataGen service running in the cloud. They demonstrated how users
could register on PET’s “Real Data/Insanely Fast” DataGen site, click a “Try it Now” button and immediately begin using DataGen. Their solution bypassed the need to load anything onto a laptop. Team PET uploaded three SCXML files and produced
the output for the judges to examine. Marcinowski and Koo split $512, winning the Best Big Data or Cloud Solution ($256) and Best Product or Monetizing Idea Implementation ($256).
No one solved the Sudoku challenge. However, the judges awarded Yuriy Yankop, of Team Diversification Finder, the Nexus tablet for his 401(k) option analyzer.