Sergey Aleynikov Found Guilty of Stealing Goldman Sachs Code
Posted Dec 11 2010 1:12am
I don’t know if we will get to hear additional information on this case but the jury found Sergey Aleynikov of stealing algorithmic computer code on his last day of employment before going to another firm. He did find a way to get the small sized file on the last day of work, which if someone knows they are going to leave I would think they would not wait until the last day but who knows.
When I read the part about only transferring less than 32 megabytes, just common sense would tell me this is indeed only a portion of what would be required, however it could be a module that could be used elsewhere, as I used modules written by others in some of my projects, which by itself was pretty useless as it only did one or two things, and of course a full program like an EMR needs lots of modules and SQL (structured query language) statements. On the other hand too, I could see a programmer accidentally scooping up some code accidentally if multi-tasking with other items on the computer he’s working on.
A jury has found a former Goldman Sachs computer programmer guilty of stealing source code from the bank’s high-frequency trading platform. Part of the argument was that the code was open source and if that was the case why didn’t he get it somewhere else where open source code is usually open and available?
It is strange that he had the code with him on his computer though so there must have been some value, and perhaps the code had been modified from it’s original source too. I do hope we hear more about this case from the technology side and how it was proven that there was code stolen that had value and was a module that was used for high frequency trading. The circumstances of the code being found with him somewhat leads one to believe there was some value to it other than just being free and open source code/algorithms. BD
The trial of Sergey Aleynikov, a 40-year-old Russian immigrant, spotlighted the world of high-frequency trading, which uses complex computer algorithms to make rapid-fire trades to exploit tiny price discrepancies. High-frequency trading has become a growing important source of revenue at Wall Street firms. As a result, banks fiercely protect the code underpinning their businesses.