Solving real problems without reading code

Thursday, 9:00 AM EST - AURINKO (2ND FLOOR)

Too often, developers drill into the see of data related to a software system manually armed with only rudimentary techniques and tool support. This approach does not scale for understanding larger pieces and it should not perpetuate.

Software is not text. Software is data. Once you see it like that, you will want tools to deal with it.

Developers are data scientists. Or at least, they should be.

50% of the development time is typically spent on figuring out the system in order to figure out what to do next. In other words, software engineering is primarily a decision making business. Add to that the fact that often systems contain millions of lines of code and even more data, and you get an environment in which decisions have to be made quickly about lots of ever moving data.

Yet, too often, developers drill into the see of data manually with only rudimentary tool support. Yes, rudimentary. The syntax highlighting and basic code navigation are nice, but they only count when looking into fine details. This approach does not scale for understanding larger pieces and it should not perpetuate.

This might sound as if it is not for everyone, but consider this: when a developer sets out to figure out something in a database with million rows, she will write a query first; yet, when the same developer sets out to figure out something in a system with a million lines of code, she will start reading. Why are these similar problems approached so differently: one time tool-based and one time through manual inspection? And if reading is such a great tool, why do we even consider queries at all? The root problem does not come from the basic skills. They exist already. The main problem is the perception of what software engineering is, and of what engineering tools should be made of.

In this talk, we show live examples of how software engineering decisions can be made quickly and accurately by building custom analysis tools that enable browsing, visualizing or measuring code and data. Once this door is open you will notice how software development changes. Dramatically.

About Tudor Gîrba

Tudor Gîrba

Tudor Gîrba (tudorgirba.com) is a software environmentalist and co-founder of feenk.com where he works with an amazing team on the Glamorous Toolkit, a novel IDE that reshapes the Development eXperience (gtoolkit.com).

He built all sorts of projects like the Moose platform for software and data analysis (moosetechnology.org), and he authored a couple of methods like humane assessment (humane-assessment.com). In 2014, he also won the prestigious Dahl-Nygaard Junior Prize for his research (aito.org). This was a surprising prize as he is the only recipient that was not a university professor, even if he does hold a PhD from the University of Bern from a previous life.

These days he likes to talk about moldable development. If you want to see how much he likes that, just ask him if moldable development can fundamentally change how we approach software development.

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