[jes5199]

I’m in the same boat, I really like the idea of it but the actual use of it eludes me. It’s like there’s a cultural gap, even when they’re talking about the practical applications of the system it’s incomprehensible; I eventually came to the conclusion that they are doing a lot of work to deal with situations that I have never even heard of people being in

[tudorgirba]

Interesting observation.

The problem we address is how to understand a situation about a software system without relying on reading code.

Reading code is the most expensive activity today in software engineering. We read code because we want to understand enough to decide how to change the system. The activity is actually decision making. Reading is just the way we extract information from the system. Where there is a way, there can be others.

In our case, we say that for every question we have about the system it's possible to create tools that give you the answer. Perhaps a question is why not use standard tools? As systems are highly contextual, we cannot predict the specific problems so standard tools will always require extra manual work. The alternative is to build the tools during development, after you know the problem. For this to be practical, the creation of the tools must be inexpensive, and this is what GT shows to be possible.

This might sound theoretical, but it turns out that we can apply it to various kinds of problems: browsing and making sense of an API that has no documentation, finding dependencies in code, applying transformations over a larger code base, exploring observability logs and so on.

Does this help in any way?

[jes5199]

I’m still trying to understand this. Could it be that these are much larger codebases than I’m used to? I actually haven’t seen software analysis of codebases provide much value

[tudorgirba]

Ok, do you write tests? If you do, you are already employing analyses :).

The interesting bit about a test is that it's inexpensive to create and you can create it within the context of your system after you know the problem. You do not download it from the web. You create it in context and then, when even a single test fails you might stop and fix that one. Why? Because it reveals something you consider valuable.

Now, tests answer functional questions, but the same idea can be applied to any other kinds of analyses. The key is to have them created within the system. If you download an analysis from the web, they will be solving some problem, just not yours, so it will not look interesting.