4 ms·

Yes, the DOOP folks under Iannis Smaragdakis have been doing this for a while. They use souffle, I believe: https://souffle-lang.github.io/ https://souffle-lang

by rntz 8y ago

Yes, the DOOP folks under Iannis Smaragdakis have been doing this for a while. They use souffle, I believe: https://souffle-lang.github.io/ https://souffle-lang.github.io/. This is Semmle's business model (https://semmle.com/ https://semmle.com/). They have a custom Datalog with OO features they call QL. I've heard LogicBlox used to do program analysis as well, but AIUI they turned more towards business analytics and then got bought out, and the Datalog engine team all jumped ship. The Rust compiler has been exploring implementing some of their type system (the borrow checker, I think?) in a Datalog. On the academic front, Tamás Szabó and Sebastian Erdweg have been working on an incremental Datalog engine for static analysis; https://github.com/szabta89/IncA https://github.com/szabta89/IncA. I know Tamas has worked for Itemis, but I don't know whether they're using this tech. I'm working on a functional language, Datafun, inspired by Datalog, but it's too much of a toy to do any real analysis with at the moment. All in all, Datalog is still a niche language and static analysis a niche application of it, but it seems to be on the rise.

trurl 8y ago
The LogicBlox platform is still in use and in active development at Infor. But yes, many of the principals have indeed left. DOOP actually used LogicBlox before Souffle existed, but it is difficult to be competitive when Souffle doesn't need things like transactions, ACID, datasets larger than memory, incremental evaluation, etc.
cfallin 8y ago
Doop is a fantastic base system to extend for anyone wanting to do program analysis generally! I built my thesis work on top of it (recently defended but unfortunately not published yet) and Datalog is incredibly productive to prototype ideas. (Performance is another matter -- one has to pay careful attention to clause ordering, and watch out for O(n^2) / O(n^3) / ... loop nests, but at least it's easier to try options than refactoring an ad-hoc analysis engine.)
frankmcsherry 8y ago
Moar links! (caveat: I am involved in many things) 1. You can implement some minor flavor of Doop in differential dataflow (https://github.com/TimelyDataflow/differential-dataflow/tree/master/doop https://github.com/TimelyDataflow/differential-dataflow/tree...). The fragment came from Yannis which he described as a minimal non-trivial analysis (vs other, even smaller fragments), but it still uses some 900 dataflow operators (updates in 10s of ms when inputs change, though). The DD impl isn't meant to be understood, I'm afraid. 2. Many ex-LB folks are now at relational.ai doing .. advanced weird tech like they did with LB. I'd watch them (I do). 3. Polonius (https://github.com/rust-lang/polonius https://github.com/rust-lang/polonius) defines the Rust borrow checker as Datalog rules, and went from differential dataflow to datafrog (https://github.com/rust-lang/datafrog https://github.com/rust-lang/datafrog). 4. If you want to check out other incremental Datalog environments, in addition to IncA, there are https://github.com/comnik/declarative-dataflow https://github.com/comnik/declarative-dataflow https://github.com/ryzhyk/differential-datalog https://github.com/ryzhyk/differential-datalog https://github.com/TimelyDataflow/differential-dataflow https://github.com/TimelyDataflow/differential-dataflow Good times for Datalog, imo.

by rntz 8y ago

trurl 8y ago

The LogicBlox platform is still in use and in active development at Infor. But yes, many of the principals have indeed left. DOOP actually used LogicBlox before Souffle existed, but it is difficult to be competitive when Souffle doesn't need things like transactions, ACID, datasets larger than memory, incremental evaluation, etc.

cfallin 8y ago

Doop is a fantastic base system to extend for anyone wanting to do program analysis generally! I built my thesis work on top of it (recently defended but unfortunately not published yet) and Datalog is incredibly productive to prototype ideas. (Performance is another matter -- one has to pay careful attention to clause ordering, and watch out for O(n^2) / O(n^3) / ... loop nests, but at least it's easier to try options than refactoring an ad-hoc analysis engine.)

frankmcsherry 8y ago

Moar links! (caveat: I am involved in many things) 1. You can implement some minor flavor of Doop in differential dataflow (https://github.com/TimelyDataflow/differential-dataflow/tree/master/doop https://github.com/TimelyDataflow/differential-dataflow/tree...). The fragment came from Yannis which he described as a minimal non-trivial analysis (vs other, even smaller fragments), but it still uses some 900 dataflow operators (updates in 10s of ms when inputs change, though). The DD impl isn't meant to be understood, I'm afraid. 2. Many ex-LB folks are now at relational.ai doing .. advanced weird tech like they did with LB. I'd watch them (I do). 3. Polonius (https://github.com/rust-lang/polonius https://github.com/rust-lang/polonius) defines the Rust borrow checker as Datalog rules, and went from differential dataflow to datafrog (https://github.com/rust-lang/datafrog https://github.com/rust-lang/datafrog). 4. If you want to check out other incremental Datalog environments, in addition to IncA, there are https://github.com/comnik/declarative-dataflow https://github.com/comnik/declarative-dataflow https://github.com/ryzhyk/differential-datalog https://github.com/ryzhyk/differential-datalog https://github.com/TimelyDataflow/differential-dataflow https://github.com/TimelyDataflow/differential-dataflow Good times for Datalog, imo.