Mangle

Mangle is a programming language for deductive database programming. It
is an extension of Datalog, with various extensions like aggregation, function
calls and optional type-checking.

Deductive database programming is useful for bringing data from multiple
data sources together since it enables us to represent and query that data in
a uniform way. It can also be used to model domain knowledge, similar
to machine-readable ontology but without being restricted to binary
predicates.

Datalog is an expressive declarative language similar to relational calculus
(think SQL and relational views). Unlike relational calculus, it also supports
recursive rules and program structuring in a straightforward way.

Mangle contains Datalog as a fragment and adds extensions that make its use
more practical. Some of the good properties like guaranteed termination are
lost when such extensions are used.

The goal of Mangle as an open source project is to convey the concepts in
a way that is accessible to developers and lends itself to easy experimentation.
This repository contains an implementation of Mangle as a go library that can be
easily embedded into applications.

Check out the docs and the
GitHub discussions for more
information. There is also a Q&A section.

For an example how to use Mangle library in a database-like grpc service,
see the separate Mangle demo service repo.

This is not an officially supported Google product.

Table of Contents

• Examples
• Building

Examples

Simple Queries

Imagine you were asked to spot software affected by the
log4j vulnerability discovered in late 2021.
We want to look for projects that contain a Java archive (jar file) of
log4j that is not updated to the patched version.

projects_with_vulnerable_log4j(P) :-
  projects(P),
  contains_jar(P, "log4j", Version),
  Version != "2.17.1",
  Version != "2.12.4",
  Version != "2.3.2".

This is a Mangle rule: conceptually, the implementation retrieve all
possible values for variables P and Version that make all the subgoals true.

Simple Mangle rules like this correspond to select-project-join relational
queries. The same query in SQL would look like this:

SELECT projects.id as P
FROM projects JOIN contains_jar ON projects.id = contains_jar.project_id
WHERE contains_jar.version NOT IN ("2.17.1", "2.12.4", "2.3.2")

Unlike SQL, our Mangle rule projects_with_vulnerable_log4j has a name
and can be referenced in other queries.

(If translating non-recursive Datalog into SQL queries sounds interesting, you
should check out the Logica open source project.)

Aggregation

In practice, querying is rarely enough and we also need grouping and
aggregation.

contains_jar(P, Name, Version) :-
  contains_jar_directly(P, Name, Version).

contains_jar(P, Name, Version) :-
  project_depends(P, Q),
  contains_jar(Q, Name, Version).

go get -t ./...
go build ./...
go test ./...

wget http://www.antlr.org/download/antlr-4.13.2-complete.jar
alias antlr='java -jar $PWD/antlr-4.13.2-complete.jar'
antlr -Dlanguage=Go -package gen -o ./ parse/gen/Mangle.g4 -visitor