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 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 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.
This is not an officially supported Google product.
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
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.)
In practice, querying is rarely enough and we also need grouping and aggregation.
count_projects_with_vulnerable_log4j(Num) :- projects_with_vulnerable_log4j(P) |> do fn:group_by(), let Num = fn:Count().
The example does not specify what
contains_jar does. Here is a possible
contains_jar that walks a dependency graph.
This shows that Mangle rules can be recursive.
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).
The two rules correspond to two cases in which a project may "contain" a jar: either directly, or through some dependency.
When engineering requirements, it is useful to model a slice of the real world through a domain model and controlled vocabulary. Description logics use roles to describe how concepts interact, but the relationships are always binary. Mangle can represent binary predicates, but also arbitrary n-ary relations.
one_or_two_leg_trip(Codes, Start, Destination, Price) :- direct_conn(Code, Start, Destination, Price) |> let Codes = [Code]. one_or_two_leg_trip(Codes, Start, Destination, Price) :- direct_conn(FirstCode, Start, Connecting, FirstLegPrice). direct_conn(SecondCode, Connecting, Destination, SecondLegPrice) |> let Code = [FirstCode, SecondCode], let Price = fn:sum(FirstLegPrice, SecondLegPrice).
graph LR /zurich -->|/code/ZL <br /> 60 CHF| /lausanne /zurich -->|/code/ZB <br /> 30 CHF| /bern /bern -->|/code/ZL <br /> 30 CHF| /lausanne
If you want to build from source, you need to set up ANTLR first, which requires Java runtime environment.
wget http://www.antlr.org/download/antlr-4.11.1-complete.jar alias antlr='java -jar $PWD/antlr-4.11.1-complete.jar'
Then you can generate the parser sources
antlr -Dlanguage=Go -package gen -o ./ parse/gen/Mangle.g4 -visitor
... and finally get the dependencies (see go.mod) and build the library:
go get ... go build ...
The Mangle maintainers welcome external contributions to spec, documentation and this implementation (see CONTRIBUTING.md) and also other implementations. Pull requests will be handled like for tensorflow, to ensure our internal usage and tests will pass.