  The traditional approach in HEP analysis software is to loop over every event
and every object via the ROOT framework. This method follows an imperative
paradigm, in which the code is tied to the storage format and steps of
execution. A more desirable strategy would be to implement a declarative
language, such that the storage medium and execution are not included in the
abstraction model. This will become increasingly important to managing the
large dataset collected by the LHC and the HL-LHC. A new analysis description
language (ADL) inspired by functional programming, FuncADL, was developed using
Python as a host language. The expressiveness of this language was tested by
implementing example analysis tasks designed to benchmark the functionality of
ADLs. Many simple selections are expressible in a declarative way with FuncADL,
which can be used as an interface to retrieve filtered data. Some limitations
were identified, but the design of the language allows for future extensions to
add missing features. FuncADL is part of a suite of analysis software tools
being developed by the Institute for Research and Innovation in Software for
High Energy Physics (IRIS-HEP). These tools will be available to develop highly
scalable physics analyses for the LHC.
