Research

HackPPL is a probabilistic programming language (PPL) built within the Hack programming language. Its universal inference engine allows developers to perform inference across a diverse set of models expressible in arbitrary Hack code. Through language-level extensions and direct integration with developer tools, HackPPL aims to bridge the gap between domain-specific and embedded PPLs. This paper overviews the design and implementation choices for the HackPPL toolchain and presents findings by applying it to a representative problem faced by social media companies.