From Datalog to flix: a declarative language for fixed points on lattices

Abstract

We present FLIX, a declarative programming language for specifying and solving least fixed point problems, particularly static program analyses. FLIX is inspired by Datalog and extends it with lattices and monotone functions. Using FLIX, implementors of static analyses can express a broader range of analyses than is currently possible in pure Datalog, while retaining its familiar rule-based syntax.We define a model-theoretic semantics of FLIX as a natural extension of the Datalog semantics. This semantics captures the declarative meaning of FLIX programs without imposing any specific evaluation strategy. An efficient strategy is semi-naïve evaluation which we adapt for FLIX. We have implemented a compiler and runtime for FLIX, and used it to express several well-known static analyses, including the IFDS and IDE algorithms. The declarative nature of FLIX clearly exposes the similarity between these two algorithms.

Effective interactive resolution of static analysis alarms

“…Non-Datalog Analyses. We focus on program analyses implemented in Datalog for two reasons: (1) it is easy to capture provenance information for such analyses; and (2) there is a growing trend towards specifying program analyses in Datalog [Jordan et al 2016;Madsen et al 2016;Mangal et al 2015;Smaragdakis and Bravenboer 2010;Zhang et al 2014]. However, not all analyses are implemented in Datalog; for example, see Ayewah et al [2008]; Bessey et al [2010]; Copeland [2005].…”

“…Our approach automatically generates the ILP formulation for any analysis specified in a constraint language. Specifically, we target Datalog, a declarative logic programming language that is widely used in formulating program analyses [Madsen et al 2016;Mangal et al 2015;Smaragdakis and Bravenboer 2010;Smaragdakis et al 2014;Whaley et al 2005;Zhang et al 2014]. Our constraint-based approach also allows incorporating orthogonal techniques to reduce user effort, such as alarm clustering techniques that express dependencies between different alarms using constraints, possibly in a different abstract domain [Le and Soffa 2010;Lee et al 2012].…”

Seminaïve evaluation for a higher-order functional language

“…A natural approach to solving this problem is to find a language in which to write the extensions, which preserves the semantic guarantees that Datalog offers. Two such proposals are Flix [Madsen et al 2016] and Datafun [Arntzenius and Krishnaswami 2016]. Conveniently for our exposition, these two languages embody two alternative design strategies.…”

Some trade-offs in reducing the overhead of assertion run-time checks via static analysis

“…Some concrete examples of the application of this approach that we have explored within Ciao include cost analysis of Java bytecode programs [33,34] and energy bound inference in binaries stemming from C-style programs [35,36]. Recently [37] proposed an approach for using Horn clauses as an intermediate language which is quite similar to Ciao's [32].The Horn clause-based transformational approach is currently receiving considerable interest (see, e.g., [38][39][40]), and is even the subject of the "Horn clause-based Verification and Synthesis" workshop series [41]. In [42] encouraging results are reported for the direct inference of the verification conditions of safety properties for C programs based on their (C)LP representation.…”

“…The Horn clause-based transformational approach is currently receiving considerable interest (see, e.g., [38][39][40]), and is even the subject of the "Horn clause-based Verification and Synthesis" workshop series [41]. In [42] encouraging results are reported for the direct inference of the verification conditions of safety properties for C programs based on their (C)LP representation.…”