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Static analysis approximates the results of a program by examining only its syntax. For example, control-flow analysis (CFA) determines which syntactic lambdas (for functional languages) or (for object-oriented) methods may be invoked at each call site within a program. Rich theoretical results exist studying control flow analysis for Scheme-like languages, but implementations are often complex and specialized. By contrast, object-oriented languages (Java in particular) enjoy high-precision control-flow analyses that scale to thousands (or more) of lines of code. State-of-the-art implementations (such as DOOP on Souffle) structure the analysis using Horn-SAT (Datalog) to enable compilation of the analysis to efficient implementations such as high-performance relational algebra kernels. In this paper, we present an implementation of control-flow analysis for a significant subset of Scheme (including set!, call/cc, and primitive operations) using the Souffle Datalog engine. We present an evaluation on a worst-case term demonstrating the polynomial complexity of our m-CFA and remark upon scalability results using Souffle.
Variability-aware computing is the efficient application of programs to different sets of inputs that exhibit some variability. One example is program analyses applied to Software Product Lines (SPLs). In this paper we present the design and developm
In this paper, a new technique for the optimization of (partially) bound queries over disjunctive Datalog programs with stratified negation is presented. The technique exploits the propagation of query bindings and extends the Magic Set (MS) optimiza
The capacity and programmability of reconfigurable hardware such as FPGAs has improved steadily over the years, but they do not readily provide any mechanisms for monitoring or debugging running programs. Such mechanisms need to be written into the p
We study the problem of unlearning datapoints from a learnt model. The learner first receives a dataset $S$ drawn i.i.d. from an unknown distribution, and outputs a model $widehat{w}$ that performs well on unseen samples from the same distribution. H
Frama-C is a software analysis framework that provides a common infrastructure and a common behavioral specification language to plugins that implement various static and dynamic analyses of C programs. Most plugins do not support concurrency. We hav