arXiv subjects

Mark Santolucito

Publications and source records attributed to Mark Santolucito.

22 records · Page 2Linked to original sources

arXiv2019

Synthesizing Functional Reactive Programs

Functional Reactive Programming (FRP) is a paradigm that has simplified the construction of reactive programs. There are many libraries that implement incarnations of FRP, using abstractions such as Applicative, Monads, and Arrows. However, finding a good control flow, that correctly manages state and switches behaviors at the right times, still poses a major challenge to developers. An attractive alternative is specifying the behavior instead of programming it, as made possible by the recently developed logic: Temporal Stream Logic (TSL). However, it has not been explored so far how Control Flow Models (CFMs), as synthesized from TSL specifications, can be turned into executable code that is compatible with libraries building on FRP. We bridge this gap, by showing that CFMs are indeed a suitable formalism to be turned into Applicative, Monadic, and Arrowized FRP. We demonstrate the effectiveness of our translations on a real-world kitchen timer application, which we translate to a desktop application using the Arrowized FRP library Yampa, a web application using the Monadic threepenny-gui library, and to hardware using the Applicative hardware description language ClaSH.

cs.PL↗

arXiv2019

Temporal Stream Logic: Synthesis beyond the Bools

Reactive systems that operate in environments with complex data, such as mobile apps or embedded controllers with many sensors, are difficult to synthesize. Synthesis tools usually fail for such systems because the state space resulting from the discretization of the data is too large. We introduce TSL, a new temporal logic that separates control and data. We provide a CEGAR-based synthesis approach for the construction of implementations that are guaranteed to satisfy a TSL specification for all possible instantiations of the data processing functions. TSL provides an attractive trade-off for synthesis. On the one hand, synthesis from TSL, unlike synthesis from standard temporal logics, is undecidable in general. On the other hand, however, synthesis from TSL is scalable, because it is independent of the complexity of the handled data. Among other benchmarks, we have successfully synthesized a music player Android app and a controller for an autonomous vehicle in the Open Race Car Simulator (TORCS.)

cs.LO↗

arXiv2018

Statically Verifying Continuous Integration Configurations

Continuous Integration (CI) testing is a popular software development technique that allows developers to easily check that their code can build successfully and pass tests across various system environments. In order to use a CI platform, a developer must include a set of configuration files to a code repository for specifying build conditions. Incorrect configuration settings lead to CI build failures, which can take hours to run, wasting valuable developer time and delaying product release dates. Debugging CI configurations is challenging because users must manage configurations for the build across many system environments, to which they may not have local access. Thus, the only way to check a CI configuration is to push a commit and wait for the build result. To address this problem, we present the first approach, VeriCI, for statically checking for errors in a given CI configuration before the developer pushes a commit to build on the CI server. Our key insight is that the repositories in a CI environment contain lists of build histories which offer the time-aware repository build status. Driven by this insight, we introduce the Misclassification Guided Abstraction Refinement (MiGAR) loop that automates part of the learning process across the heterogeneous build environments in CI. We then use decision tree learning to generate constraints on the CI configuration that must hold for a build to succeed by training on a large history of continuous integration repository build results. We evaluate VeriCI on real-world data from GitHub and find that we have 83% accuracy of predicting a build failure.

cs.SE↗

arXiv2018

Vehicle Platooning Simulations with Functional Reactive Programming

Functional languages have provided major benefits to the verification community. Although features such as purity, a strong type system, and computational abstractions can help guide programmers away from costly errors, these can present challenges when used in a reactive system. Functional Reactive Programming is a paradigm that allows users the benefits of functional languages and an easy interface to a reactive environment. We present a tool for building autonomous vehicle controllers in FRP using Haskell.

cs.PL↗