Angello Astorga, Chiao Hsieh, P. Madhusudan, Sayan Mitra
{"title":"Perception Contracts for Safety of ML-Enabled Systems","authors":"Angello Astorga, Chiao Hsieh, P. Madhusudan, Sayan Mitra","doi":"10.1145/3622875","DOIUrl":"https://doi.org/10.1145/3622875","url":null,"abstract":"We introduce a novel notion of perception contracts to reason about the safety of controllers that interact with an environment using neural perception. Perception contracts capture errors in ground-truth estimations that preserve invariants when systems act upon them. We develop a theory of perception contracts and design symbolic learning algorithms for synthesizing them from a finite set of images. We implement our algorithms and evaluate synthesized perception contracts for two realistic vision-based control systems, a lane tracking system for an electric vehicle and an agricultural robot that follows crop rows. Our evaluation shows that our approach is effective in synthesizing perception contracts and generalizes well when evaluated over test images obtained during runtime monitoring of the systems.","PeriodicalId":20697,"journal":{"name":"Proceedings of the ACM on Programming Languages","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136112663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Adithya Murali, Lucas Peña, Ranjit Jhala, P. Madhusudan
{"title":"Complete First-Order Reasoning for Properties of Functional Programs","authors":"Adithya Murali, Lucas Peña, Ranjit Jhala, P. Madhusudan","doi":"10.1145/3622835","DOIUrl":"https://doi.org/10.1145/3622835","url":null,"abstract":"Several practical tools for automatically verifying functional programs (e.g., Liquid Haskell and Leon for Scala programs) rely on a heuristic based on unrolling recursive function definitions followed by quantifier-free reasoning using SMT solvers. We uncover foundational theoretical properties of this heuristic, revealing that it can be generalized and formalized as a technique that is in fact complete for reasoning with combined First-Order theories of algebraic datatypes and background theories, where background theories support decidable quantifier-free reasoning. The theory developed in this paper explains the efficacy of these heuristics when they succeed, explain why they fail when they fail, and the precise role that user help plays in making proofs succeed.","PeriodicalId":20697,"journal":{"name":"Proceedings of the ACM on Programming Languages","volume":"176 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136112805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
George Zakhour, Pascal Weisenburger, Guido Salvaneschi
{"title":"Type-Safe Dynamic Placement with First-Class Placed Values","authors":"George Zakhour, Pascal Weisenburger, Guido Salvaneschi","doi":"10.1145/3622873","DOIUrl":"https://doi.org/10.1145/3622873","url":null,"abstract":"Several distributed programming language solutions have been proposed to reason about the placement of data, computations, and peers interaction. Such solutions include, among the others, multitier programming, choreographic programming and various approaches based on behavioral types. These methods statically ensure safety properties thanks to a complete knowledge about placement of data and computation at compile time. In distributed systems, however, dynamic placement of computation and data is crucial to enable performance optimizations, e.g., driven by data locality or in presence of a number of other constraints such as security and compliance regarding data storage location. Unfortunately, in existing programming languages, dynamic placement conflicts with static reasoning about distributed programs: the flexibility required by dynamic placement hinders statically tracking the location of data and computation. In this paper we present Dyno, a programming language that enables static reasoning about dynamic placement. Dyno features a type system where values are explicitly placed, but in contrast to existing approaches, placed values are also first class, ensuring that they can be passed around and referred to from other locations. Building on top of this mechanism, we provide a novel interpretation of dynamic placement as unions of placement types. We formalize type soundness, placement correctness (as part of type soundness) and architecture conformance. In case studies and benchmarks, our evaluation shows that Dyno enables static reasoning about programs even in presence of dynamic placement, ensuring type safety and placement correctness of programs at negligible performance cost. We reimplement an Android app with ∼ 7 K LOC in Dyno, find a bug in the existing implementation, and show that the app's approach is representative of a common way to implement dynamic placement found in over 100 apps in a large open-source app store.","PeriodicalId":20697,"journal":{"name":"Proceedings of the ACM on Programming Languages","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136112807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chijin Zhou, Quan Zhang, Lihua Guo, Mingzhe Wang, Yu Jiang, Qing Liao, Zhiyong Wu, Shanshan Li, Bin Gu
{"title":"Towards Better Semantics Exploration for Browser Fuzzing","authors":"Chijin Zhou, Quan Zhang, Lihua Guo, Mingzhe Wang, Yu Jiang, Qing Liao, Zhiyong Wu, Shanshan Li, Bin Gu","doi":"10.1145/3622819","DOIUrl":"https://doi.org/10.1145/3622819","url":null,"abstract":"Web browsers exhibit rich semantics that enable a plethora of web-based functionalities. However, these intricate semantics present significant challenges for the implementation and testing of browsers. For example, fuzzing, a widely adopted testing technique, typically relies on handwritten context-free grammars (CFGs) for automatically generating inputs. However, these CFGs fall short in adequately modeling the complex semantics of browsers, resulting in generated inputs that cover only a portion of the semantics and are prone to semantic errors. In this paper, we present SaGe, an automated method that enhances browser fuzzing through the use of production-context sensitive grammars (PCSGs) incorporating semantic information. Our approach begins by extracting a rudimentary CFG from W3C standards and iteratively enhancing it to create a PCSG. The resulting PCSG enables our fuzzer to generate inputs that explore a broader range of browser semantics with a higher proportion of semantically-correct inputs. To evaluate the efficacy of SaGe, we conducted 24-hour fuzzing campaigns on mainstream browsers, including Chrome, Safari, and Firefox. Our approach demonstrated better performance compared to existing browser fuzzers, with a 6.03%-277.80% improvement in edge coverage, a 3.56%-161.71% boost in semantic correctness rate, twice the number of bugs discovered. Moreover, we identified 62 bugs across the three browsers, with 40 confirmed and 10 assigned CVEs.","PeriodicalId":20697,"journal":{"name":"Proceedings of the ACM on Programming Languages","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136114709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Spirea: A Mechanized Concurrent Separation Logic for Weak Persistent Memory","authors":"Simon Friis Vindum, Lars Birkedal","doi":"10.1145/3622820","DOIUrl":"https://doi.org/10.1145/3622820","url":null,"abstract":"Weak persistent memory (a.k.a. non-volatile memory) is an emerging technology that offers fast byte-addressable durable main memory. A wealth of algorithms and libraries has been developed to explore this exciting technology. As noted by others, this has led to a significant verification gap. Towards closing this gap, we present Spirea, the first concurrent separation logic for verification of programs under a weak persistent memory model. Spirea is based on the Iris and Perennial verification frameworks, and by combining features from these logics with novel techniques it supports high-level modular reasoning about crash-safe and thread-safe programs and libraries. Spirea is fully mechanized in the Coq proof assistant and allows for interactive development of proofs with the Iris Proof Mode. We use Spirea to verify several challenging examples with modular specifications. We show how our logic can verify thread-safety and crash-safety of non-blocking durable data structures with null-recovery, in particular the Treiber stack and the Michael-Scott queue adapted to persistent memory. This is the first time durable data structures have been verified with a program logic.","PeriodicalId":20697,"journal":{"name":"Proceedings of the ACM on Programming Languages","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136115199","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Mechanizing Session-Types using a Structural View: Enforcing Linearity without Linearity","authors":"Chuta Sano, Ryan Kavanagh, Brigitte Pientka","doi":"10.1145/3622810","DOIUrl":"https://doi.org/10.1145/3622810","url":null,"abstract":"Session types employ a linear type system that ensures that communication channels cannot be implicitly copied or discarded. As a result, many mechanizations of these systems require modeling channel contexts and carefully ensuring that they treat channels linearly. We demonstrate a technique that localizes linearity conditions as additional predicates embedded within type judgments, which allows us to use structural typing contexts instead of linear ones. This technique is especially relevant when leveraging (weak) higher-order abstract syntax to handle channel mobility and the intricate binding structures that arise in session-typed systems. Following this approach, we mechanize a session-typed system based on classical linear logic and its type preservation proof in the proof assistant Beluga, which uses the logical framework LF as its encoding language. We also prove adequacy for our encoding. This shows the tractability and effectiveness of our approach in modelling substructural systems such as session-typed languages.","PeriodicalId":20697,"journal":{"name":"Proceedings of the ACM on Programming Languages","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136115395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Simple Reference Immutability for System F <sub><:</sub>","authors":"Edward Lee, Ondřej Lhoták","doi":"10.1145/3622828","DOIUrl":"https://doi.org/10.1145/3622828","url":null,"abstract":"Reference immutability is a type based technique for taming mutation that has long been studied in the context of object-oriented languages, like Java. Recently, though, languages like Scala have blurred the lines between functional programming languages and object oriented programming languages. We explore how reference immutability interacts with features commonly found in these hybrid languages, in particular with higher-order functions – polymorphism – and subtyping. We construct a calculus System F<:M which encodes a reference immutability system as a simple extension of System F<: and prove that it satisfies the standard soundness and immutability safety properties.","PeriodicalId":20697,"journal":{"name":"Proceedings of the ACM on Programming Languages","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136115977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Formal Abstractions for Packet Scheduling","authors":"Anshuman Mohan, Yunhe Liu, Nate Foster, Tobias Kappé, Dexter Kozen","doi":"10.1145/3622845","DOIUrl":"https://doi.org/10.1145/3622845","url":null,"abstract":"Early programming models for software-defined networking (SDN) focused on basic features for controlling network-wide forwarding paths, but more recent work has considered richer features, such as packet scheduling and queueing, that affect performance. In particular, PIFO trees , proposed by Sivaraman et al., offer a flexible and efficient primitive for programmable packet scheduling. Prior work has shown that PIFO trees can express a wide range of practical algorithms including strict priority, weighted fair queueing, and hierarchical schemes. However, the semantic properties of PIFO trees are not well understood. This paper studies PIFO trees from a programming language perspective. We formalize the syntax and semantics of PIFO trees in an operational model that decouples the scheduling policy running on a tree from the topology of the tree. Building on this formalization, we develop compilation algorithms that allow the behavior of a PIFO tree written against one topology to be realized using a tree with a different topology. Such a compiler could be used to optimize an implementation of PIFO trees, or realize a logical PIFO tree on a target with a fixed topology baked into the hardware. To support experimentation, we develop a software simulator for PIFO trees, and we present case studies illustrating its behavior on standard and custom algorithms.","PeriodicalId":20697,"journal":{"name":"Proceedings of the ACM on Programming Languages","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136112410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Narges Shadab, Pritam Gharat, Shrey Tiwari, Michael D. Ernst, Martin Kellogg, Shuvendu K. Lahiri, Akash Lal, Manu Sridharan
{"title":"Inference of Resource Management Specifications","authors":"Narges Shadab, Pritam Gharat, Shrey Tiwari, Michael D. Ernst, Martin Kellogg, Shuvendu K. Lahiri, Akash Lal, Manu Sridharan","doi":"10.1145/3622858","DOIUrl":"https://doi.org/10.1145/3622858","url":null,"abstract":"A resource leak occurs when a program fails to free some finite resource after it is no longer needed. Such leaks are a significant cause of real-world crashes and performance problems. Recent work proposed an approach to prevent resource leaks based on checking resource management specifications. A resource management specification expresses how the program allocates resources, passes them around, and releases them; it also tracks the ownership relationship between objects and resources, and aliasing relationships between objects. While this specify-and-verify approach has several advantages compared to prior techniques, the need to manually write annotations presents a significant barrier to its practical adoption. This paper presents a novel technique to automatically infer a resource management specification for a program, broadening the applicability of specify-and-check verification for resource leaks. Inference in this domain is challenging because resource management specifications differ significantly in nature from the types that most inference techniques target. Further, for practical effectiveness, we desire a technique that can infer the resource management specification intended by the developer, even in cases when the code does not fully adhere to that specification. We address these challenges through a set of inference rules carefully designed to capture real-world coding patterns, yielding an effective fixed-point-based inference algorithm. We have implemented our inference algorithm in two different systems, targeting programs written in Java and C#. In an experimental evaluation, our technique inferred 85.5% of the annotations that programmers had written manually for the benchmarks. Further, the verifier issued nearly the same rate of false alarms with the manually-written and automatically-inferred annotations.","PeriodicalId":20697,"journal":{"name":"Proceedings of the ACM on Programming Languages","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136112414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Data Extraction via Semantic Regular Expression Synthesis","authors":"Qiaochu Chen, Arko Banerjee, Çağatay Demiralp, Greg Durrett, Işıl Dillig","doi":"10.1145/3622863","DOIUrl":"https://doi.org/10.1145/3622863","url":null,"abstract":"Many data extraction tasks of practical relevance require not only syntactic pattern matching but also semantic reasoning about the content of the underlying text. While regular expressions are very well suited for tasks that require only syntactic pattern matching, they fall short for data extraction tasks that involve both a syntactic and semantic component. To address this issue, we introduce semantic regexes, a generalization of regular expressions that facilitates combined syntactic and semantic reasoning about textual data. We also propose a novel learning algorithm that can synthesize semantic regexes from a small number of positive and negative examples. Our proposed learning algorithm uses a combination of neural sketch generation and compositional type-directed synthesis for fast and effective generalization from a small number of examples. We have implemented these ideas in a new tool called Smore and evaluated it on representative data extraction tasks involving several textual datasets. Our evaluation shows that semantic regexes can better support complex data extraction tasks than standard regular expressions and that our learning algorithm significantly outperforms existing tools, including state-of-the-art neural networks and program synthesis tools.","PeriodicalId":20697,"journal":{"name":"Proceedings of the ACM on Programming Languages","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136112534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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