We present Solythesis, a source to source Solidity compiler which takes a smart contract code and a user specified invariant as the input and produces an instrumented contract that rejects all transactions that violate the invariant. The design of Solythesis is driven by our observation that the consensus protocol and the storage layer are the primary and the secondary performance bottlenecks of Ethereum, respectively. Solythesis operates with our novel delta update and delta check techniques to minimize the overhead caused by the instrumented storage access statements. Our experimental results validate our hypothesis that the overhead of runtime validation, which is often too expensive for other domains, is in fact negligible for smart contracts. The CPU overhead of Solythesis is only 0.1% on average for our 23 benchmark contracts.
{"title":"Securing smart contract with runtime validation","authors":"Ao Li, Jemin Andrew Choi, Fan Long","doi":"10.1145/3385412.3385982","DOIUrl":"https://doi.org/10.1145/3385412.3385982","url":null,"abstract":"We present Solythesis, a source to source Solidity compiler which takes a smart contract code and a user specified invariant as the input and produces an instrumented contract that rejects all transactions that violate the invariant. The design of Solythesis is driven by our observation that the consensus protocol and the storage layer are the primary and the secondary performance bottlenecks of Ethereum, respectively. Solythesis operates with our novel delta update and delta check techniques to minimize the overhead caused by the instrumented storage access statements. Our experimental results validate our hypothesis that the overhead of runtime validation, which is often too expensive for other domains, is in fact negligible for smart contracts. The CPU overhead of Solythesis is only 0.1% on average for our 23 benchmark contracts.","PeriodicalId":20580,"journal":{"name":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83591917","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}
The real numbers are pervasive, both in daily life, and in mathematics. Students spend much time studying their properties. Yet computers and programming languages generally provide only an approximation geared towards performance, at the expense of many of the nice properties we were taught in high school. Although this is entirely appropriate for many applications, particularly those that are sensitive to arithmetic performance in the usual sense, we argue that there are others where it is a poor choice. If arithmetic computations and result are directly exposed to human users who are not floating point experts, floating point approximations tend to be viewed as bugs. For applications such as calculators, spreadsheets, and various verification tasks, the cost of precision sacrifices is high, and the performance benefit is often not critical. We argue that previous attempts to provide accurate and understandable results for such applications using the recursive reals were great steps in the right direction, but they do not suffice. Comparing recursive reals diverges if they are equal. In many cases, comparison of numbers, including equal ones, is both important, particularly in simple cases, and intractable in the general case. We propose an API for a real number type that explicitly provides decidable equality in the easy common cases, in which it is often unnatural not to. We describe a surprisingly compact and simple implementation in detail. The approach relies heavily on classical number theory results. We demonstrate the utility of such a facility in two applications: testing floating point functions, and to implement arithmetic in Google's Android calculator application.
{"title":"Towards an API for the real numbers","authors":"H. Boehm","doi":"10.1145/3385412.3386037","DOIUrl":"https://doi.org/10.1145/3385412.3386037","url":null,"abstract":"The real numbers are pervasive, both in daily life, and in mathematics. Students spend much time studying their properties. Yet computers and programming languages generally provide only an approximation geared towards performance, at the expense of many of the nice properties we were taught in high school. Although this is entirely appropriate for many applications, particularly those that are sensitive to arithmetic performance in the usual sense, we argue that there are others where it is a poor choice. If arithmetic computations and result are directly exposed to human users who are not floating point experts, floating point approximations tend to be viewed as bugs. For applications such as calculators, spreadsheets, and various verification tasks, the cost of precision sacrifices is high, and the performance benefit is often not critical. We argue that previous attempts to provide accurate and understandable results for such applications using the recursive reals were great steps in the right direction, but they do not suffice. Comparing recursive reals diverges if they are equal. In many cases, comparison of numbers, including equal ones, is both important, particularly in simple cases, and intractable in the general case. We propose an API for a real number type that explicitly provides decidable equality in the easy common cases, in which it is often unnatural not to. We describe a surprisingly compact and simple implementation in detail. The approach relies heavily on classical number theory results. We demonstrate the utility of such a facility in two applications: testing floating point functions, and to implement arithmetic in Google's Android calculator application.","PeriodicalId":20580,"journal":{"name":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79261607","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}
We present λPSI, the first probabilistic programming language and system that supports higher-order exact inference for probabilistic programs with first-class functions, nested inference and discrete, continuous and mixed random variables. λPSI’s solver is based on symbolic reasoning and computes the exact distribution represented by a program. We show that λPSI is practically effective—it automatically computes exact distributions for a number of interesting applications, from rational agents to information theory, many of which could so far only be handled approximately.
{"title":"λPSI: exact inference for higher-order probabilistic programs","authors":"Timon Gehr, Samuel Steffen, Martin T. Vechev","doi":"10.1145/3385412.3386006","DOIUrl":"https://doi.org/10.1145/3385412.3386006","url":null,"abstract":"We present λPSI, the first probabilistic programming language and system that supports higher-order exact inference for probabilistic programs with first-class functions, nested inference and discrete, continuous and mixed random variables. λPSI’s solver is based on symbolic reasoning and computes the exact distribution represented by a program. We show that λPSI is practically effective—it automatically computes exact distributions for a number of interesting applications, from rational agents to information theory, many of which could so far only be handled approximately.","PeriodicalId":20580,"journal":{"name":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81028007","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}
Varot Premtoon, James Koppel, Armando Solar-Lezama
We present a new approach to semantic code search based on equational reasoning, and the Yogo tool implementing this approach. Our approach works by considering not only the dataflow graph of a function, but also the dataflow graphs of all equivalent functions reachable via a set of rewrite rules. In doing so, it can recognize an operation even if it uses alternate APIs, is in a different but mathematically-equivalent form, is split apart with temporary variables, or is interleaved with other code. Furthermore, it can recognize when code is an instance of some higher-level concept such as iterating through a file. Because of this, from a single query, Yogo can find equivalent code in multiple languages. Our evaluation further shows the utility of Yogo beyond code search: encoding a buggy pattern as a Yogo query, we found a bug in Oracle’s Graal compiler which had been missed by a hand-written static analyzer designed for that exact kind of bug. Yogo is built on the Cubix multi-language infrastructure, and currently supports Java and Python.
{"title":"Semantic code search via equational reasoning","authors":"Varot Premtoon, James Koppel, Armando Solar-Lezama","doi":"10.1145/3385412.3386001","DOIUrl":"https://doi.org/10.1145/3385412.3386001","url":null,"abstract":"We present a new approach to semantic code search based on equational reasoning, and the Yogo tool implementing this approach. Our approach works by considering not only the dataflow graph of a function, but also the dataflow graphs of all equivalent functions reachable via a set of rewrite rules. In doing so, it can recognize an operation even if it uses alternate APIs, is in a different but mathematically-equivalent form, is split apart with temporary variables, or is interleaved with other code. Furthermore, it can recognize when code is an instance of some higher-level concept such as iterating through a file. Because of this, from a single query, Yogo can find equivalent code in multiple languages. Our evaluation further shows the utility of Yogo beyond code search: encoding a buggy pattern as a Yogo query, we found a bug in Oracle’s Graal compiler which had been missed by a hand-written static analyzer designed for that exact kind of bug. Yogo is built on the Cubix multi-language infrastructure, and currently supports Java and Python.","PeriodicalId":20580,"journal":{"name":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81950361","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}
Brian Suchy, Simone Campanoni, Nikos Hardavellas, P. Dinda
Virtual memory is a critical abstraction in modern computer systems. Its common model, paging, is currently seeing considerable innovation, yet its implementations continue to be co-designs between power-hungry/latency-adding hardware (e.g., TLBs, pagewalk caches, pagewalkers, etc) and software (the OS kernel). We make a case for a new model for virtual memory, compiler- and runtime-based address translation (CARAT), which instead is a co-design between the compiler and the OS kernel. CARAT can operate without any hardware support, although it could also be retrofitted into a traditional paging model, and could leverage simpler hardware support. CARAT uses compile-time transformations and optimizations combined with tightly-coupled runtime/kernel interaction to generate programs that run efficiently in a physical address space, but nonetheless allow the kernel to maintain protection and dynamically manage physical memory similar to what is possible using traditional virtual memory. We argue for the feasibility of CARAT through an empirical study of application characteristics and kernel behavior, as well as through the design, implementation, and performance evaluation of a CARAT prototype. Because our prototype works at the IR level (in particular, via LLVM bitcode), it can be applied to most C and C++ programs with minimal or no restrictions.
{"title":"CARAT: a case for virtual memory through compiler- and runtime-based address translation","authors":"Brian Suchy, Simone Campanoni, Nikos Hardavellas, P. Dinda","doi":"10.1145/3385412.3385987","DOIUrl":"https://doi.org/10.1145/3385412.3385987","url":null,"abstract":"Virtual memory is a critical abstraction in modern computer systems. Its common model, paging, is currently seeing considerable innovation, yet its implementations continue to be co-designs between power-hungry/latency-adding hardware (e.g., TLBs, pagewalk caches, pagewalkers, etc) and software (the OS kernel). We make a case for a new model for virtual memory, compiler- and runtime-based address translation (CARAT), which instead is a co-design between the compiler and the OS kernel. CARAT can operate without any hardware support, although it could also be retrofitted into a traditional paging model, and could leverage simpler hardware support. CARAT uses compile-time transformations and optimizations combined with tightly-coupled runtime/kernel interaction to generate programs that run efficiently in a physical address space, but nonetheless allow the kernel to maintain protection and dynamically manage physical memory similar to what is possible using traditional virtual memory. We argue for the feasibility of CARAT through an empirical study of application characteristics and kernel behavior, as well as through the design, implementation, and performance evaluation of a CARAT prototype. Because our prototype works at the IR level (in particular, via LLVM bitcode), it can be applied to most C and C++ programs with minimal or no restrictions.","PeriodicalId":20580,"journal":{"name":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81005032","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}
All pointer-based nonblocking concurrent data structures should deal with the problem of safe memory reclamation: before reclaiming a memory block, a thread should ensure no other threads hold a local pointer to the block that may later be dereferenced. Various safe memory reclamation schemes have been proposed in the literature, but none of them satisfy the following desired properties at the same time: (i) robust: a non-cooperative thread does not prevent the other threads from reclaiming an unbounded number of blocks; (ii) fast: it does not incur significant time overhead; (iii) compact: it does not incur significant space overhead; (iv) self-contained: it neither relies on special hardware/OS supports nor intrusively affects execution environments; and (v) widely applicable: it supports many data structures. We introduce PEBR, which we believe is the first scheme that satisfies all the properties above. PEBR is inspired by Snowflake’s hybrid design of pointer- and epoch-based reclamation schemes (PBR and EBR, resp.) that is mostly robust, fast, and compact but neither self-contained nor widely applicable. To achieve self-containedness, we design algorithms using only the standard C/C++ concurrency features and process-wide memory fence. To achieve wide applicability, we characterize PEBR’s requirement for safe reclamation that is satisfied by a variety of data structures, including Harris’s and Harris-Herlihy-Shavit’s lists that are not supported by PBR. We experimentally evaluate whether PEBR is fast and robust using microbenchmarks, for which PEBR performs comparably to the state-of-the-art schemes.
{"title":"A marriage of pointer- and epoch-based reclamation","authors":"Jeehoon Kang, Jaehwang Jung","doi":"10.1145/3385412.3385978","DOIUrl":"https://doi.org/10.1145/3385412.3385978","url":null,"abstract":"All pointer-based nonblocking concurrent data structures should deal with the problem of safe memory reclamation: before reclaiming a memory block, a thread should ensure no other threads hold a local pointer to the block that may later be dereferenced. Various safe memory reclamation schemes have been proposed in the literature, but none of them satisfy the following desired properties at the same time: (i) robust: a non-cooperative thread does not prevent the other threads from reclaiming an unbounded number of blocks; (ii) fast: it does not incur significant time overhead; (iii) compact: it does not incur significant space overhead; (iv) self-contained: it neither relies on special hardware/OS supports nor intrusively affects execution environments; and (v) widely applicable: it supports many data structures. We introduce PEBR, which we believe is the first scheme that satisfies all the properties above. PEBR is inspired by Snowflake’s hybrid design of pointer- and epoch-based reclamation schemes (PBR and EBR, resp.) that is mostly robust, fast, and compact but neither self-contained nor widely applicable. To achieve self-containedness, we design algorithms using only the standard C/C++ concurrency features and process-wide memory fence. To achieve wide applicability, we characterize PEBR’s requirement for safe reclamation that is satisfied by a variety of data structures, including Harris’s and Harris-Herlihy-Shavit’s lists that are not supported by PBR. We experimentally evaluate whether PEBR is fast and robust using microbenchmarks, for which PEBR performs comparably to the state-of-the-art schemes.","PeriodicalId":20580,"journal":{"name":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75229442","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}
Nick Giannarakis, Devon Loehr, Ryan Beckett, D. Walker
Network misconfiguration has caused a raft of high-profile outages over the past decade, spurring researchers to develop a variety of network analysis and verification tools. Unfortunately, developing and maintaining such tools is an enormous challenge due to the complexity of network configuration languages. Inspired by work on intermediate languages for verification such as Boogie and Why3, we develop NV, an intermediate language for verification of network control planes. NV carefully walks the line between expressiveness and tractability, making it possible to build models for a practical subset of real protocols and their configurations, and also facilitate rapid development of tools that outperform state-of-the-art simulators (seconds vs minutes) and verifiers (often 10x faster). Furthermore, we show that it is possible to develop novel analyses just by writing new NV programs. In particular, we implement a new fault-tolerance analysis that scales to far larger networks than existing tools.
{"title":"NV: an intermediate language for verification of network control planes","authors":"Nick Giannarakis, Devon Loehr, Ryan Beckett, D. Walker","doi":"10.1145/3385412.3386019","DOIUrl":"https://doi.org/10.1145/3385412.3386019","url":null,"abstract":"Network misconfiguration has caused a raft of high-profile outages over the past decade, spurring researchers to develop a variety of network analysis and verification tools. Unfortunately, developing and maintaining such tools is an enormous challenge due to the complexity of network configuration languages. Inspired by work on intermediate languages for verification such as Boogie and Why3, we develop NV, an intermediate language for verification of network control planes. NV carefully walks the line between expressiveness and tractability, making it possible to build models for a practical subset of real protocols and their configurations, and also facilitate rapid development of tools that outperform state-of-the-art simulators (seconds vs minutes) and verifiers (often 10x faster). Furthermore, we show that it is possible to develop novel analyses just by writing new NV programs. In particular, we implement a new fault-tolerance analysis that scales to far larger networks than existing tools.","PeriodicalId":20580,"journal":{"name":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74756099","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}
Rodrigo C. O. Rocha, Pavlos Petoumenos, Zheng Wang, M. Cole, Hugh Leather
Function merging is an important optimization for reducing code size. This technique eliminates redundant code across functions by merging them into a single function. While initially limited to identical or trivially similar functions, the most recent approach can identify all merging opportunities in arbitrary pairs of functions. However, this approach has a serious limitation which prevents it from reaching its full potential. Because it cannot handle phi-nodes, the state-of-the-art applies register demotion to eliminate them before applying its core algorithm. While a superficially minor workaround, this has a three-fold negative effect: by artificially lengthening the instruction sequences to be aligned, it hinders the identification of mergeable instruction; it prevents a vast number of functions from being profitably merged; it increases compilation overheads, both in terms of compile-time and memory usage. We present SalSSA, a novel approach that fully supports the SSA form, removing any need for register demotion. By doing so, we notably increase the number of profitably merged functions. We implement SalSSA in LLVM and apply it to the SPEC 2006 and 2017 suites. Experimental results show that our approach delivers on average, 7.9% to 9.7% reduction on the final size of the compiled code. This translates to around 2x more code size reduction over the state-of-the-art. Moreover, as a result of aligning shorter sequences of instructions and reducing the number of wasteful merge operations, our new approach incurs an average compile-time overhead of only 5%, 3x less than the state-of-the-art, while also reducing memory usage by over 2x.
{"title":"Effective function merging in the SSA form","authors":"Rodrigo C. O. Rocha, Pavlos Petoumenos, Zheng Wang, M. Cole, Hugh Leather","doi":"10.1145/3385412.3386030","DOIUrl":"https://doi.org/10.1145/3385412.3386030","url":null,"abstract":"Function merging is an important optimization for reducing code size. This technique eliminates redundant code across functions by merging them into a single function. While initially limited to identical or trivially similar functions, the most recent approach can identify all merging opportunities in arbitrary pairs of functions. However, this approach has a serious limitation which prevents it from reaching its full potential. Because it cannot handle phi-nodes, the state-of-the-art applies register demotion to eliminate them before applying its core algorithm. While a superficially minor workaround, this has a three-fold negative effect: by artificially lengthening the instruction sequences to be aligned, it hinders the identification of mergeable instruction; it prevents a vast number of functions from being profitably merged; it increases compilation overheads, both in terms of compile-time and memory usage. We present SalSSA, a novel approach that fully supports the SSA form, removing any need for register demotion. By doing so, we notably increase the number of profitably merged functions. We implement SalSSA in LLVM and apply it to the SPEC 2006 and 2017 suites. Experimental results show that our approach delivers on average, 7.9% to 9.7% reduction on the final size of the compiled code. This translates to around 2x more code size reduction over the state-of-the-art. Moreover, as a result of aligning shorter sequences of instructions and reducing the number of wasteful merge operations, our new approach incurs an average compile-time overhead of only 5%, 3x less than the state-of-the-art, while also reducing memory usage by over 2x.","PeriodicalId":20580,"journal":{"name":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85027001","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}
Sotiris Apostolakis, Ziyang Xu, Zujun Tan, Greg Chan, Simone Campanoni, David I. August
Program analysis determines the potential dataflow and control flow relationships among instructions so that compiler optimizations can respect these relationships to transform code correctly. Since many of these relationships rarely or never occur, speculative optimizations assert they do not exist while optimizing the code. To preserve correctness, speculative optimizations add validation checks to activate recovery code when these assertions prove untrue. This approach results in many missed opportunities because program analysis and thus other optimizations remain unaware of the full impact of these dynamically-enforced speculative assertions. To address this problem, this paper presents SCAF, a Speculation-aware Collaborative dependence Analysis Framework. SCAF learns of available speculative assertions via profiling, computes their full impact on memory dependence analysis, and makes this resulting information available for all code optimizations. SCAF is modular (adding new analysis modules is easy) and collaborative (modules cooperate to produce a result more precise than the confluence of all individual results). Relative to the best prior speculation-aware dependence analysis technique, by computing the full impact of speculation on memory dependence analysis, SCAF dramatically reduces the need for expensive-to-validate memory speculation in the hot loops of all 16 evaluated C/C++ SPEC benchmarks.
程序分析确定指令之间潜在的数据流和控制流关系，以便编译器优化能够尊重这些关系以正确转换代码。由于其中许多关系很少或从未发生，因此推测性优化在优化代码时断言它们不存在。为了保持正确性，推测性优化添加了验证检查，以便在这些断言被证明不正确时激活恢复代码。这种方法导致许多错失的机会，因为程序分析和其他优化仍然没有意识到这些动态强制推测断言的全部影响。为了解决这个问题，本文提出了SCAF，一个推测感知的协作依赖分析框架。SCAF通过分析了解可用的推测断言，计算它们对内存依赖性分析的全部影响，并使这些结果信息可用于所有代码优化。SCAF是模块化的(添加新的分析模块很容易)和协作的(模块合作产生的结果比所有单个结果的汇合更精确)。相对于最好的预先推测依赖性分析技术，通过计算推测对内存依赖性分析的全部影响，SCAF显著减少了在所有16个评估的C/ c++ SPEC基准的热循环中验证昂贵的内存推测的需要。
{"title":"SCAF: a speculation-aware collaborative dependence analysis framework","authors":"Sotiris Apostolakis, Ziyang Xu, Zujun Tan, Greg Chan, Simone Campanoni, David I. August","doi":"10.1145/3385412.3386028","DOIUrl":"https://doi.org/10.1145/3385412.3386028","url":null,"abstract":"Program analysis determines the potential dataflow and control flow relationships among instructions so that compiler optimizations can respect these relationships to transform code correctly. Since many of these relationships rarely or never occur, speculative optimizations assert they do not exist while optimizing the code. To preserve correctness, speculative optimizations add validation checks to activate recovery code when these assertions prove untrue. This approach results in many missed opportunities because program analysis and thus other optimizations remain unaware of the full impact of these dynamically-enforced speculative assertions. To address this problem, this paper presents SCAF, a Speculation-aware Collaborative dependence Analysis Framework. SCAF learns of available speculative assertions via profiling, computes their full impact on memory dependence analysis, and makes this resulting information available for all code optimizations. SCAF is modular (adding new analysis modules is easy) and collaborative (modules cooperate to produce a result more precise than the confluence of all individual results). Relative to the best prior speculation-aware dependence analysis technique, by computing the full impact of speculation on memory dependence analysis, SCAF dramatically reduces the need for expensive-to-validate memory speculation in the hot loops of all 16 evaluated C/C++ SPEC benchmarks.","PeriodicalId":20580,"journal":{"name":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89929235","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}
We introduce Semantic Fusion, a general, effective methodology for validating Satisfiability Modulo Theory (SMT) solvers. Our key idea is to fuse two existing equisatisfiable (i.e., both satisfiable or unsatisfiable) formulas into a new formula that combines the structures of its ancestors in a novel manner and preserves the satisfiability by construction. This fused formula is then used for validating SMT solvers. We realized Semantic Fusion as YinYang, a practical SMT solver testing tool. During four months of extensive testing, YinYang has found 45 confirmed, unique bugs in the default arithmetic and string solvers of Z3 and CVC4, the two state-of-the-art SMT solvers. Among these, 41 have already been fixed by the developers. The majority (29/45) of these bugs expose critical soundness issues. Our bug reports and testing effort have been well-appreciated by SMT solver developers.
{"title":"Validating SMT solvers via semantic fusion","authors":"Dominik Winterer, Chengyu Zhang, Z. Su","doi":"10.1145/3385412.3385985","DOIUrl":"https://doi.org/10.1145/3385412.3385985","url":null,"abstract":"We introduce Semantic Fusion, a general, effective methodology for validating Satisfiability Modulo Theory (SMT) solvers. Our key idea is to fuse two existing equisatisfiable (i.e., both satisfiable or unsatisfiable) formulas into a new formula that combines the structures of its ancestors in a novel manner and preserves the satisfiability by construction. This fused formula is then used for validating SMT solvers. We realized Semantic Fusion as YinYang, a practical SMT solver testing tool. During four months of extensive testing, YinYang has found 45 confirmed, unique bugs in the default arithmetic and string solvers of Z3 and CVC4, the two state-of-the-art SMT solvers. Among these, 41 have already been fixed by the developers. The majority (29/45) of these bugs expose critical soundness issues. Our bug reports and testing effort have been well-appreciated by SMT solver developers.","PeriodicalId":20580,"journal":{"name":"Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81368936","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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