Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation最新文献_第4页

Armada: low-effort verification of high-performance concurrent programs Armada:高性能并发程序的低工作量验证

Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation Pub Date : 2020-06-06 DOI: 10.1145/3385412.3385971

Jacob R. Lorch, Yixuan Chen, Manos Kapritsos, Bryan Parno, S. Qadeer, Upamanyu Sharma, James R. Wilcox, Xueyuan Zhao

引用次数: 31

Towards a verified range analysis for JavaScript JITs 迈向JavaScript jit的验证范围分析

Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation Pub Date : 2020-06-06 DOI: 10.1145/3385412.3385968

Fraser Brown, John Renner, Andres Nötzli, Sorin Lerner, H. Shacham, D. Stefan

引用次数: 10

Reconciling enumerative and deductive program synthesis 调和枚举和演绎程序综合

Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation Pub Date : 2020-06-06 DOI: 10.1145/3385412.3386027

Kangjing Huang, Xiaokang Qiu, Peiyuan Shen, Yanjun Wang

{"title":"Reconciling enumerative and deductive program synthesis","authors":"Kangjing Huang, Xiaokang Qiu, Peiyuan Shen, Yanjun Wang","doi":"10.1145/3385412.3386027","DOIUrl":"https://doi.org/10.1145/3385412.3386027","url":null,"abstract":"Syntax-guided synthesis (SyGuS) aims to find a program satisfying semantic specification as well as user-provided structural hypotheses. There are two main synthesis approaches: enumerative synthesis, which repeatedly enumerates possible candidate programs and checks their correctness, and deductive synthesis, which leverages a symbolic procedure to construct implementations from specifications. Neither approach is strictly better than the other: automated deductive synthesis is usually very efficient but only works for special grammars or applications; enumerative synthesis is very generally applicable but limited in scalability. In this paper, we propose a cooperative synthesis technique for SyGuS problems with the conditional linear integer arithmetic (CLIA) background theory, as a novel integration of the two approaches, combining the best of the two worlds. The technique exploits several novel divide-and-conquer strategies to split a large synthesis problem to smaller subproblems. The subproblems are solved separately and their solutions are combined to form a final solution. The technique integrates two synthesis engines: a pure deductive component that can efficiently solve some problems, and a height-based enumeration algorithm that can handle arbitrary grammar. We implemented the cooperative synthesis technique, and evaluated it on a wide range of benchmarks. Experiments showed that our technique can solve many challenging synthesis problems not possible before, and tends to be more scalable than state-of-the-art synthesis algorithms.","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":"75707729","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}

引用次数: 30

Static analysis of Java enterprise applications: frameworks and caches, the elephants in the room Java企业应用的静态分析:框架和缓存，房间里的大象

Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation Pub Date : 2020-06-06 DOI: 10.1145/3385412.3386026

A. Antoniadis, Nikos Filippakis, Paddy Krishnan, R. Ramesh, N. Allen, Y. Smaragdakis

{"title":"Static analysis of Java enterprise applications: frameworks and caches, the elephants in the room","authors":"A. Antoniadis, Nikos Filippakis, Paddy Krishnan, R. Ramesh, N. Allen, Y. Smaragdakis","doi":"10.1145/3385412.3386026","DOIUrl":"https://doi.org/10.1145/3385412.3386026","url":null,"abstract":"Enterprise applications are a major success domain of Java, and Java is the default setting for much modern static analysis research. It would stand to reason that high-quality static analysis of Java enterprise applications would be commonplace, but this is far from true. Major analysis frameworks feature virtually no support for enterprise applications and offer analyses that are woefully incomplete and vastly imprecise, when at all scalable. In this work, we present two techniques for drastically enhancing the completeness and precision of static analysis for Java enterprise applications. The first technique identifies domain-specific concepts underlying all enterprise application frameworks, captures them in an extensible, declarative form, and achieves modeling of components and entry points in a largely framework-independent way. The second technique offers precision and scalability via a sound-modulo-analysis modeling of standard data structures. In realistic enterprise applications (an order of magnitude larger than prior benchmarks in the literature) our techniques achieve high degrees of completeness (on average more than 4x higher than conventional techniques) and speedups of about 6x compared to the most precise conventional analysis, with higher precision on multiple metrics. The result is JackEE, an enterprise analysis framework that can offer precise, high-completeness static modeling of realistic enterprise applications.","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":"72571412","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}

引用次数: 18

Zippy LL(1) parsing with derivatives Zippy LL(1)带有导数的解析

Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation Pub Date : 2020-06-06 DOI: 10.1145/3385412.3385992

Romain Edelmann, Jad Hamza, Viktor Kunčak

引用次数: 6

Faster general parsing through context-free memoization 通过上下文无关的记忆实现更快的一般解析

Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation Pub Date : 2020-06-06 DOI: 10.1145/3385412.3386032

G. Herman

引用次数: 5

Compiler-directed soft error resilience for lightweight GPU register file protection 编译器定向软错误弹性轻量级GPU注册文件保护

Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation Pub Date : 2020-06-06 DOI: 10.1145/3385412.3386033

Hongjune Kim, Jianping Zeng, Qingrui Liu, Mohammad Abdel-Majeed, Jaejin Lee, Changhee Jung

引用次数: 14

Scalable validation of binary lifters 二进制提升器的可扩展验证

Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation Pub Date : 2020-06-06 DOI: 10.1145/3385412.3385964

Sandeep Dasgupta, S. Dinesh, Deepan Venkatesh, Vikram S. Adve, Christopher W. Fletcher

{"title":"Scalable validation of binary lifters","authors":"Sandeep Dasgupta, S. Dinesh, Deepan Venkatesh, Vikram S. Adve, Christopher W. Fletcher","doi":"10.1145/3385412.3385964","DOIUrl":"https://doi.org/10.1145/3385412.3385964","url":null,"abstract":"Validating the correctness of binary lifters is pivotal to gain trust in binary analysis, especially when used in scenarios where correctness is important. Existing approaches focus on validating the correctness of lifting instructions or basic blocks in isolation and do not scale to full programs. In this work, we show that formal translation validation of single instructions for a complex ISA like x86-64 is not only practical, but can be used as a building block for scalable full-program validation. Our work is the first to do translation validation of single instructions on an architecture as extensive as x86-64, uses the most precise formal semantics available, and has the widest coverage in terms of the number of instructions tested for correctness. Next, we develop a novel technique that uses validated instructions to enable program-level validation, without resorting to performance-heavy semantic equivalence checking. Specifically, we compose the validated IR sequences using a tool we develop called Compositional Lifter to create a reference standard. The semantic equivalence check between the reference and the lifter output is then reduced to a graph-isomorphism check through the use of semantic preserving transformations. The translation validation of instructions in isolation revealed 29 new bugs in McSema – a mature open-source lifter from x86-64 to LLVM IR. Towards the validation of full programs, our approach was able to prove the translational correctness of 2254/2348 functions taken from LLVM’s single-source benchmark test-suite.","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":"88454020","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}

引用次数: 15

Blended, precise semantic program embeddings 混合，精确的语义程序嵌入

Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation Pub Date : 2020-06-06 DOI: 10.1145/3385412.3385999

Ke Wang, Z. Su

{"title":"Blended, precise semantic program embeddings","authors":"Ke Wang, Z. Su","doi":"10.1145/3385412.3385999","DOIUrl":"https://doi.org/10.1145/3385412.3385999","url":null,"abstract":"Learning neural program embeddings is key to utilizing deep neural networks in program languages research --- precise and efficient program representations enable the application of deep models to a wide range of program analysis tasks. Existing approaches predominately learn to embed programs from their source code, and, as a result, they do not capture deep, precise program semantics. On the other hand, models learned from runtime information critically depend on the quality of program executions, thus leading to trained models with highly variant quality. This paper tackles these inherent weaknesses of prior approaches by introducing a new deep neural network, Liger, which learns program representations from a mixture of symbolic and concrete execution traces. We have evaluated Liger on two tasks: method name prediction and semantics classification. Results show that Liger is significantly more accurate than the state-of-the-art static model code2seq in predicting method names, and requires on average around 10x fewer executions covering nearly 4x fewer paths than the state-of-the-art dynamic model DYPRO in both tasks. Liger offers a new, interesting design point in the space of neural program embeddings and opens up this new direction for exploration.","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":"74587738","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}

引用次数: 44

Detecting network load violations for distributed control planes 检测网络负载违反分布式控制平面

Proceedings of the 41st ACM SIGPLAN Conference on Programming Language Design and Implementation Pub Date : 2020-06-06 DOI: 10.1145/3385412.3385976

Kausik Subramanian, Anubhavnidhi Abhashkumar, Loris D'antoni, Aditya Akella

引用次数: 9