State Of the Art in Java Program Analysis最新文献

A software product line for static analyses: the OPAL framework 用于静态分析的软件产品线:OPAL框架

State Of the Art in Java Program Analysis Pub Date : 2014-06-12 DOI: 10.1145/2614628.2614630

Michael Eichberg, Ben Hermann

引用次数: 32

How to build the perfect Swiss army knife, and keep it sharp?: Challenges for the soot program-analysis framework in the light of past, current and future demands 如何打造一把完美的瑞士军刀，并让它保持锋利?根据过去、现在和未来的需求，烟灰方案分析框架面临的挑战

State Of the Art in Java Program Analysis Pub Date : 2014-06-12 DOI: 10.1145/2614628.2614634

E. Bodden

引用次数: 0

TS4J: a fluent interface for defining and computing typestate analyses TS4J:用于定义和计算类型状态分析的流畅接口

State Of the Art in Java Program Analysis Pub Date : 2014-06-12 DOI: 10.1145/2614628.2614629

E. Bodden

{"title":"TS4J: a fluent interface for defining and computing typestate analyses","authors":"E. Bodden","doi":"10.1145/2614628.2614629","DOIUrl":"https://doi.org/10.1145/2614628.2614629","url":null,"abstract":"Typestate analyses determine whether a program's use of a given API obeys this API's usage constraints in the sense that the right methods are called on the right objects in the right order. Previously, we and others have described approaches that generate typestate analyses from textual finite-state property definitions written in specialized domain-specific languages. While such an approach is feasible, it requires a heavyweight compiler, hindering an effective integration into the programmer's development environment and thus often also into her software-development practice.\u0000 Here we explain the design of a pure-Java interface facilitating both the definition and evaluation of typestate analyses. The interface is fluent, a term coined by Eric Evans and Martin Fowler. Fluent interfaces provide the user with the possibility to write method-invocation chains that almost read like natural-language text, in our case allowing for a seemingly declarative style of typestate definitions. In all previously described approaches, however, fluent APIs are used to build configuration objects. In this work, for the first time we show how to design a fluent API in such a way that it also encapsulates actual computation, not just configuration.\u0000 We describe an implementation on top of Soot, Heros and Eclipse, which we are currently evaluating together with pilot customers in an industrial context at Fraunhofer SIT.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127390905","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: 14

Large-scale configurable static analysis 大规模可配置静态分析

State Of the Art in Java Program Analysis Pub Date : 2014-06-12 DOI: 10.1145/2614628.2614635

M. Naik

{"title":"Large-scale configurable static analysis","authors":"M. Naik","doi":"10.1145/2614628.2614635","DOIUrl":"https://doi.org/10.1145/2614628.2614635","url":null,"abstract":"Program analyses developed over the last three decades have demonstrated the ability to prove non-trivial properties of real-world programs. This ability in turn has applications to emerging software challenges in security, software-defined networking, cyber-physical systems, and beyond. The diversity of such applications necessitates adapting the underlying program analyses to client needs, in aspects of scalability, applicability, and accuracy. Today's program analyses, however, do not provide useful tuning knobs. This talk presents a general computer-assisted approach to effectively adapt program analyses to diverse clients.\u0000 The approach has three key ingredients. First, it poses optimization problems that expose a large set of choices to adapt various aspects of an analysis, such as its cost, the accuracy of its result, and the assumptions it makes about missing information. Second, it solves those optimization problems by new search algorithms that efficiently navigate large search spaces, reason in the presence of noise, interact with users, and learn across programs. Third, it comprises a program analysis platform that facilitates users to specify and compose analyses, enables search algorithms to reason about analyses, and allows using large-scale computing resources to parallelize analyses.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114981336","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: 1

Android taint flow analysis for app sets Android应用程序集的污染流分析

State Of the Art in Java Program Analysis Pub Date : 2014-06-12 DOI: 10.1145/2614628.2614633

William Klieber, Lori Flynn, Amar Bhosale, Limin Jia, Lujo Bauer

引用次数: 221

Dynamic slicing with soot 煤烟动态切片

State Of the Art in Java Program Analysis Pub Date : 2014-06-12 DOI: 10.1145/2614628.2614631

Arian Treffer, M. Uflacker

引用次数: 4

Explicit and symbolic techniques for fast and scalable points-to analysis 用于快速和可扩展的点分析的显式和符号技术

State Of the Art in Java Program Analysis Pub Date : 2014-06-12 DOI: 10.1145/2614628.2614632

E. Pek, P. Madhusudan

{"title":"Explicit and symbolic techniques for fast and scalable points-to analysis","authors":"E. Pek, P. Madhusudan","doi":"10.1145/2614628.2614632","DOIUrl":"https://doi.org/10.1145/2614628.2614632","url":null,"abstract":"Points-to analysis that scales to large programs is still an open area of research and there are several trade-offs between speed and precision. In this paper, we report advances in achieving extremely fast and scalable analysis for field-sensitive inclusion-based points-to analysis. The first algorithm is based on an explicit representation, sparse bit-vector set representation. The second algorithm is a refinement of the first using symbolic set representations using binary decision diagrams. The first algorithm scales extremely well when compared with the state-of-the-art points-to analysis problems solving the same problem, while the second reduces the memory footprint tremendously, using, on average, 4.6x less memory than the first, and even performs slightly faster points-to set propagation. The techniques that we introduce are a judicious combination of several heuristics involving sparse bit-vector set representations, prioritized processing of worklists for efficient iteration while computing fixed-points, and usage of binary decision diagrams for storing (but not propagating) points-to sets.\u0000 The implementation of our approaches scales to large real life Java applications. We evaluated our implementation on benchmark applications from two recent releases of DaCapo benchmark suite using a recent version of Java Standard Library (JRE 1.7_03). Using our techniques we can propagate points-to information on all the benchmarks in less than a minute, using at most 2GB of memory for explicit representation and, at most 600MB for symbolic representation. Comparison with the fastest and the most closely related explicit and symbolic approaches reveals that our techniques are more scalable than related explicit approaches, and in terms of time, on average 4x times faster than the current state-of-the-art.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126810862","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: 4

OCSEGen: open components and systems environment generator OCSEGen:开放组件和系统环境生成器

State Of the Art in Java Program Analysis Pub Date : 2013-06-20 DOI: 10.1145/2487568.2487572

O. Tkachuk

引用次数: 10

Numerical static analysis with Soot 用Soot进行数值静态分析

State Of the Art in Java Program Analysis Pub Date : 2013-06-20 DOI: 10.1145/2487568.2487571

G. Amato, S. Maio, F. Scozzari

引用次数: 11

Joogie: from Java through Jimple to Boogie 从Java到Jimple再到Boogie

State Of the Art in Java Program Analysis Pub Date : 2013-06-20 DOI: 10.1145/2487568.2487570

Stephan Arlt, Philipp Rümmer, Martin Schäf

引用次数: 12