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data-flow analysis OF ARRAY AND SCALAR REFERENCES

INTERNATIONAL JOURNAL OF PARALLEL PROGRAMMING 1991年第1期20卷 23-53页

作者： FEAUTRIER, P UNIV PIERRE & MARIE CURIL MASI LABF-75252 PARIS 05FRANCE

Given a program written in a simple imperative language (assignment statements, for loops, affine indices and loop limits), this paper presents an algorithm for analyzing the patterns along which values flow as the execution proceeds. For each array or scalar reference, the result is the name and iteration vector of the source statement as a function of the iteration vector of the referencing statement. The paper discusses several applications of the method: conversion of a program to a set of recurrence equations, array and scalar expansion, program verification and parallel program construction.

关键词： data-flow analysis SEMANTICS analysis ARRAY EXPANSION

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data-flow analysis-Based Approach of database Watermarking 2nd

Data-Flow Analysis-Based Approach of Database Watermarking

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2nd International Doctoral Symposium on Applied Computation and Security Systems (ACSS)

作者： Rani, Sapana Kachhap, Preeti Halder, Raju Indian Inst Technol Patna Bihar India

ISBN: (纸本)9788132226536;9788132226512

In this paper, we propose a persistent watermarking technique of information systems supported by relational databases at the back-end. The persistency is achieved by identifying an invariant part of the database which remains unchanged w.r.t. the operations in the associated applications. To achieve this, we apply static data-flow analysis technique to the applications. The watermark is then embedded into the invariant part of the database, leading to a persistent watermark. We also watermark the associated applications in the information system by using opaque predicates which are obtained from the variant part of the database.

关键词： Persistent watermarking Relational databases data-flow analysis Security

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data-flow analysis for MPI programs

Data-flow analysis for MPI programs

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35th International Conference on Parallel Processing

作者： Strout, Michelle Mills Kreaseck, Barbara Hovland, Paul D. Colorado State Univ Ft Collins CO 80523 USA La Sierra Univ Riverside CA USA Argonne Natl Lab Argonne IL USA

ISBN: (纸本)0769526365

Message passing via MPI is widely used in single-program, multiple-data (SPMD) parallel programs. Existing data-flow frameworks do not model the semantics of message-passing SPMD programs, which can result in less precise and even incorrect analysis results. We present a data-flow analysis framework for performing interprocedural analysis of message-passing SPMD programs. The framework is based on the MPI-ICFG representation, which is an interprocedural control-flow graph (ICFG) augmented with communication edges between possible send and receive pairs and partial context sensitivity. We show how to formulate nonseparable data-flow analyses within our framework using reaching constants as a canonical example. We also formulate and provide experimental results for the nonseparable analysis, activity analysis. Activity analysis is a domain-specific analysis used to reduce the computation and storage requirements for automatically differentiated MPI programs. Automatic differentiation is important for application domains such as climate modeling, electronic device simulation, oil reservoir simulation, medical treatment planning and computational economics to name a few. Our experimental results show that using the MPI-ICFG data-flow analysis framework improves the precision of activity analysis and as a result significantly reduces memory requirements for the automatically differentiated versions of a set of parallel benchmarks, including some of the NAS Parallel Benchmarks.

关键词： MPI data-flow analysis activity analysis SPMD MPI-ICFG

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Lifting inter-app data-flow analysis to large app sets

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AUTOMATED SOFTWARE ENGINEERING 2018年第2期25卷 315-346页

作者： Sattler, Florian von Rhein, Alexander Berger, Thorsten Johansson, Niklas Schalck Hardo, Mikael Mark Apel, Sven Univ Passau Passau Germany CQSE GmbH Munich Germany Chalmers I Univ Gothenburg Gothenburg Sweden IT Univ Copenhagen Copenhagen Denmark

Mobile apps process increasing amounts of private data, giving rise to privacy concerns. Such concerns do not arise only from single apps, which might-accidentally or intentionally-leak private information to untrusted parties, but also from multiple apps communicating with each other. Certain combinations of apps can create critical data flows not detectable by analyzing single apps individually. While sophisticated tools exist to analyze data flows inside and across apps, none of these scale to large numbers of apps, given the combinatorial explosion of possible (inter-app) data flows. We present a scalable approach to analyze data flows across Android apps. At the heart of our approach is a graph-based data structure that represents inter-app flows efficiently. Following ideas from product-line analysis, the data structure exploits redundancies among flows and thereby tames the combinatorial explosion. Instead of focusing on specific installations of app sets on mobile devices, we lift traditional data-flow analysis approaches to analyze and represent data flows of all possible combinations of apps. We developed the tool Sifta and applied it to several existing app benchmarks and real-world app sets, demonstrating its scalability and accuracy.

关键词： Android data-flow analysis Inter-app communication Variability-aware analysis Variational data structures

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May/must analysis and the DFAGen data-flow analysis generator

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INFORMATION AND SOFTWARE TECHNOLOGY 2009年第10期51卷 1440-1453页

作者： Stone, Andrew Strout, Michelle Behere, Shweta Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA Avaya Inc Milpitas CA 95035 USA

data-flow analysis is a common technique for gathering program information for use in program transformations such as register allocation, dead-code elimination, common subexpression elimination, and scheduling. Current tools for generating data-flow analysis implementations enable analysis details to be specified orthogonally to the iterative analysis algorithm but still require implementation details regarding the may and must use and definition sets that occur due to the effects of pointers, side effects, arrays, and user-defined structures. This paper presents the data-flow analysis Generator tool (DFAGen), which enables analysis writers to generate analyses for separable and nonseparable data-flow analyses that are pointer, aggregate, and side-effect cognizant from a specification that assumes only scalars. By hiding the compiler-specific details behind predefined set definitions, the analysis specifications for the DFAGen tool are typically less than ten lines long and similar to those in standard compiler textbooks. The main contribution of this work is the automatic determination of when to use the may or must variant of a predefined set usage in the analysis specification. (C) 2009 Elsevier B.V. All rights reserved.

关键词： data-flow analysis May Must Static analysis Program analysis Compilers

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INCREMENTAL data-flow analysis ALGORITHMS

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ACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMS 1988年第1期10卷 1-50页

作者： RYDER, BG PAULL, MC Rutgers Univ. New Brunswick NJ

An incremental update algorithm modifies the solution of a problem that has been changed, rather than re-solving the entire problem. ACINCF and ACINCB are incremental update algorithms for forward and backward data-flow analysis, respectively, based on our equations model of Allen-Cocke interval analysis. In addition, we have studied their performance on a “nontoy” structured programming language L. Given a set of localized program changes in a program written in L, we identify a priori the nodes in its flow graph whose corresponding data-flow equations may be affected by the changes. We characterize these possibly affected nodes by their corresponding program structures and their relation to the original change sites, and do so without actually performing the incremental updates. Our results can be refined to characterize the reduced equations possibly affected if structured loop exit mechanisms are used, either singly or together, thereby relating richness of programming language usage to the ease of incremental updating.

关键词： data-flow analysis elimination methods

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Paged absolute addressing mode optimizations for embedded digital signal processors using post-pass data-flow analysis

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DESIGN AUTOMATION FOR EMBEDDED SYSTEMS 1999年第1期4卷 41-59页

作者： Sudarsanam, A Malik, S Tjiang, S Liao, S Princeton Univ Dept Elect Engn Princeton NJ 08544 USA Tensilica Inc Cupertino CA USA Synopsys Inc Mountain View CA USA

We address the problem of code generation for embedded DSP systems. In such systems, it is typical for one or more digital signal processors (DSPs), program memory, and custom circuitry to be integrated onto a single IC. Consequently, the amount of silicon area that is dedicated to program memory is limited, so the embedded software must be sufficiently dense. Additionally, this software must be written so as to meet various high-performance constraints, which may include hard real-time constraints. Unfortunately, existing compiler technology is unable to generate dense, high-performance code for DSPs since it does not provide adequate support for the specialized architectural features of DSPs. These specialized features not only allow for the fast execution of common DSP operations, but they also allow for the generation of dense assembly code that specifies these operations. Thus, system designers often hand-program the embedded software in assembly, which is a very time-consuming task. In this paper, we focus on providing compiler support for one particular specialized architectural feature, namely the paged absolute addressing mode - this feature is found in two commercial DSPs, the Texas Instruments' TMS320C25 and TMS320C50 fixed-point DSPs;however, it may also be featured in application-specific processors (ASIPs). We present some machine-dependent code optimizations that improve code density by exploiting this architectural feature. Experimental results demonstrate that for a set of typical DSP benchmarks, some of our optimizations reduce overall code size and data memory consumption by an average of 5.0% and 16.0%, respectively. Our experimental vehicle throughout this research is the TMS320C25.(1)

关键词： basic block code generation control-flow graph data-flow analysis

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TRACTABLE data-flow analysis FOR DISTRIBUTED SYSTEMS

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 1994年第8期20卷 579-593页

作者： CHEUNG, SC KRAMER, J UNIV LONDON IMPERIAL COLL SCI TECHNOL & MED DEPT COMP LONDON SW7 2BZ ENGLAND

Automated behavior analysis is a valuable technique in the development and maintainence of distributed systems. In this paper, we present a tractable dataflow analysis technique for the detection of unreachable states and actions in distributed systems. The technique follows an approximate approach described by Reif and Smolka, but delivers a more accurate result in assessing unreachable states and actions. The higher accuracy is achieved by the use of two concepts: action dependency and history sets. Although the technique, does not exhaustively detect all possible errors, it detects nontrivial errors with a worst-case complexity quadratic to the system size. It can be automated and applied to systems with arbitrary loops and nondeterministic structures. The technique thus provides practical and tractable behavior analysis for preliminary designs of distributed systems. This makes it an ideal candidate for an interactive checker in software development tools. The technique is illustrated with case studies of a pump control system and an erroneous distributed program. Results from a prototype implementation are presented.

关键词： DISTRIBUTED SYSTEMS data-flow analysis LABELED TRANSITION SYSTEMS STATIC analysis PROGRAM VERIFICATION DISTRIBUTED SOFTWARE ENGINEERING SYNCHRONOUS COMMUNICATING SYSTEMS AND REACHABILITY analysis

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SafeDrop: Detecting Memory Deallocation Bugs of Rust Programs via Static data-flow analysis

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ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY 2023年第4期32卷 1-21页

作者： Cui, Mohan Chen, Chengjun Xu, Hui Zhou, Yangfan Fudan Univ Sch Comp Sci Shanghai Peoples R China Shanghai Key Lab Intelligent Informat Proc Shanghai Peoples R China

Rust is an emerging programming language that aims to prevent memory-safety bugs. However, the current design of Rust also brings side effects, which may increase the risk of memory-safety issues. In particular, it employs ownership-based resource management and enforces automatic deallocation of unused resources without using the garbage collector. It may therefore falsely deallocate reclaimed memory and lead to use-after-free or double-free issues. In this article, we study the problem of invalid memory deallocation and propose SafeDrop, a static path-sensitive data-flow analysis approach to detect such bugs. Our approach analyzes each function of a Rust crate iteratively in a flow-sensitive and field-sensitive way. It leverages a modified Tarjan algorithm to achieve scalable path-sensitive analysis and a cache-based strategy for efficient inter-procedural analysis. We have implemented our approach and integrated it into the Rust compiler. Experiment results show that the approach can successfully detect all such bugs in our experiments with a limited number of false positives and incurs a very small overhead compared to the original compilation time.

关键词： Rust data-flow analysis meet over path path sensitivity

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Compiler analysis for cache coherence: Interprocedural array data-flow analysis and its impact on cache performance

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2000年第9期11卷 879-896页

作者： Choi, L Yew, PC Korea Univ Sch Elect Engn Seoul 136701 South Korea Univ Minnesota Dept Comp Sci Minneapolis MN 55455 USA

In this paper, we present compiler algorithms for detecting references to stale data in shared-memory multiprocessors. The algorithm consists of two key analysis techniques, stale reference detection and locality preserving analysis. While the stale reference detection finds the memory reference patterns that may violate cache coherence, the locality preserving analysis minimizes the number of such stale references by analyzing both temporal and spatial reuses. By computing the regions referenced by arrays inside loops, we extend the previous scalar algorithms [9] for more precise analysis. We develop a full interprocedural array data-flow algorithm, which performs both bottom-up side-effect analysis and top-down context analysis on the procedure call graph to further exploit locality across procedure boundaries. The interprocedural algorithm eliminates cache invalidations at procedure boundaries, which were assumed in the previous compiler algorithms [9]. We have fully implemented the algorithm in the Polaris parallelizing compiler [28]. Using execution-driven simulations on Perfect Club benchmarks, we demonstrate how unnecessary cache misses can be eliminated by the automatic stale reference detection. The algorithm can be used to implement cache coherence in the shared-memory multiprocessors that do not have hardware directories, such as Gray T3D [21].

关键词： compiler interprocedural analysis data-flow analysis cache coherence shared-memory multiprocessors

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