The value flow graph: A program representation for optimal program transformations

Steffen, Bernhard; Knoop, Jens; Rüthing, Oliver

doi:10.1007/3-540-52592-0_76

Cited by 39 publications

(44 citation statements)

References 11 publications

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“…The SED is a directed acyclic graph representation of expressions. It is similar to the structured partition DAG in [16]. Each SED represents a partition of expressions and each node in the SED represents an equivalence class.…”

Section: Representation Of Equivalence Informationmentioning

confidence: 99%

An Improved Algorithm for Redundancy Detection Using Global Value Numbering

2015

J Inf Process Syst

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Global value numbering (GVN) is a method for detecting equivalent expressions in programs. Most of the GVN algorithms concentrate on detecting equalities among variables and hence, are limited in their ability to identify value-based redundancies. In this paper, we suggest improvements by which the efficient GVN algorithm by Gulwani and Necula (2007) can be made to detect expression equivalences that are required for identifying value based redundancies. The basic idea for doing so is to use an anticipability-based Join algorithm to compute more precise equivalence information at join points. We provide a proof of correctness of the improved algorithm and show that its running time is a polynomial in the number of expressions in the program.

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Section: Representation Of Equivalence Informationmentioning

confidence: 99%

An Improved Algorithm for Redundancy Detection Using Global Value Numbering

2015

J Inf Process Syst

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“…This shows the power of being able to ne-tune the benchmarks' proles. Applying randomized POE [4,27] together with some pruning heuristics allows one to almost arbitrarily obfuscate the original cycle orientation, and it provides room for a subsequent application of (global) code motion techniques, ranging from merely syntactical analyses reminiscent of partial redundancy elimination [8,28,11,20,12,2931] to more semantic transformations in terms of semantic code motion [10,9,32,33,21], which shifts the orginal local reasoning problem to the global level.…”

Section: Mealy-to-program Model Transformationmentioning

confidence: 99%

Property-Driven Benchmark Generation

Steffen

Isberner

Naujokat

et al. 2013

Model Checking Software

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Abstract. We present a systematic approach to the automatic generation of platform-independent benchmarks of tailored complexity for evaluating verication tools for reactive systems. Key to this approach is a tool chain that essentially transforms a set of automatically generated LTL properties into source code for various formats, platforms, and competition scenarios via a sequence of property-preserving steps. These

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“…[11]) or the computation of semantically equivalent program terms (cf. [23]), which can quite naturally and easily be expressed on the instruction level, but not on the basic-block level. In [15] this is illustrated by means of constant propagation.…”

Section: Limited Generalitymentioning

confidence: 99%

“…the computation of semantically equivalent terms (cf. [23]) are beyond the scope of a BB-modelling (cf. Section 4.3).…”

Section: Practice: Empirical Evaluationmentioning

confidence: 99%

Basic-block graphs: Living dinosaurs?

Knoop

Koschützki

Steffen

1998

Lecture Notes in Computer Science

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Abstract. Since decades, basic-block (BB) graphs have been the stateof-the-art means for representing programs in advanced industrial compiler environments. The usual justification for introducing the intermediate BB-structures in the program representation is performance: analyses on BB-graphs are generally assumed to outperform their counterparts on single-instruction (SI) graphs, which, undoubtedly, are conceptually much simpler, easier to implement, and more straightforward to verify. In this article, we discuss the difference between the two program representations and show by means of runtime measurements that, according to the new computer generations, performance is no longer on the side of the more complex BB-graphs. In fact, it turns out that no sensible reason for the BB-structure remains. Rather, we will demonstrate that edge-labeled SI-graphs, which model statements in their edges instead of in their nodes as classical flow graphs do, are most adequate, both for the theoretical reasoning about and for the implementation of analysis and optimization algorithms. We are convinced that this perception has far-reaching consequences for the design of compiler systems. MotivationIn program analysis and optimization it is common to work on so-called flow graphs, whose edge structure makes the control flow of the underlying program explicit. Most widely used are node-labeled basic-block (BB) graphs, whose nodes represent maximal sequences of straight-line code. This most prominent representation can be modified according to (1) its granularity in order to arrive at single-instruction (SI) graphs and/or to (2) its way of instruction modelling: edge-labeled graphs model instructions/basic blocks by edges rather than nodes.In this article we investigate these four variants of program representation both from a theoretical and practical point of view. It turns out that the most prominent representation in practice is no longer adequate in times where already the main storage of home computers easily accommodates SI-graphs for huge procedures. Moreover, we show that edge-labeled graphs simplify both the theoretical reasoning about analysis and optimization as well as their implementation in comparison to their node-labeled counterparts.

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The value flow graph: A program representation for optimal program transformations

Cited by 39 publications

References 11 publications

An Improved Algorithm for Redundancy Detection Using Global Value Numbering

An Improved Algorithm for Redundancy Detection Using Global Value Numbering

Property-Driven Benchmark Generation

Basic-block graphs: Living dinosaurs?

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