Invariance of Approximative Semantics with Respect to Program Transformations

Giegerich, Robert; Möncke, Ulrich; Wilhelm, Reinhard

doi:10.1007/978-3-662-01089-1_1

Cited by 32 publications

(24 citation statements)

References 3 publications

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“…Faint code elimination (c£ [8,10,17]), a generalization of dead code elimination, is a typical representative of such a problem, which seems to be impossible to formulate on a basic-block level. The point is that the local properties of a basic block are not invariant under the global faintness analysis.…”

Section: Short-comingsmentioning

confidence: 99%

“…[8,10,17]) is a striking example of a practically relevant problem where it is not at all obvious of how to express it on the basicblock level. Intuitively, a variable is faint if there is no program continuation on which it is used without a preceding modification, or if the left-hand side variable of the instruction it is used in, is faint as well.…”

Section: Limited Generalitymentioning

confidence: 99%

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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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Section: Short-comingsmentioning

confidence: 99%

Section: Limited Generalitymentioning

confidence: 99%

Basic-block graphs: Living dinosaurs?

Knoop

Koschützki

Steffen

1998

Lecture Notes in Computer Science

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“…For our tree transformation strategy, where re-evaluations may be restricted to the restructured area, we extend the classical attribute grammar framework by allowing a set of values to be correct for each attribute instance. Each value of such a set should be an approximation of the correct value according to the classical attribute grammar definition [5,[8][9][10]14].…”

Section: Iteration Of Evaluation and Tree Transformation Phasesmentioning

confidence: 99%

“…In [9,10] the new correct values are called safe, whereas the old correct values are called consistent. We also use this terminology.…”

Section: Iteration Of Evaluation and Tree Transformation Phasesmentioning

confidence: 99%

Iteration of transformation passes over attributed program trees

Alblas

1989

Acta Informatica

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Summary.Transformations of attributed program trees form an essential part of compiler optimizations. A strategy of repeatedly applying alternate attribute evaluation and tree transformation phases is discussed. An attribute evaluation phase consists of a sequence of passes over the tree. A tree transformation phase consists of a single pass, which is never interrupted to carry out a re-evaluation. Both phases can be performed in parallel. This strategy requires a distinction between consistent (i.e., correct) and approximate attribute values. Tree transformations can be considered safe if they guarantee that the attribute values everywhere in the program tree will remain consistent or will become at least approximations of the consistent values, so that subsequent transformations can be applied correctly.This attribute evaluation and tree transformation strategy shows similarities with the evaluation methods for circular attribute grammars.

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“…This means that all the transformations performed during the transformation pass are correct, but in interrupt of the transformation pass in order to make extra tree walks for re-evaluation purposes might have disclosed further opportunities for optimization [9,10].…”

Section: Iterative Application Of a Transformation Passmentioning

confidence: 99%

One-pass transformations of attributed program trees

Alblas

1987

Acta Informatica

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Invariance of Approximative Semantics with Respect to Program Transformations

Cited by 32 publications

References 3 publications

Basic-block graphs: Living dinosaurs?

Basic-block graphs: Living dinosaurs?

Iteration of transformation passes over attributed program trees

One-pass transformations of attributed program trees

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