This paper shows howalarge class of interprocedural dataflow-analysis problems can be solved precisely in polynomial time. The only restrictions are that the set of dataflowfacts is a finite set, and that the dataflowfunctions distribute overthe confluence operator (either union or intersection). This class of problems includes---but is not limited to---the classical separable problems (also known as "gen/kill" or "bit-vector" problems)---e.g.,reaching definitions, available expressions, and live variables. In addition, the class of problems that our techniques handle includes manynon-separable problems, including trulylive variables, copyconstant propagation, and possibly-uninitialized variables. Anovelaspect of our approach is that an interprocedural dataflow-analysis problem is transformed into a special kind of graph-reachability problem (reachability along interprocedurally realizable paths). The paper presents three polynomial-time algorithms for the realizable-path reachability problem: an exhaustive version, a second exhaustive version that may be more appropriate in the incremental and/or interactive context, and a demand version. The first and third of these algorithms are asymptotically faster than the best previously known realizable-path reachability algorithm. An additional benefit of our techniques is that theylead to improvedalgorithms for twoother kinds of interproceduralanalysis problems: interprocedural flow-sensitive side-effect problems (as studied by Callahan) and interprocedural program slicing (as studied by Horwitz, Reps, and Binkley). CR Categories and Subject Descriptors: D.3.4 [Programming Languages]: Processors - compilers, optimization;E.1 [Data

The first interprocedural modification side-effects analysis for C (MOD_C) that obtains better than worst-case precision on programs with general-purpose pointer usage is presented with empirical results. The analysis consists of an algorithm schema corresponding to a family of MODC algorithms with two independent phases: one for determining pointer-induced aliases and a subsequent one for propagating interprocedural side effects. These MOD_C algorithms are parameterized by the aliasing method used. The empirical results compare the performance of two dissimilar MOD_C algorithms: MOD_C(FSAlias) uses a flow-sensitive, calling-context-sensitive interprocedural alias analysis [LR92]; MOD_C(FIAlias) uses a flow-insensitive, calling-context-insensitive alias analysis which is much faster, but less accurate. These two algorithms were profiled on 45 programs ranging in size from 250 to 30,000 lines of C code, and the results demonstrate dramatically the possible cost-precision tradeoffs. This first comparative implementation of MODC analyses offers insight into the differences between flow-/context-sensitive and flow-/context-insensitive analyses. The analysis cost versus precision tradeoffs in side-effect information obtained is reported. The results show surprisingly that the precision of flow-sensitive side-effect analysis is not always prohibitive in cost, and that the precision of flow-insensitive analysis is substantially better than worst-case estimates and seems sufficient for certain applications. On average MODC (FSAlias) for procedures and calls is in the range of 20% more precise than MODC (F IAlias); however, the performance was found to be at least an order of magnitude slower than MODC (F IAlias).

This paper describes how a number of program-analysis problems can be solved by transforming them to graph-reachability problems. Some of the program-analysis problems that are amenable to this treatment include program slicing, certain dataflow-analysis problems, and the problem of approximating the possible "shapes" that heap-allocated structures in a program can take on. Relationships between graph reachability and other approaches to program analysis are described. Some techniques that go beyond pure graph reachability are also discussed.

Abstract. Recently, pushdown systems (PDSs) have been extended to weighted PDSs, in which each transition is labeled with a value, and the goal is to determine the meet-over-allpaths value (for paths that meet a certain criterion). This paper shows how weighted PDSs yield new algorithms for certain classes of interprocedural dataflow-analysis problems. 1

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The existence of statically detectable correlation among conditional branches enables their elimination, an optimization that has a number of benefits. This paper presents techniques to determine whether an interprocedural execution path leading to a conditional branch exists along which the branch outcome is known at compile time, and then to eliminate the branch along this path through code restructuring. The technique consists of a demand driven interprocedural analysis that determines whether a specific branch outcome is correlated with prior statements or branch outcomes. The optimization is performed using a code restructuring algorithm that replicates code to separate out the paths with correlation. When the correlated path is affected by a procedure call, the restructuring is based on procedure entry splitting and exit splitting. The entry splitting transformation creates multiple entries to a procedure, and the exit splitting transformation allows a procedure to return control...

this article, we present a general framework for developing demand-driven interprocedural data flow analyzers and report our experience in evaluating the performance of this approach. A demand for data flow information is modeled as a set of queries. The framework includes a generic demand-driven algorithm that determines the response to a query by iteratively applying a system of query propagation rules. The propagation rules yield precise responses for the class of distributive finite data flow problems. We also describe a two-phase framework variation to accurately handle nondistributive problems. A performance evaluation of our demand-driven approach is presented for two data flow problems, namely, reaching-definitions and copy constant propagation. Our experiments show that demand-driven analysis performs well in practice, reducing both time and space requirements when compared with exhaustive analysis.

dynamic optimization, compiler, trace selection, binary translation © Copyright Hewlett-Packard Company 1999 Dynamic optimization refers to the runtime optimization of a native program binary. This report describes the design and implementation of Dynamo, a prototype dynamic optimizer that is capable of optimizing a native program binary at runtime. Dynamo is a realistic implementation, not a simulation, that is written entirely in user-level software, and runs on a PA-RISC machine under the HPUX operating system. Dynamo does not depend on any special programming language,

Known algorithms for pointer analysis are "global" in the sense that they perform an exhaustive analysis of a program or program component. In this paper we introduce a demand-driven approach for pointer analysis. Specifically, we describe a demand-driven flow-insensitive, subset-based, context-insensitive points-to analysis. Given a list of pointer variables (a query), our analysis performs just enough computation to determine the points-to sets for these query variables. Using deductive reachability formulations of both the exhaustive and the demand-driven analyses, we prove that our algorithm is correct. We also show that our analysis is optimal in the sense that it does not do more work than necessary. We illustrate the feasibility and efficiency of our analysis with an implementation of demand-driven points-to analysis for computing the call-graphs of C programs with function pointers. The performance of our system varies substantially across benchmarks - the main factor is how much of the points-to graph must be computed to determine the call-graph. For some benchmarks, only a small part of the points-to graph is needed (e.g povray, emacs and gcc), and here we see more than a 10x speedup. For other benchmarks (e.g. burlap and gimp), we need to compute most (? 95%) of the points-to graph, and here the demanddriven algorithm is considerably slower, because using the demand-driven algorithm is a slow method of computing the full points-to graph.

. To produce high quality code, modern compilers use global optimization algorithms based on abstract interpretation. These algorithms are rather complex; their implementation is therefore a non--trivial task and error--prone. However, since they are based on a common theory, they have large similar parts. We conclude that analyzer writing better should be replaced with analyzer generation. We present the tool PAG that has a high level functional input language to specify data flow analyses. It offers the specification of even recursive data structures and is therefore not limited to bit vector problems. PAG generates efficient analyzers which can be easily integrated in existing compilers. The analyzers are interprocedural, they can handle recursive procedures with local variables and higher order functions. PAG has successfully been tested by generating several analyzers (e.g. alias analysis, constant propagation) for an industrial quality ANSI-C and Fortran90 compiler. Keywords: d...