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Unfortunately,deciding to recompile for better optimizationis not as simple a choice. First,the compiler may not be able to capitalizeon the changed interproceduralsets—the optimizationmight have been prevented by facts other than theone just changed. Second, even if the optimizationcan be done, the run-timeimprovementobtained may not justify the cost of recompilation,particularlyif the procedure is large.

On the other hand, the changed informationmightmake a major difference—forexample, if it exposed a substantialamount ofparallelism.Before we can construct a practical compiler that capitalizeson tests forimproved optimization,we need reasonable estimators that can predict runtime improvementas a function of changes to interproceduralfacts, Untilsuch an estimatoris available, recompilingfor improvementis almost certainly a hit-or-missproposition.The tests that we have presented in thissection can be used to tell the compiler which procedures are candidates forsuch analysis, but they cannot, by themselves, predict the results of recompiling.9. SUMMARYAND CONCLUSIONSCompilinga program in the presence of interproceduralinformationintroduces dependencebetween its procedures that complicate the question ofwhat to recompile when a change is made in the program.

In the absence ofinformationabout these dependence,all procedures in the program must berecompiledwhenevera change is made to any one of them. This papersets, for reducing thedescribes a general framework,based upon annotationACM Transactionson ProgrammingLanguages and Systems, Vol. 15, No. 3, July 1993.398.M. Burke and L. Torczonnumber of unnecessary recompilationrequiredframework,several methods for computingthepresented. These methods differ in the amountprecision of the resulting recompilationanalysis.be evaluated is compilationtime versus numberafter a change.

Within thisannotationsets have beenof work requiredand theThe fundamentaltradeoff toof spurious recompilation.ACKNOWLEDGMENTSKeith Cooper and Ken Kennedy contributedto the initial work in this areaand encouraged and supported the extensions presented in this paper. FrancesAllen, Ron Cytron, and David Shields of IBM contributedto our discussionsof this problem. Barbara Ryder pointed out several problems with the versionof this work that was presentedat SIGPLAN’86.

The TOPLAS refereesprovidedcommentsand suggestionsthat improvedthe expositionof theresults presented in this paper. Both the R n and PTRAN implementationteams have provided marvelous research vehicles for experimentingwith newideas about interproceduralanalysis and optimization.To all of these peoplego our heartfelt thanks.REFERENCESA. V., SETHI, R., AND ULLMAN, J. D,Addison Wesley, Reading, Mass., 1986,1.AHo,2.ALLEN, F E., BURKE, M., CHARLES, P., CYTRON, R,, AND FERRANTE, J.DLstribCornPTRAN analysis system for multiprocessing.J. Parall.Compilers:Prmclples,TechniquesandTools,An overviewof theput.

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