Compilers: principles, techniques, and tools
Compilers: principles, techniques, and tools
Incremental data-flow analysis algorithms
ACM Transactions on Programming Languages and Systems (TOPLAS)
An efficient hybrid algorithm for incremental data flow analysis
POPL '90 Proceedings of the 17th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Precise interprocedural dataflow analysis via graph reachability
POPL '95 Proceedings of the 22nd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
C and tcc: a language and compiler for dynamic code generation
ACM Transactions on Programming Languages and Systems (TOPLAS)
PEPM '02 Proceedings of the 2002 ACM SIGPLAN workshop on Partial evaluation and semantics-based program manipulation
The Combining DAG: A Technique for Parallel Data Flow Analysis
IEEE Transactions on Parallel and Distributed Systems
Jumbo: run-time code generation for Java and its applications
Proceedings of the international symposium on Code generation and optimization: feedback-directed and runtime optimization
Compiling for Runtime Code Generation (Extended Version)
Compiling for Runtime Code Generation (Extended Version)
Optimizing marshalling by run-time program generation
GPCE'05 Proceedings of the 4th international conference on Generative Programming and Component Engineering
Interprocedural dataflow analysis in the presence of large libraries
CC'06 Proceedings of the 15th international conference on Compiler Construction
Static analysis of multi-staged programs via unstaging translation
Proceedings of the 38th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
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Program generators are most naturally specified using a quote/antiquote facility; the programmer writes programs with holes which are filled in, at program generation time, by other program fragments. If the programs are generated at compile-time, analysis and compilation follow generation, and no changes in the compiler are needed. However, if program generation is done at run time, compilation and analysis need to be optimized so that they will not overwhelm overall execution time. In this paper, we give a compositional framework for defining program analyses which leads directly to a method of staging these analyses. The staging allows the analysis of incomplete programs to be started at compile time; the residual work to be done at run time may be much less costly than the full analysis. We give frameworks for forward and backward analyses, present several examples of specific analyses, and give timing results showing significant speed-ups for the run-time portion of the analysis relative to the full analysis.