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Technical Report

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Technical Report Number



While it is generally accepted that garbage-collected languages offer advantages over languages in which objects must be explicitly deallocated, real-time developers are leery of the adverse effects a garbage collector might have on real-time performance. Semiautomatic approaches based on regions have been proposed, but incorrect usage could cause unbounded storage leaks or program failure. Moreover, correct usage cannot be guaranteed at compile-time. Recently, real-time garbage collectors have been developed that provide a guaranteed fraction of the CPU to the application, and the correct operation of those collectors has been proven, subject only to the specification of certain statistics related to the type and rate of objects allocated by the application. However, unless those statistics are provided or estimated appropriately, the collector may fail to collect dead storage at a rate sufficient to pace the application’s need. Overspecification of those statistics is safe, but leaves the application with less than its possible share of the CPU, which may prevent the application from meeting its deadlines. In this thesis, we present a dynamic and static analysis of one such statistic, namely the real-time application’s memory allocation rate. The dynamic analysis highlights the variability of a program’s allocation rate. It also serves to quantify the conservatism of the statically computed upper bound. The static analysis is based on a data flow framework that requires interprocedural evaluation. We present the framework and results from analyzing some Java benchmarks from the jvm98 suite. Our work is a necessary step toward making real-time garbage collectors attractive to the hard-real-time community. By guaranteeing a bound on statistics provided to a real-time collector, we can guarantee the operation of the collector for a given application.


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