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Performance Impact of Object Oriented Programming

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It is widely accepted that object-oriented design improves code reusability, facilitates code maintainability and enables higher levels of abstraction. Although the software engineering community has embraced object-oriented programming for these benefits, it has not been clear what performance overheads are associated with this programming paradigm. In this paper, we present some quantitative results based on the performance of a few programs in C and C++. Several programs were profiled and the statistics of several program executions at various compiler optimization levels were generated on two architectures, the MIPS and SPARC. One observation was that in spite of a static code increase in C++, the dynamic instruction counts were either comparable or smaller in C++. However the cache miss ratios and traffic ratios were significantly worse for C++ (often twice). It was also seen that some of the C++ features such as function overloading and free unions did not incur any run time over...
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Previous studies have shown that object-oriented programs have different execution characteristics than procedural programs, and that special object-oriented hardware can improve performance. The results of these studies may no longer hold because compiler optimizations can remove a large fraction of the differences. Our measurements show that SELF programs are more similar to C programs than are C++ programs, even though SELF is much more radically object-oriented than C++ and thus should differ much more from C.Furthermore, the benefit of tagged arithmetic instructions in the SPARC architecture (originally motivated by Smalltalk and Lisp implementations) appears to be small. Also, special hardware could hardly reduce message dispatch overhead since dispatch sequences are already very short. Two generic hardware features, instruction cache size and data cache write policy, have a much greater impact on performance.
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