This paper addresses the problem of resolving virtual method and interface calls in Java bytecode. The main focus is on a new practical technique that can be used to analyze large applications. Our fundamental design goal was to develop a technique that can be solved with only one iteration, and thus scales linearly with the size of the program, while at the same time providing more accurate results than two popular existing linear techniques, class hierarchy analysis and rapid type analysis. We present two variations of our new technique, variable-type analysis and a coarser-grain version called declared-type analysis. Both of these analyses are inexpensive, easy to implement, and our experimental results show that they scale linearly in the size of the program. We have implemented our new analyses using the Soot framework, and we report on empirical results for seven benchmarks. We have used our techniques to build accurate call graphs for complete applications (including librarie...

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Dynamically-dispatched calls often limit the performance of object-oriented programs since object-oriented programming encourages factoring code into small, reusable units, thereby increasing the frequency of these expensive operations. Frequent calls not only slow down execution with the dispatch overhead per se, but more importantly they hinder optimization by limiting the range and effectiveness of standard global optimizations. In particular, dynamicallydispatched calls prevent standard interprocedural optimizations that depend on the availability of a static call graph. The SELF implementation described here offers two novel approaches to optimization. Type feedback speculatively inlines dynamically-dispatched calls based on profile information that predicts likely receiver classes. Adaptive optimization reconciles optimizing compilation with interactive performance by incrementally optimizing only the frequently-executed parts of a program. When combined, these two techniques result in a system that can execute programs significantly faster than previous systems while retaining much of the interactiveness of an interpreted system.

In this dissertation, we show how a relatively simple and extremely fast interprocedural optimization algorithm can be used to optimize many of the expensive features of statically typed, object-oriented languages --- in particular, C++ and Java. We present a new program analysis algorithm, Rapid Type Analysis, and show that it is fast both in theory and in practice, and significantly out-performs other "fast" algorithms for virtual function call resolution. We present optimization algorithms for the resolution of virtual function calls, conversion of virtual inheritance to direct inheritance, elimination of dynamic casts and dynamic type checks, and removal of object synchronization. These algorithms are all presented within a common framework that allows them to be driven by the information collected by Rapid Type Analysis, or by some other type analysis algorithm. Collectively, the optimizations in this dissertation free the programmer from having to sacrifice modularity and extensibility for performance. Instead, the programmer can freely make use of the most powerful features of object-oriented programming, since the optimizer will remove unnecessary extensibility from the program.

Over the last seven years, we have developed static-analysis methods to recover a good approximation to the variables and dynamically-allocated memory objects of a stripped executable, and to track the flow of values through them. The paper presents the algorithms that we developed, explains how they are used to recover intermediate representations (IRs) from executables that are similar to the IRs that would be available if one started from source code, and describes their application in the context of program understanding and automated bug hunting. Unlike algorithms for analyzing executables that existed prior to our work, the ones presented in this paper provide useful information about memory accesses, even in the absence of debugging information. The ideas described in the paper are incorporated in a tool for analyzing Intel x86 executables, called CodeSurfer/x86. CodeSurfer/x86 builds a system dependence graph for the program, and provides a GUI for exploring the graph by (i) navigating its edges, and (ii) invoking operations, such as forward slicing, backward slicing, and chopping, to discover how parts of the program can impact other parts. To assess the usefulness of the IRs recovered by CodeSurfer/x86 in the context of automated bug hunting, we built a tool on top of CodeSurfer/x86, called Device-Driver Analyzer for x86

Class libraries are generally designed with an emphasis on versatility and extensibility. Applications that use a library typically exercise only part of the library's functionality. As a result, objects created by the application may contain unused members. We present an algorithm that specializes a class hierarchy with respect to its usage in a program P . That is, the algorithm analyzes the member access patterns for P's variables, and creates distinct classes for variables that accessdifferent members. Class hierarchy specialization reduces object size,and is hence primarily a space optimization. However, execution time may also be reduced through reduced object creation/destruction time, and caching/paging effects. 1 Introduction Class libraries are generally designed with an emphasis on versatility and extensibility. An application that uses a class library typically exercises only part of the library's functionality. Unfortunately, this leads to situations where the objects cr...

SmallEiffel is an Eiffel compiler which uses a fast simple type inference mechanism to remove most late binding calls, replacing them by static bindings. Starting from the system's entry point, it compiles only statically living code, which saves compiling and then removing dead code. As the whole system is analyzed at compile time, multiple inheritance and genericity do not cause any overhead. SmallEiffel features a coding scheme which eliminates the need for virtual function tables. Dynamic dispatch is implemented without any array access but uses a simple static binary branch code. We show that this implementation makes it possible to use modern hardware very efficiently. It also allows us to inline more calls even when dynamic dispatch is required. Some more dispatch sites are removed after the type inference algorithm has been performed, if the dioeerent branches of a dispatch site lead to the same code. The advantage of this approach is that it greatly speeds up execution time and...

Object-oriented applications may contain data members that can be removed from the application without affecting program behavior. Such "dead" data members may occur due to unused functionality in class libraries, or due to the programmer losing track of member usage as the application changes over time. We present a simple and efficient algorithm for detecting dead data members in C++ applications. This algorithm has been implemented using a prototype version of the IBM VisualAge C++ compiler, and applied to a number of realistic benchmark programs ranging from 600 to 58,000 lines of code. For the non-trivial benchmarks, we found that up to 27.3% of the data members in the benchmarks are dead (average 12.5%), and that up to 11.6% of the object space of these applications may be occupied by dead data members at run-time (average 4.4%). 1 Introduction Object-oriented applications may contain data members (instance variables) that can be removed from the application without affecting p...

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We introduce dependence-based pre-computation as a complement to history-based target prediction schemes. We present pre-computation in the context of virtual function calls (v-calls), a class of control transfers that is becoming increasingly important and has resisted conventional prediction. Our proposed technique dynamically identifies the sequence of operations that computes a v-call’s target. When the first instruction in such a sequence is encountered, a small execution engine speculatively and aggressively pre-executes the rest. The pre-computed target is stored and subsequently used when a prediction needs to be made. We show that a common v-call instruction sequence can be exploited to implement pre-computation using a previously proposed prefetching mechanism and minimal additional hardware. In a suite of C++ programs, dependence-based pre-computation eliminates 46 % of the mispredictions incurred by a simple BTB and 24 % of those associated with a path-based two-level predictor. 1