Debugging optimized code is a desirable capability not provided by most current debuggers. Users are forced to debug the unoptimized code when a bug occurs in the optimized version. Current research offers partial solutions for a small class of optimizations, but not a unified approach that handles a wide range of optimizations, such as the sophisticated optimizations performed by supercomputer compilers.The trend with current research is to make the effects of optimization transparent, i.e., provide the same behavior as that of the unoptimized program. We contend that this approach is neither totally feasible nor entirely desirable. Instead, we propose a new approach based on the premise that one should be able to debug the optimized code. This implies mapping the current state of execution back to the original source, tracking the location of variables, and mapping compiler-synthesized variables back to user-defined induction variables. To aid the user in understanding program behavior, various visual means are provided, e.g., different forms of highlighting and annotating of the source/assembly code. While this unavoidably requires the user to have a basic understanding of the optimizations performed, it permits the user to see what is actually happening, infer the optimizations performed, and detect bugs. An example illustrates the effectiveness of visual feedback.To support conventional debugger functionality for optimized code, the compiler must generate additional information. Current compiler-debugger interfaces (CDIs) were neither designed to handle this new information nor are they extensible in a straight forward manner. Therefore, a new CDI was designed that supports providing visual feedback and the debugging of optimized code. This paper specifies the details of a new CDI and relates each feature back to the debugger functionality it supports.

A new approach to debugging optimized code

Correct optimization can change the behavior of an incorrect program; therefore at times it is necessary to debug optimized code. However, optimizing compilers produce code that impedes source-level debugging.Optimization can cause an inconsistency between where the user expects a breakpoint to be located and the breakpoint's actual location. This article describes a mapping between statements and breakpoint locations that ameliorates this problem. The mapping enables debugger behavior on optimized code that approximates debugger behavior on unoptimized code sufficiently closely for the user to use traditional debugging strategies.Optimization can also cause the value of a variable to be noncurrent—to differ from the value that would be predicted by a close reading of the source code. This article presents a method of determining when this has occurred, and shows how a debugger can describe the relevant effects of optimization. The determination method is more general than previously published methods; it handles global optimization and many flow graph transformations, and it is not tightly coupled to optimizations performed by a particular compiler. Necessary compiler support is also described.

Debugging optimized code without being misled

In object-oriented programming languages, an object is said to escape the method or thread in which it was created if it can also be accessed by other methods or threads. Knowing which objects do not escape allows a compiler to perform aggressive optimizations.This paper presents a new intraprocedural and interprocedural algorithm for escape analysis in the context of dynamic compilation where the compiler has to cope with dynamic class loading and deoptimization. It was implemented for Sun Microsystems' Java HotSpot™ client compiler and operates on an intermediate representation in SSA form. We introduce equi-escape sets for the efficient propagation of escape information between related objects. The analysis is used for scalar replacement of fields and synchronization removal, as well as for stack allocation of objects and fixed-sized arrays. The results of the interprocedural analysis support the compiler in inlining decisions and allow actual parameters to be allocated on the caller stack.Under certain circumstances, the Java HotSpot™ VM is forced to stop executing a method's machine code and transfer control to the interpreter. This is called deoptimization. Since the interpreter does not know about the scalar replacement and synchronization removal performed by the compiler, the deoptimization framework was extended to reallocate and relock objects on demand.

/pdf/escape-analysis-in-the-context-of-dynamic-compilation-and-4kth7gfez9.pdf

Escape analysis in the context of dynamic compilation and deoptimization

Debugging of computer programs is necessary for the development of the programs as well as for maintaining the operation of the programs. Symbolic debugging requires the ability to relate the current position in the object code program to the corresponding position in the source code. In the absence of compiler optimization, correlating the source and object code elements is a straightforward procedure. However, when the object code has been optimized, the relation between the source code constructs and object code instructions can become convoluted and complex. A correlation technique for optimized code is disclosed which maps the source constructs (source units) through each of the optimization operations by use of compilation nodes and associated source units to build a table which relates ranges of object instructions to the source units which produced the object instructions.

Debugger program which includes correlation of computer program source code with optimized objet code

A debugger is used in an environment of optimized compiling to track both user-defined and synthesized variables so that the values of these variables at selected programmer counter addresses can be either determined or set. The tracking is primarily accomplished by the generation of various interrelated tables including a Type Scope Table, a Name Space Table, an Expression Table, a Location Range Table and a Variable Table. These tables define the existence of variables at defined program counter ranges and provide the algebraic definitions for the synthesized variables. A programmer can efficiently debug a program produced with optimized compiling through the operations of determining variable values and setting variable values.

Computer program debugging in the presence of compiler synthesized variables

A note on Hennessy's “symbolic debugging of optimized code”

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A note on Hennessy's “symbolic debugging of optimized code”