Instrumenting code to collect profiling information can cause substantial execution overhead. This overhead makes instrumentation difficult to perform at runtime, often preventing many known offline feedback-directed optimizations from being used in online systems. This paper presents a general

, and thus it works at a lower level than abstract-syntax trees. But CIL is also more high-level than typical intermediate languages (e.g., three-address code) designed for compilation. As a result, what we have is a representation that makes it easy to analyze and manipulate C programs, and emit them in a

Our capabilities of both generating and collecting data have been increasing rapidly in the last several decades. Contributing factors include the widespread use of bar codes for most commercial products, the computerization of many business, scientific and government transactions and managements

Ideally, software is derived from requirements whose properties have been established as good. However, it is difficult to define and analyze requirements. Moreover, derivation of software from requirements is error prone. Finally, the installation and use of compiled software can introduce errors. Thus, it can be difficult to provide assurances about the state of a software's execution.

shows that the inference is very effective for many C programs, as it is able to infer that most or all of the pointers are statically verifiable to be type safe. The remaining pointers are instrumented with efficient run-time checks to ensure that they are used safely. The resulting performance loss

. Thus, it can be difficult to provide assurances about the state of a software's execution. We present a framework to monitor requirements of software as it executes. The framework is general, and allows for automated support. In this paper, we introduced the framework, and show how Java code can

We present a post-compiler program manipulation tool called Dyninst which provides a C++ class library for program instrumentation. Using this library, it is possible to instrument and modify application programs during execution. A unique feature of this library is that it permits machine

We propose a low-overhead sampling infrastructure for gathering information from the executions experienced by a program 's user community. Several example applications illustrate ways to use sampled instrumentation to isolate bugs. Assertion-dense code can be transformed to share the cost

for TinyOS applications. In PowerTOSSIM, TinyOS components corresponding to specific hardware peripherals (such as the radio, EEPROM, LEDs, and so forth) are instrumented to obtain a trace of each device’s activity during the simulation run. PowerTOSSIM employs a novel code-transformation technique

as PARAFRASE). Other projects that have influenced our work are the Texas Instruments ASC compiler [9, 33], the Cray-1 FORTRAN compiler [15], and the Massachusetts Computer Associates Vectorizer [22, 25]. The paper is organized into seven sections. Section 2 introduces FORTRAN 8x and gives examples of its use