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Harrold,
Mary Jean
Harrold,
Mary Jean
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ItemA Framework for Understanding Data Dependences(Georgia Institute of Technology, 2002) Orso, Alessandro ; Liang, Donglin ; Sinha, Saurabh ; Harrold, Mary JeanIdentifying and understanding data dependences is important for a variety of software-engineering tasks. The presence of pointers, arrays, and dynamic memory allocation introduces subtle and complex data dependences that may be difficult to understand. In this paper, we present a refinement of our previously developed classification that also distinguishes the types of memory locations, considers interprocedural data dependences, and further distinguishes such data dependences based on the kinds of interprocedura paths on which they occur. This new classification enables reasoning about the complexity of data dependences in programs using features such as pointers, arrays, and dynamic memory allocation. We present an algorithm for computing interprocedural data dependences according to our classification. To evaluate the classification, we compute the distribution of data dependences for a set of real C programs and we discuss how the distribution can be useful in understanding the characteristics of a program. We also evaluate how alias information provided by different algorithms, varying in precision, affects the distribution. Finally, we investigate how the classification can be exploited to estimate complexity of the data dependences in a program.
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ItemGamma System: Continuous Evolution of Software after Deployment(Georgia Institute of Technology, 2002) Orso, Alessandro ; Liang, Donglin ; Harrold, Mary Jean ; Lipton, Richard J.In this paper, we present the Gamma system---a new approach for continuous improvement of software systems after their deployment. The Gamma system facilitates remote monitoring of deployed software using a revolutionary approach that exploits the opportunities presented by a software product being used by many users connected through a network. Gamma splits monitoring tasks across different instances of the software, so that partial information can be collected from different users by means of light-weight instrumentation, and integrated to gather the overall monitoring information. This system enables software producers (1) to perform continuous, minimally intrusive analyses of their software's behavior, and (2) to use the information thus gathered to improve and evolve their software. We describe the Gamma system and its underlying technology in detail, and illustrate the different components of the system. We also present a prototype implementation of the system and show our initial experiences with it.
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ItemPaper: Evaluating the Precision of Static Reference Analysis Using Profiling(Georgia Institute of Technology, 2002) Liang, Donglin ; Pennings, Maikel ; Harrold, Mary JeanProgram analyses and optimization of Java programs require reference information that determines the instances that may be accessed through dereferences. Reference information can be computed using reference analysis. This paper presents a set of studies that evaluate the precision of some existing approaches for identifying instances and for computing reference information in a reference analysis. The studies use dynamic reference information collected during run-time as a lower bound approximation to the precise reference information. The studies measure the precision of an existing approach by comparing the information computed using the approach with the lower bound approximation. The paper also presents case studies that attempt to identify the cases under which an existing approach is not effective. The presented studies provide information that may guide the usage of existing reference analysis techniques and the development of new reference analysis techniques.
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ItemExtending and Evaluating Flow-Insensitve and Context-insensitive Points-to Analyses for Java(Georgia Institute of Technology, 2001) Liang, Donglin ; Pennings, Maikel ; Harrold, Mary JeanThis paper presents extensions to Steensgaard's and Andersen's algorithms to handle Java features. Without careful consideration, the handling of these features may affect the correctness, precision, and efficiency of these algorithms. The paper also presents the results of empirical studies. These studies compare the precision and efficiency of these two algorithms and evaluate the effectiveness of handling Java features using alternative approaches. The studies also evaluate the impact of the points-to information provided by these two algorithms on client analyses that use the information.
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ItemEfficient Computation of Parameterized Pointer Information for Interprocedural Analyses(Georgia Institute of Technology, 2000) Liang, Donglin ; Harrold, Mary JeanPointer information that is provided by many algorithms identifies a memory location using the same name throughout a program. Such pointer information is inappropriate for use in analyzing C programs because, using such information, a program analysis may propagate a large amount of spurious information across procedure boundaries. This paper presents a modular algorithm that efficiently computes parameterized pointer information in which symbolic names are introduced to identify memory locations whose addresses may be passed into a procedure. Because a symbolic name may identify different memory locations when the procedure is invoked under different callsites, using parameterized pointer information can help a program analysis reduce the spurious information that is propagated across procedure boundaries. The paper also presents a set of empirical studies, that demonstrate (a) the efficiency of the algorithm, and (b) the benefits of using parameterized pointer information over using non-parameterized pointer information in program analyses. The studies show that using parameterized pointer information may significantly improve the precision and the efficiency of many program analyses.