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Harrold,
Mary Jean
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Mary Jean
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ItemUsing Component Metadata to Support the Regression Testing of Component-Based Software(Georgia Institute of Technology, 2000) Harrold, Mary Jean ; Orso, Alessandro ; Rosenblum, David S. ; Rothermel, Gregg ; Soffa, Mary Lou ; Do, HyunsookInterest in component-based software continues to grow with the recognition of its potential in managing the increasing complexity of software systems. However, the use of externally-provided components has serious drawbacks, in most cases due to the lack of information about the components, for a wide range of activities in the engineering of component-based applications. Consider the activity of regression testing, whose high cost has been, and continues to be, a problem. In the case of component-based applications, regression testing can be even more expensive. When a new version of one or more components is integrated into an application, the lack of information about such externally-developed components makes it difficult to effectively determine the test cases that should be rerun on the resulting application. In previous work, we proposed the use of metadata, which are additional data provided with a component, to support software engineering tasks. In this paper, we present two new metadata-based techniques that address the problem of regression test selection for component-based applications: a code-based approach and a specification-based approach. First, using an example, we illustrate the two techniques. Then, we present a case study that applies the code-based technique to a real component-based system. The results of the study indicate that, on average, 26% of the overall testing effort can be saved over seven releases of the component-based system studied, with a maximum savings of 99% of the testing effort for one version. This reduction demonstrates that metadata can produce benefits in regression testing by reducing the costs related to this activity.
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ItemIncremental Slicing Based on Data-Dependences Types(Georgia Institute of Technology, 2000) Orso, Alessandro ; Sinha, Saurabh ; Harrold, Mary JeanProgram slicing is useful for assisting with software-maintenance tasks, such as program understanding, debugging, impact analysis, and regression testing. The presence and frequent usage of pointers, in languages such as C, causes complex data dependences. To function effectively on such programs, slicing techniques must account for pointerinduced data dependences. Although many existing slicing techniques function in the presence of pointers, none of those techniques distinguishes data dependences based on their types. This paper presents a new slicing technique, in which slices are computed based on types of data dependences. This new slicing technique offers several benefits and can be exploited in different ways, such as identifying subtle data dependences for debugging purposes, computing reduced-size slices quickly for complex programs, and performing incremental slicing. In particular, this paper describes an algorithm for incremental slicing that increases the scope of a slice in steps, by incorporating different types of data dependences at each step. The paper also presents empirical results to illustrate the performance of the technique in practice. The experimental results show how the sizes of the slices grow for different small- and mediumsized subjects. Finally, the paper presents a case study that explores a possible application of the slicing technique for debugging.
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ItemEffects of Pointers on Data Dependences(Georgia Institute of Technology, 2000) Orso, Alessandro ; Sinha, Saurabh ; Harrold, Mary JeanData dependences, which relate statements that compute data value to statements that use those values, are useful for automating a variety of program-comprehension-related activities, such as reverse engineering, impact analysis, and debugging. Unfortunately, data dependences are difficult to compute and understand in the presence of commonly-used language features such as pointers, arrays, and structures. To facilitate the comprehension of data dependences in programs that use such features, we define a technique for computing and classifying data dependences that takes into account the complexities introduced by specific language constructs. The classification that we present is finer-grained than previously proposed classification. Moreover, unlike previous work, we present empirical results that illustrate the distribution of data dependences for a set of C subjects. We also present a potential application for the proposed classification: program slicing. We propose a technique that allows for computing slices based on data-dependence types. This technique facilitates the use of slicing for understanding a program because a user can either incrementally augment a slice by incorporating data dependences based on their relevance, or focus on specific kinds of dependences. Finally, we present a case study that shows how the incremental computation of slices can (1) highlight subtle data dependences within a program, and (2) provide useful information about those dependences.
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ItemAnalysis and Testing of Programs with Exception-Handling Constructs(Georgia Institute of Technology, 2000) Sinha, Saurabh ; Harrold, Mary JeanAnalysis techniques, such as control flow, data flow, and control dependence, are used for a variety of software-engineering tasks, including structural and regression testing, dynamic execution profiling, static and dynamic slicing, and program understanding. To be applicable to programs in languages such as Java and C++, these analysis techniques must account for the effects of exception occurrences and exception-handling constructs; failure to do so can cause the analysis techniques to compute incorrect results and thus, limit the usefulness of the applications that use them. This paper discusses the effect of exception-handling constructs on several analysis techniques. The paper presents techniques to construct representations for programs with explicit exception occurrences --- exceptions that are raised explicitly through throw statements --- and exception-handling constructs. The paper presents algorithms that use these representations to perform the desired analyses. The paper also discusses several software-engineering applications that use these analyses. Finally, the paper describes empirical results pertaining to the occurrence of exception-handling constructs in Java programs, and their impact on some analysis tasks.
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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.