Regression testing is applied to modified software to provide confidence that the changed parts behave as intended and that the unchanged parts have not been adversely affected by the modifications. To reduce the cost of regression testing, test cases are selected from the test suite that was used to test the original version of the software-this process is called regression test selection. A safe regressiontest-selection algorithm selects every test case in the test suite that may reveal a fault in the modified software. Safe regression-test-selection techniques can help to reduce the time required to perform regression testing because they select only a portion of the test suite for use in the testing but guarantee that the faults revealed by this subset will be the same as those revealed by running the entire test suite. This paper presents the first safe regression-test-selection technique that, based on the use of a suitable representation, handles the features of the Java language. Unlike other safe regression test selection techniques, the presented technique also handles incomplete programs. The technique can thus be safely applied in the (very common) case of Java software that uses external libraries or components; the analysis of the external code is not required for the technique to select test cases for such software. The paper also describes Retest, a regression-test-selection system that implements our technique, and a set of empirical studies that demonstrate that the regression-test-selection algorithm can be effective in reducing the size of the test suite.

Regression testing is applied to modified software to provide confidence that the changed parts behave as intended and that the unchanged parts have not been adversely affected by the modifications. To reduce the cost of regression testing, test cases are selected from the test suite that was used to test the original version of the software-this process is called regression test selection. A safe regressiontest-selection algorithm selects every test case in the test suite that may reveal a fault in the modified software. Safe regression-test-selection techniques can help to reduce the time required to perform regression testing because they select only a portion of the test suite for use in the testing but guarantee that the faults revealed by this subset will be the same as those revealed by running the entire test suite. This paper presents the first safe regression-test-selection technique that, based on the use of a suitable representation, handles the features of the Java language. Unlike other safe regression test selection techniques, the presented technique also handles incomplete programs. The technique can thus be safely applied in the (very common) case of Java software that uses external libraries or components; the analysis of the external code is not required for the technique to select test cases for such software. The paper also describes Retest, a regression-test-selection system that implements our technique, and a set of empirical studies that demonstrate that the regression-test-selection algorithm can be effective in reducing the size of the test suite.

This 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.

Program analysis and program optimization of Java programs require reference information that estimates the instances of classes that may be accessed through dereferences. Recent work has presented several approaches for adapting Andersen's algorithm [1]---the most precise flow-insensitive and context-insensitive points-to analysis algorithm developed for C--- for analyzing Java programs (e.g., [5, 9, 12]). Studies in our previous work [6] indicate that this algorithm may compute very imprecise reference information for Java programs.

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