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

We present a new mining algorithm for discovering program structure built on a warehouse of program-analysis data. We make use of statement definition-use data along with variable typing information to learn about the structure of legacy code. Using concept analysis, we develop an interactive knowledge discovery framework into which different types of analysis data can be integrated. This work is the first in a series of data warehousing experiments that is designed to tap the wealth of information hidden in existing program-analysis data.