The DDP (Demand-driven/Pruning) analysis algorithm allows us to perform data-flow analyses of programming languages that are dynamically typed and have higher-order control flow, such as Smalltalk or Scheme. Because it is demand-driven and employs search pruning, it scales to large code bases. However, versions of the algorithm previously described [19] do not handle data polymorphism well, conservatively merging separate data flows that go through distinct instantiations of a collection type. In this paper, we describe a new extension to DDP that helps to disentangle these flows, permitting more precise results. The extension is based on source-tagging classes so that each reference to a class in the source code yields a subdivision of the type associated with that class. An initial implementation of this polyvariant analysis has been added to the DDP-based tool Chuck, a part of the integrated Squeak program-development environment; we show examples of the tool in action.

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