We present TackleTest, an open-source tool for automatic generation of unit-level test cases for Java applications. TackleTest builds on top of two well-known test-generation tools, EvoSuite and Randoop, by adding a new combinatorial-testing-based approach for computing coverage goals that comprehensively exercises different parameter type combinations of the methods under test, at configurable interaction levels. We describe the tool architecture, the main tool components, and the combinatorial type-based testing technique. TackleTest was developed in the context of application modernization at IBM, but it is also applicable as a general-purpose test-generation tool. We have evaluated TackleTest on several IBM-internal enterprise applications as well as on a subset of the SF110 benchmark, and share our findings and lessons learned. Overall, TackleTest implements a new and complementary way of computing coverage goals for unit testing via a novel white-box application of combinatorial testing.

We present Finding Related Interesting Events via Neighbor Detection (FRIENDS), a novel approach to assist verification teams with coverage closure. FRIENDS uses formal verification to find the neighboring events of a never-hit, or hard-to-hit, coverage event. The neighbor events of a given target event are defined as those events for which a test hitting them has higher probability of hitting the target event than a test not hitting them. Assuming that some of the neighboring events are easier to hit than the target event itself, this information can be used by the team or by a Coverage Directed Generation (CDG) tool during the coverage closure process.

The widely used Mark-and-Sweep garbage collector has a drawback in that it does not move objects during collection. As a result, large long-running realistic applications, such as Web application servers, frequently face the fragmentation problem. To eliminate fragmentation, a heap compaction is run periodically. However, compaction typically imposes very long undesirable pauses in the application. While efficient concurrent collectors are ubiquitous in production runtime systems (such as JVMs), an efficient non-intrusive compactor is still missing.In this paper we present the Compressor, a novel compaction algorithm that is concurrent, parallel, and incremental. The Compressor compacts the entire heap to a single condensed area, while preserving the objects' order, but reduces pause times significantly, thereby allowing acceptable runs on large heaps. Furthermore, the Compressor is the first compactor that requires only a single heap pass. As such, it is the most efficient compactors known today, even when run in a parallel Stop-the-World manner (i.e., when the program threads are halted). Thus, to the best of our knowledge, the Compressor is the most efficient compactor known today. The Compressor was implemented on a Jikes Research RVM and we provide measurements demonstrating its qualities.