Marathon is a GUI test tool that allows you to play and record scripts against a Java Swing UI. It's written in Java, and uses Python and Ruby as its scripting language (the emphasis being on an extremely simple, readable syntax that customers/testers/analysts feel comfortable with). Marathon includes a recorder, editor, player, and debugger to simplify working with test scripts.
System and Process Monitor in Java provides a JNI (Java Native Interface) implementation for monitoring global system resources and processes (outside JVM) via a unified (cross-platform) interface. The Java interface and all native libraries are compiled into a single JAR and are loaded transparently on any architecture upon request. It should be easy to embedd this code into your Java applications, either as a separate JAR or as one single application archive.
TSPSG is intended to generate and solve "travelling salesman problem" (TSP) tasks. It uses the Branch and Bound method for solving. Its input is a number of cities and a matrix of city-to-city travel costs. The matrix can be populated with random values in a given range (which is useful for generating tasks). The result is an optimal route, its price, step-by-step matrices of solving, and a solving graph. The task can be saved in an internal binary format and opened later. The result can be printed or saved as PDF, HTML, or ODF. TSPSG may be useful for teachers to generate test tasks or just for regular users to solve TSPs. Also, it may be used as an example of using the Branch and Bound method to solve a particular task.
Feed4JUnit makes it easy to write parameterized tests for the JUnit framework and feed them with predefined or randomly generated test data: test case data can be read from Excel or CSV files, databases, or custom data sources, and equivalence class tests can be defined easily. Setup is based on Java annotations and is easy to learn, apply, and maintain. Annotations defined in the "Bean Validation" JSR 303, Java 7, and Benerator are automatically recognized and generated smoke test data will match the constraints. By connecting to Benerator, you can configure generation of complex valid and invalid data sets.