As software grows in size and complexity, it also becomes more interdependent. Multiple internal components often share state and data. Whether these dependencies are intentional or not, we have found that their mismanagement often poses several challenges to testing. This thesis seeks to make it easier to create reliable software by making testing more efficient and more effective through explicit knowledge of these hidden dependencies. The first problem that this thesis addresses, reducing

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... ting time, directly impacts the day-to-day work of every software developer. The frequency with which code can be built (compiled, tested, and package) directly impacts the productivity of developers: longer build times mean a longer wait before determining if a change to the application being build was successful. We have discovered that in the case of some languages, such as Java, the vast majority of build time is spent running tests. Therefore, it's incredibly important to focus on approaches to accelerating testing, while simultaneously making sure that we do not inadvertently cause tests to erratically fail (i.e. become flaky). Typical techniques for accelerating tests (like running only a subset of them, or running them in parallel) often can't be applied soundly, since there may be hidden dependencies between tests. While we might think that each test should be independent (i.e. that a test's outcome isn't influenced by the execution of another test), we and others have found many examples in real software projects where tests truly have these dependencies: some tests require others to run first, or else their outcome will change. Previous work has shown that these dependencies are often complicated, unintentional, and hidden from developers. We have built several systems, VMVM and ElectricTest, that detect different sorts of dependencies between tests and use that information to soundly reduce testing time by several orders of magnitude. In our first approach, Unit Test Virtualization, we reduce [...]