Explicitly stated program invariants can help programmers by identifying program properties that must be preserved when modifying code. In practice, however, these invariants are usually implicit.An alternative to expecting programmers to fully annotate code with invariants is to automatically infer invariants from the program itself. This research focuses on dynamic techniques for discovering invariants from execution traces. This paper reports two results. First, it describes techniques for dynamically discovering invariants, along with an instrumenter and an inference engine that embody these techniques. Second, it reports on the application of the engine to two sets of target programs. In programs from Gries's work on program derivation, we rediscovered predefined invariants. In a C program lacking explicit invariants, we discovered invariants that assisted a software evolution task.

ÐThe artifacts constituting a software system often drift apart over time. We have developed the software reflexion model technique to help engineers perform various software engineering tasks by exploitingÐrather than removingÐthe drift between design and implementation. More specifically, the technique helps an engineer compare artifacts by summarizing where one artifact (such as a design) is consistent with and inconsistent with another artifact (such as source). The technique can be applied to help a software engineer evolve a structural mental model of a system to the point that it is ªgood-enoughº to be used for reasoning about a task at hand. The software reflexion model technique has been applied to support a variety of tasks, including design conformance, change assessment, and an experimental reengineering of the million-lines-of-code Microsoft Excel product. In this paper, we provide a formal characterization of the reflexion model technique, discuss practical aspects of the approach, relate experiences of applying the approach and tools, and place the technique into the context of related work. Fig. 2. (a) High-level and (b) reflexion models for the NetBSD virtual memory subsystem.

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Abstract. Object-oriented unit tests consist of sequences of method invocations. Behavior of an invocation depends on the method's arguments and the state of the receiver at the beginning of the invocation. Correspondingly, generating unit tests involves two tasks: generating method sequences that build relevant receiverobject states and generating relevant method arguments. This paper proposes Symstra, a framework that achieves both test generation tasks using symbolic execution of method sequences with symbolic arguments. The paper defines symbolic states of object-oriented programs and novel comparisons of states. Given a set of methods from the class under test and a bound on the length of sequences, Symstra systematically explores the object-state space of the class and prunes this exploration based on the state comparisons. Experimental results show that Symstra generates unit tests that achieve higher branch coverage faster than the existing test-generation techniques based on concrete method arguments.