TitleDynamically discovering likely program invariants to support program evolution
Publication TypeJournal Article
Year of Publication2001
AuthorsErnst MD, Cockrell J, Griswold WG, Notkin D
JournalIEEE Transactions on Software Engineering
Volume27
Pagination99–123
Date or Month PublishedFebruary
Abstract

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 likely invariants from the program itself. This research focuses on dynamic techniques for discovering invariants from execution traces.

This article reports three results. First, it describes techniques for dynamically discovering invariants, along with an implementation, named Daikon, that embodies these techniques. Second, it reports on the application of Daikon to two sets of target programs. In programs from Gries's work on program derivation, the system rediscovered predefined invariants. In a C program lacking explicit invariants, the system discovered invariants that assisted a software evolution task. These experiments demonstrate that, at least for small programs, invariant inference is both accurate and useful. Third, it analyzes scalability issues such as invariant detection runtime and accuracy as functions of test suites and program points instrumented.

Downloadshttp://homes.cs.washington.edu/~mernst/pubs/invariants-icse99.pdf ICSE 1999 paper (PDF) http://homes.cs.washington.edu/~mernst/pubs/invariants-icse99-slides.ppt ICSE 1999 talk slides (PowerPoint) http://homes.cs.washington.edu/~mernst/pubs/invariants-icse99-slides.pdf ICSE 1999 talk slides (PDF) http://plse.cs.washington.edu/daikon/ Daikon implementation http://homes.cs.washington.edu/~mernst/pubs/invariants-tse2001.pdf PDF
Citation KeyErnstCGN2001:TSE