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## 1 Introduction

Daikon is an implementation of dynamic detection of likely invariants; that is, the Daikon invariant detector reports likely program invariants. An invariant is a property that holds at a certain point or points in a program; these are often seen in assert statements, documentation, and formal specifications. Invariants can be useful in program understanding and a host of other applications. Examples include ‘`x.field > abs(y)`’; ‘`y = 2*x+3`’; ‘`array a is sorted`’; for all list objects lst, ‘`lst.next.prev = lst`’; for all treenode objects n, ‘`n.left.value < n.right.value`’; ‘`p != null => p.content in myArray`’; and many more. You can extend Daikon to add new properties (see Enhancing Daikon output, or see New invariants in Daikon Developer Manual).

Dynamic invariant detection runs a program, observes the values that the program computes, and then reports properties that were true over the observed executions. Daikon can detect properties in C, C++, C#, Eiffel, F#, Java, Perl, and Visual Basic programs; in spreadsheet files; and in other data sources. (Dynamic invariant detection is a machine learning technique that can be applied to arbitrary data.) It is easy to extend Daikon to other applications.

Daikon is freely available for download from download-site. Daikon’s license permits unrestricted use (see License). The distribution includes both source code (also available on GitHub) and documentation, Many researchers and practitioners have used Daikon; those uses, and Daikon itself, are described in various publications.

For more information on Daikon, see Introduction in Daikon Developer Manual. For instance, the Daikon Developer Manual indicates how to obtain Daikon’s source code and how to extend Daikon with new invariants, new derived variables, and front ends for new languages. It also contains information about the implementation and about debugging flags.

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