JEqualityGen

Abstract

Manually implementing equals (for object comparisons) and hashCode (for object hashing) methods in large software projects is tedious and error-prone. This is due to many special cases, such as field shadowing, comparison between different types, or cyclic object graphs. Here, we present JEqualityGen, a source code generator that automatically derives implementations of these methods.JEqualityGen proceeds in two states: it first uses source code reflection in MetaAspectJ to generate aspects that contain the method implementations, before it uses weaving on the bytecode level to insert these into the target application. JEqualityGen generates not only correct, but efficient source code that on a typical large-scale Java application exhibits a performance improvement of more than two orders of magnitude in the equality operations generated, compared to an existing system based on runtime reflection. JEquality-Gen achieves this by generating runtime profiling code that collects data. This enables it to generate optimised method implementations in a second round.

Semi-automated Algorithm for Complex Test Data Generation for Interface-based Regression Testing of Software Components

“…There are also several papers focused on object equality. In [24], the equals() method generator for complex objects is discussed. Deep equality is described recursively.…”

Deep Object Comparison for Interface-based Regression Testing of Software Components

“…A generator of the equals() methods for complex objects is described in [16]. In this work, the objects are compared on per-field basis.…”

“…Depth-1 (shallow equality) means that, for all corresponding fields of two objects, the referential equality holds. The deep equality then means that, for all corresponding fields of two objects, the deep equality holds [16].…”

“…As arises from Section III, there are various views on the equality of two objects. Nevertheless, since our goal is to uncover any difference of the compared objects, however subtle, we have to adopt the view of the deep equality described in [16]. Similar definitions are described also in [7], [10], or [11].…”

“…Since the DOC algorithm creates a graph representing the internal structure of the object, our definition is based on this graph. It is not recursive, but expresses similar conditions as the definition of the deep equality described in [16].…”