Change prediction helps developers by recommending program entities that will have to be changed alongside the entities currently being changed. To evaluate their accuracy, current change prediction approaches use data from versioning systems such as CVS or SVN. These data sources provide a coarse-grained view of the development history that flattens the sequence of changes in a single commit. They are thus not a valid basis for evaluation in the case of development-style prediction, where the order of the predictions has to match the order of the changes a developer makes. We propose a benchmark for the evaluation of change prediction approaches based on fine-grained change data recorded from IDE usage. Moreover, the change prediction approaches themselves can use the more accurate data to fine-tune their prediction. We present an evaluation procedure and use it on several change prediction approaches, both novel and from the literature, and report on the results.

Mainstream IDEs generally rely on the static structure of a software project to support browsing and navigation. We propose HeatMaps, a simple but highly configurable technique to enrich the way an IDE displays the static structure of a software system with additional kinds of information. A HeatMap highlights software artifacts according to various metric values, such as bright red or pale blue, to indicate their potential degree of interest. We present a prototype system that implements HeatMaps, and we describe an initial study that assesses the degree to which different HeatMaps effectively guide developers in navigating software.

To maintain and understand large applications, it is important to know their architecture. The first problem is that unlike classes and packages, architecture is not explicitly represented in the code. The second problem is that successful applications evolve over time, so their architecture inevitably drifts. Reconstructing the architecture and checking whether it is still valid is therefore an important aid. While there is a plethora of approaches and techniques supporting architecture reconstruction, there is no comprehensive software architecture reconstruction state of the art and it is often difficult to compare the approaches. This paper presents a state of the art in software architecture reconstruction approaches.

Large object-oriented applications are structured over large number of packages. Packages are important but complex structural entities that may be difficult to understand since they play different development roles (i.e., class containers, code ownership basic structure, architectural elements...). Maintainers of large applications face the problem of understanding how packages are structured in general and how they relate to each others. In this paper, we present a compact visualization, named Package Surface Blueprint, that qualifies the relationships that a package has with its neighbours. A Package Surface Blueprint represents packages around the notion of package surfaces: groups of relationships according to the packages they refer to. We present two specific views one stressing the references made by a package and another showing the inheritance structure of a package. We applied the visualization on two large case studies: ArgoUML and Squeak.

In this article, we investigate the use of the OO computational paradigm for the formulation of knowledge model patterns as OO analysis patterns. We seek to take advantage of research on design pattern specification, aimed at modelling patterns by means of structural and behavioural "meta-level" constraints, introducing appropriate modifications into the UML. We illustrate our argument with the formulation of an OO "assessment pattern" in analogy to the well known "assessment task template".