Claus Lewerentz

Software cities are visualizations of software systems in the form of virtual cities. They are used as platforms to integrate a large variety of product- and process-related analysis data. Their usability, however, for real-world software development often suffers from their inability to appropriately deal with software changes. Even small structural changes can disrupt the overall structure of the city, which in turn corrupts the mental maps of its users. In this article we describe a systematic approach to utilize the city metaphor for the visualization of evolving software systems as growing software cities. The main contribution is a new layout approach which explicitly takes the development history of software systems into account. The approach has two important effects: first, it creates a stable gestalt of software cities even when the underlying software systems evolve; thus, by preserving its users’ mental maps these cities are especially suitable for use during ongoing system development. Second, it makes history directly visible in the city layouts, which allows for supporting novel analysis scenarios. We illustrate such scenarios by presenting several thematic cities’ maps, each capturing specific development history aspects.

Software Product Lines are a strategic long-term investment and must evolve to meet new requirements over many years. In previous work, we have shown a model-driven approach (called EvoPL [21]) for planning and managing long-term evolution of product lines. It allows specifying historic and planned future evolution in terms of changes on feature model level. It provides benefits like abstraction, efficiency through automation, and the capability to perform analysis based on models. In this paper, we argue that specifying changes alone is beneficial but not sufficient. This is because for strategic evolution planning "decision drivers" like goals, requirements, and rationale are essential information as well. Hence, we propose a modeling approach that represents such decision drivers and their interrelationships. The approach is based on concepts from literature (e.g., QOC and goal-oriented requirements engineering) and combines and extends them to address the specific needs of model-driven long-term evolution management. Beyond the basic usage for documentation, the suggested models can be used for systematic future planning and tool-supported analysis, e.g., to evaluate the consistency of planned evolutionary changes.

In this paper we describe a systematic approach to utilize the city metaphor for the visualization of large software systems as evolving software cities. The main contribution is a new layout approach which explicitly takes the development history of software systems into account and makes history directly visible in the layouts. These layouts incrementally evolve in a very smooth and stable way during the development of the represented software system. They are used as a visualization platform for integrating a large variety of product and process data and thus create a coherent set of specialized visualizations. To illustrate this we present some example maps capturing specific development history aspects.

Hierarchical graphs are widely used as models of the structure of software systems. A central problem in the visualization of hierarchical graphs is the computation of layouts, i.e. of positions of the nodes in two- or three-dimensional space. We derive requirements for graph layouts from various software analysis questions, and classify the required layouts along three dimensions: layouts with meaningful distances between single nodes vs. layouts with meaningful distances between groups of nodes, layouts reflecting adjacency vs. layouts reflecting hierarchy, and layouts that faithfully reflect the size of subgraphs vs. layouts where certain subgraphs are magnified. We present a fairly simple and theoretically validated energy model for computing such layouts.

Calculating with graphs and relations has many applications in the analysis of software systems, for example, the detection of design patterns or patterns of problematic design and the computation of design metrics. These applications require an expressive query language, in particular, for the detection of graph patterns, and an efficient evaluation of the queries even for large graphs. In this paper, we introduce RML, a simple language for querying and manipulating relations based on predicate calculus, and CrocoPat, an interpreter for RML programs. RML is general because it enables the manipulation not only of graphs (i.e., binary relations), but of relations of arbitrary arity. CrocoPat executes RML programs efficiently because it internally represents relations as binary decision diagrams, a data structure that is well-known as a compact representation of large relations in computer-aided verification. We evaluate RML by giving example programs for several software analyses and CrocoPat by comparing its performance with calculators for binary relations, a Prolog system, and a relational database management system.