Abstract. The goal of this roadmap paper is to summarize the stateof-the-art and identify research challenges when developing, deploying and managing self-adaptive software systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-adaptive solutions, software engineering processes for self-adaptive systems, from centralized to decentralized control, and practical run-time verification & validation for self-adaptive systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-adaptive systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.

Context-dependent behavior is becoming increasingly important for a wide range of application domains, from pervasive computing to common business applications. Unfortunately, mainstream programming languages do not provide mechanisms that enable software entities to adapt their behavior dynamically to the current execution context. This leads developers to adopt convoluted designs to achieve the necessary runtime flexibility. We propose a new programming technique called Context-oriented Programming (COP) which addresses this problem. COP treats context explicitly, and provides mechanisms to dynamically adapt behavior in reaction to changes in context, even after system deployment at runtime. In this paper, we lay the foundations of COP, show how dynamic layer activation enables multi-dimensional dispatch, illustrate the application of COP by examples in several language extensions, and demonstrate that COP is largely independent of other commitments to programming style.

No abstract

Reverse engineering is the process of uncovering the design and the design rationale from a functioning software system. Reverse engineering is an integral part of any successful software system, because changing requirements lead to implementations that drift from their original design. In contrast to traditional reverse engineering techniques -which analyse a single snapshot of a system-we focus the reverse engineering effort by determining where the implementation has changed. Since changes of objectoriented software are often phrased in terms of refactorings, we propose a set of heuristics for detecting refactorings by applying lightweight, object-oriented metrics to successive versions of a software system. We validate our approach with three separate case studies of mature object-oriented software systems for which multiple versions are available. The case studies suggest that the heuristics support the reverse engineering process by focusing attention on the relevant parts of a software system.

No abstract

Software metrics offer us the promise of distilling useful information from vast amounts of software in order to track development progress, to gain insights into the nature of the software, and to identify potential problems. Unfortunately, however, many software metrics exhibit highly skewed, nonGaussian distributions. As a consequence, usual ways of interpreting these metrics -for example, in terms of "average" values -can be highly misleading. Many metrics, it turns out, are distributed like wealth -with high concentrations of values in selected locations. We propose to analyze software metrics using the Gini coefficient, a higherorder statistic widely used in economics to study the distribution of wealth. Our approach allows us not only to observe changes in software systems efficiently, but also to assess project risks and monitor the development process itself. We apply the Gini coefficient to numerous metrics over a range of software projects, and we show that many metrics not only display remarkably high Gini values, but that these values are remarkably consistent as a project evolves over time.

O bject-oriented programming techniques promote a new approach to software engineering. By revising "frameworks" of plug-compatible software components [3], reliable, open applications can be largely constructed, rather than programmed. Although the dream of a components-based software industry is very old [9], it is only recently that we appear close to realizing the dream. The reason for this is twofold:• Modern applications are increasingly open in terms of topology, platform and evolution, and so the need for a component-oriented approach to development is even more acute than in the past;• Objects provide an organizational paradigm for decomposing large applications into cooperating objects as well as a reuse paradigm for composing applications from prepackaged software components.

Traits are fine-grained components that can be used to compose classes, while avoiding many of the problems of multiple inheritance and mixin-based approaches. Since most implementations of traits have focused on dynamically-typed languages, the question naturally arises, how can one best introduce traits to statically-typed languages, like Java and C#? In this paper we argue that the flattening property of traits should be used as a guiding principle for any attempt to add traits to statically-typed languages. This property essentially states that, semantically, traits can be compiled away. We demonstrate how this principle applies to Featherweight-Trait Java, a conservative extension to Featherweight Java.