Abstract. The goal of this roadmap paper is to summarize the state-ofthe-art and to identify critical challenges for the systematic software engineering of self-adaptive systems. The paper is partitioned into four parts, one for each of the identified essential views of self-adaptation: modelling dimensions, requirements, engineering, and assurances. For each view, we present the state-of-the-art and the challenges that our community must address. This roadmap paper is a result of the Dagstuhl Seminar 08031 on "Software Engineering for Self-Adaptive Systems, " which took place in January 2008.

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.

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Reverse‐engineering is the process of extracting system abstractions and design information out of existing software systems. This process involves the identification of software artefacts in a particular subject system, the exploration of how these artefacts interact with one another, and their aggregation to form more abstract system representations that facilitate program understanding. This paper describes our approach to creating higher‐level abstract representations of a subject system, which involves the identification of related components and dependencies, the construction of layered subsystem structures, and the computation of exact interfaces among subsystems. We show how top‐down decompositions of a subject system can be (re)constructed via bottom‐up subsystem composition. This process involves identifying groups of building blocks (e.g., variables, procedures, modules, and subsystems) using composition operations based on software engineering principles such as low coupling and high cohesion. The result is an architecture of layered subsystem structures. The structures are manipulated and recorded using the Rigi system, which consists of a distributed graph editor and a parsing system with a central repository. The editor provides graph filters and clustering operations to build and explore subsystem hierarchies interactively. The paper concludes with a detailed, step‐by‐step analysis of a 30‐module software system using Rigi.

Over the past decade the dynamic capabilities of self-adaptive software-intensive systems have proliferated and improved significantly. To advance the field of self-adaptive and selfmanaging systems further and to leverage the benefits of selfadaptation, we need to develop methods and tools to assess and possibly certify adaptation properties of self-adaptive systems, not only at design time but also, and especially, at run-time. In this paper we propose a framework for evaluating quality-driven self-adaptive software systems. Our framework is based on a survey of self-adaptive system papers and a set of adaptation properties derived from control theory properties. We also establish a mapping between these properties and software quality attributes. Thus, corresponding software quality metrics can then be used to assess adaptation properties.

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Shimba is a reverse engineering environment to support the understanding of Java software systems. Shimba integrates the Rigi and SCED tools to analyze and visualize the static and dynamic aspects of a subject system. The static software artifacts and their dependencies are extracted from Java byte code and viewed as directed graphs using the Rigi reverse engineering environment. The run‐time information is generated by running the target software under a customized SDK debugger. The generated information is viewed as sequence diagrams using the SCED tool. In SCED, statechart diagrams can be synthesized automatically from sequence diagrams, allowing the user to investigate the overall run‐time behavior of objects in the target system. Shimba provides facilities to manage the different diagrams and to trace artifacts and relations across views. In Shimba, SCED sequence diagrams are used to slice the static dependency graphs produced by Rigi. In turn, Rigi graphs are used to guide the generation of SCED sequence diagrams and to raise their level of abstraction. We show how the information exchange among the views enables goal‐driven reverse engineering tasks and aids the overall understanding of the target software system. The FUJABA software system serves as a case study to illustrate and validate the Shimba reverse engineering environment. Copyright © 2001 John Wiley & Sons, Ltd.