SEAMS 2018 - 13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems

Modern and emerging software systems, such as industrial Internet of Things, Cyber-Physical Systems, cloud and mobile computing, have to operate without interruption. Self-adaptation and self-management enable these systems to adapt themselves at runtime to preserve and optimize their operation in the presence of uncertain changes in their operating environment, resource variability, new user needs, attacks, intrusions, and faults.
Approaches to complement software-based systems with self-managing and self-adaptive capabilities are an important area of research and development, offering solutions that leverage advances in fields such as software architecture, fault-tolerant computing, programming languages, robotics, run-time program analysis and verification, among others. Additionally, research in this field is informed by related areas such as control systems, machine learning, artificial intelligence, agent-based systems, and biologically inspired computing. The SEAMS symposium focuses on applying software engineering to these approaches, including methods, techniques, processes and tools that can be used to support self-* properties like self-protection, self-healing, self-optimization, and self-configuration.
The objective of SEAMS is to bring together researchers and practitioners from diverse areas to investigate, discuss, and examine the fundamental principles, the state of the art, and critical challenges of engineering self-adaptive and self-managing systems.
Topics of Interest:
All topics related to engineering self-adaptive and self-managing systems, including:
Foundational Concepts
Understanding and taming uncertainty
Runtime models and variability
Online analysis and planning
Consistent change of systems in operation
Mixed-initiative and human-in-the-loop systems
Adaptation Objectives
Self-* properties
Automatic configuration, openness
Adaptive security and privacy (SEAMS’18 will devote a special session on this topic)
Engineering Strategies
Architecture and model-driven approaches
Control theory
Automatic synthesis techniques
Search-based techniques and learning
Engineering Activities
Requirements elicitation techniques
Architecture and design techniques
Systematic reuse (e.g., patterns, viewpoints, reference architectures, code)
Instrumentation of legacy systems (probing and effecting)
Processes and methodologies
Adaptation in the context of DevOps
Real-world demonstrators
Controlled experiments, case studies, replication studies, surveys
Analytical Methods
Runtime decision-making (multi-objective, multi-layered, distributed)
Analysis and testing frameworks
Verification and validation
Simulation
Languages
Formal notations for modeling and analyzing self-* properties
Domain-specific language support for self-adaptation
Programming language support for self-adaptation
Application Areas
Industrial internet of things
Cyber-physical systems
Cloud and edge computing
Robotics
Smart environments
Smart user interfaces
Artifacts
Model problems and exemplars
Resources including data sets, metrics, and software useful to compare self-adaptive approaches