Towards Bridging the Gap between Control and Self-Adaptive System PropertiesNIER
Two of the main paradigms used to build adaptive software employ different types of properties to capture relevant aspects of the system’s run-time behavior. On the one hand, control systems consider properties that concern static aspects like stability, as well as dynamic properties that capture the transient evolution of variables such as settling time. On the other hand, self-adaptive systems consider mostly non-functional properties that capture concerns such as performance, reliability, and cost. In general, it is not easy to reconcile these two types of properties or identify under which conditions they constitute a good fit to provide run-time guarantees. There is a need of identifying the key properties in the areas of control and self-adaptation, as well as of characterizing and mapping them to better understand how they relate and possibly complement each other. In this paper, we take a first step to tackle this problem by: (1) identifying a set of key properties in control theory, (2) illustrating the formalization of some of these properties employing temporal logic languages commonly used to engineer self-adaptive software systems, and (3) illustrating how to map key properties that characterize self-adaptive software systems into control properties, leveraging their formalization in temporal logics. We illustrate the different steps of the mapping on an exemplar case in the cloud computing domain and conclude with identifying open challenges in the area.
Tue 30 Jun Times are displayed in time zone: (UTC) Coordinated Universal Time change
06:00 - 07:30: Session 2: Testing, Analysis, Reasoning, and MonitoringSEAMS 2020 at SEAMS Chair(s): Sona GhahremaniHasso Plattner Institute, University of Potsdam | |||
06:00 - 06:05 Talk | Leveraging Test Logs for Building a Self-Adaptive Path PlannerNIER SEAMS 2020 Kun LiuPeking University, China, Xiaoyi ZhangNational Institute of Informatics, Japan, Paolo ArcainiNational Institute of Informatics
, Fuyuki IshikawaNational Institute of Informatics, Wenpin JiaoPeking University, China Pre-print Media Attached | ||
06:05 - 06:10 Talk | Supporting Viewpoints to Review the Lack of Requirements in Space Systems with Machine LearningExperience SEAMS 2020 Kenji MoriJapan Aerospace Exploration Agency, Japan, Naoko OkuboJapan Aerospace Exploration Agency, Japan, Yasushi UedaJapan Aerospace Exploration Agency, Japan, Masafumi KatahiraJapan Aerospace Exploration Agency, Toshiyuki AmagasaUniversity of Tsukuba, Japan Media Attached | ||
06:10 - 06:15 Talk | DATESSO: Self-Adapting Service Composition with Debt-Aware Two Levels Constraint ReasoningTechnicalBest Student Paper SEAMS 2020 Satish KumarUniversity of Birmingham, United Kingdom, Tao ChenLoughborough University, Rami BahsoonUniversity of Birmingham, Rajkumar BuyyaUniversity of Melbourne, Australia DOI Pre-print Media Attached | ||
06:15 - 06:20 Talk | Towards Bridging the Gap between Control and Self-Adaptive System PropertiesNIER SEAMS 2020 Javier CamaraUniversity of York, Alessandro Vittorio PapadopoulosMälardalen University, Thomas VogelHumboldt-Universität zu Berlin, Danny WeynsKU Leuven, David GarlanCarnegie Mellon University, Shihong HuangFlorida Atlantic University, Kenji TeiWaseda University / National Institute of Informatics, Japan DOI Pre-print Media Attached | ||
06:20 - 06:25 Talk | Explanation for Human-on-the-loop: a probabilistic model checking approachNIER SEAMS 2020 NIANYU LIPeking University, China, Sridhar AdepuSingapore University of Technology and Design, Singapore, Eunsuk KangCarnegie Mellon University, David GarlanCarnegie Mellon University Pre-print Media Attached | ||
06:25 - 07:30 Other | Q&A and Discussion (Session 2) SEAMS 2020 |