Zone-based formal specification and timing analysis of real-time self-adaptive systems

Camilli, Matteo; Gargantini, Angelo; Scandurra, Patrizia

doi:10.1016/j.scico.2018.03.002

Cited by 15 publications

(4 citation statements)

References 72 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Key trends for this domain were adaptive, scalable, and robust systems. These systems are proactively aware of latency and can act in swarms [34], [52], [81], [151], [188].…”

Section: -2020 -The Last Decade -Second Halfmentioning

confidence: 99%

Self-Adaptive Systems: A Systematic Literature Review Across Categories and Domains

Wong¹,

Wagner²

2021

Preprint

View full text Add to dashboard Cite

Championed by IBM's vision of autonomic computing paper in 2003, the autonomic computing research field has seen increased research activity over the last 20 years. Several conferences (SEAMS, SASO, ICAC) and workshops (SISSY) have been established and have contributed to the autonomic computing knowledge base in search of a new kind of system -a self-adaptive system (SAS). These systems are characterized by being context-aware and can act on that awareness. The actions carried out could be on the system or on the context (or environment). The underlying goal of a SAS is the sustained achievement of its goals despite changes in its environment. Despite a number of literature reviews on specific aspects of SASs ranging from their requirements to quality attributes, we lack a systematic understanding of the current state of the art. This paper contributes a systematic literature review into self-adaptive systems using the dblp computer science bibliography as a database. We filtered the records systematically in successive steps to arrive at 293 relevant papers. Each paper was critically analyzed and categorized into an attribute matrix. This matrix consisted of five categories, with each category having multiple attributes. The attributes of each paper, along with the summary of its contents formed the basis of the literature review that spanned 30 years . We characterize the maturation process of the research area from theoretical papers over practical implementations to more holistic and generic approaches, frameworks, and exemplars, applied to areas such as networking, web services, and robotics, with much of the recent work focusing on IoT and IaaS.

show abstract

“…Key trends for this domain were adaptive, scalable, and robust systems. These systems are proactively aware of latency and can act in swarms [34], [52], [81], [151], [188].…”

Section: -2020 -The Last Decade -Second Halfmentioning

confidence: 99%

Self-Adaptive Systems: A Systematic Literature Review Across Categories and Domains

Wong¹,

Wagner²

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Many pieces of work, inside the community of self-adaptive systems, aim at making adaptation decisions taking into account the sources of uncertainty. Notable examples include recent activities by Camilli et al [35], Ramirez et al [19], and Esfahani and Malek [1]. Most of them employ Markov models to express uncertain QoS properties and make decisions under probability theory.…”

Section: Design-time Uncertainty Assessmentmentioning

confidence: 99%

Model‐based hypothesis testing of uncertain software systems

Camilli

Gargantini

Scandurra

2020

Software Testing Verif & Rel

Self Cite

View full text Add to dashboard Cite

Nowadays, there exists an increasing demand for reliable software systems able to fulfill their requirements in different operational environments and to cope with uncertainty that can be introduced both at design-time and at runtime because of the lack of control over third-party system components and complex interactions among software, hardware infrastructures and physical phenomena. This article addresses the problem of the discrepancy between measured data at runtime and the design-time formal specification by using an inverse uncertainty quantification approach. Namely, we introduce a methodology called METRIC and its supporting toolchain to quantify and mitigate software system uncertainty during testing by combining (on-the-fly) model-based testing and Bayesian inference. Our approach connects probabilistic input/output conformance theory with statistical hypothesis testing in order to assess if the behaviour of the system under test corresponds to its probabilistic formal specification provided in terms of a Markov decision process. An uncertainty-aware model-based test case generation strategy is used as a means to collect evidence from software components affected by sources of uncertainty. Test results serve as input to a Bayesian inference process that updates beliefs on model parameters encoding uncertain quality attributes of the system under test. This article describes our approach from both theoretical and practical perspectives. An extensive empirical evaluation activity has been conducted in order to assess the cost-effectiveness of our approach. We show that, under same effort constraints, our uncertainty-aware testing strategy increases the accuracy of the uncertainty quantification process up to 50 times with respect to traditional model-based testing methods. of uncertainty away because of insufficient understanding and unavailability of adequate methods and techniques. Today, endowing conventional software engineering methodologies with techniques and practices able to model, quantify, and manage uncertainty explicitly is becoming increasingly crucial [1,2]. In particular, techniques that explicitly consider uncertainty in software testing is an emerging research direction.This article focuses on the problem of uncertainty quantification and introduces a methodology able to deal with it by means of a model-based hypothesis testing approach. Namely, we use statistical hypothesis testing to reduce the discrepancy between delivered products and initial design-time uncertainty assumptions. As described by Broy at al.[3], model-based testing (MBT) is a software testing technique where runtime behaviour of a software system under test (SUT) is checked against predictions made by a model description of the system's behaviour. In our approach, the design-time model description contains uncertain aspects explicitly specified by means of probability. Uncertainty must be mitigated accounting for evidence during the actual system's execution. Thus, we make use of (on-the-fly) MBT as a means to extrac...

show abstract

“…The authors also mentioned that KAOS approach to model the adaptation goals. In the V&V domain, aiming at the temporal dependent correctness, a zone-based Time Basic Petri nets specification formalism is designed to model the timed self-adaptation behavior and to verify the timed robustness properties of self-healing [ 182 ]. The framework can divide the Petri nets into several zones to simplify verification of intra-zone properties, and apply inter-zone evaluation the global properties.…”

Section: The Safety Of Self-adaptation Strategies and The Dependabmentioning

confidence: 99%

A Comprehensive Technological Survey on the Dependable Self-Management CPS: From Self-Adaptive Architecture to Self-Management Strategies

Zhou

Zuo

Hou

et al. 2019

Sensors

View full text Add to dashboard Cite

Cyber Physical Systems (CPS) has been a popular research area in the last decade. The dependability of CPS is still a critical issue, and few surveys have been published in this domain. CPS is a dynamic complex system, which involves various multidisciplinary technologies. To avoid human errors and to simplify management, self-management CPS (SCPS) is a wise choice. To achieve dependable self-management, systematic solutions are necessary to verify the design and to guarantee the safety of self-adaptation decisions, as well as to maintain the health of SCPS. This survey first recalls the concepts of dependability, and proposes a generic environment-in-loop processing flow of self-management CPS, and then analyzes the error sources and challenges of self-management through the formal feedback flow. Focusing on reducing the complexity, we first survey the self-adaptive architecture approaches and applied dependability means, then we introduce a hybrid multi-role self-adaptive architecture, and discuss the supporting technologies for dependable self-management at the architecture level. Focus on dependable environment-centered adaptation, we investigate the verification and validation (V&V) methods for making safe self-adaptation decision and the solutions for processing decision dependably. For system-centered adaptation, the comprehensive self-healing methods are summarized. Finally, we analyze the missing pieces of the technology puzzle and the future directions. In this survey, the technical trends for dependable CPS design and maintenance are discussed, an all-in-one solution is proposed to integrate these technologies and build a dependable organic SCPS. To the best of our knowledge, this is the first comprehensive survey on dependable SCPS building and evaluation.

show abstract

Zone-based formal specification and timing analysis of real-time self-adaptive systems

Cited by 15 publications

References 72 publications

Self-Adaptive Systems: A Systematic Literature Review Across Categories and Domains

Self-Adaptive Systems: A Systematic Literature Review Across Categories and Domains

Model‐based hypothesis testing of uncertain software systems

A Comprehensive Technological Survey on the Dependable Self-Management CPS: From Self-Adaptive Architecture to Self-Management Strategies

Contact Info

Product

Resources

About