SARDE

2021 ◽  
Vol 15 (2) ◽  
pp. 1-31
Author(s):  
Johannes Grohmann ◽  
Simon Eismann ◽  
André Bauer ◽  
Simon Spinner ◽  
Johannes Blum ◽  
...  
Keyword(s):  
Adaptive Systems ◽  
System Analysis ◽  
Demand Estimation ◽  
Software Systems ◽  
Resource Demand ◽  
Ensemble Technique ◽  
Constant Change ◽  
Ensemble Estimation ◽  
System States ◽  
Adaptive Resource

Resource demands are crucial parameters for modeling and predicting the performance of software systems. Currently, resource demand estimators are usually executed once for system analysis. However, the monitored system, as well as the resource demand itself, are subject to constant change in runtime environments. These changes additionally impact the applicability, the required parametrization as well as the resulting accuracy of individual estimation approaches. Over time, this leads to invalid or outdated estimates, which in turn negatively influence the decision-making of adaptive systems. In this article, we present SARDE , a framework for self-adaptive resource demand estimation in continuous environments. SARDE dynamically and continuously tunes, selects, and executes an ensemble of resource demand estimation approaches to adapt to changes in the environment. This creates an autonomous and unsupervised ensemble estimation technique, providing reliable resource demand estimations in dynamic environments. We evaluate SARDE using two realistic datasets. One set of different micro-benchmarks reflecting different possible system states and one dataset consisting of a continuously running application in a changing environment. Our results show that by continuously applying online optimization, selection and estimation, SARDE is able to efficiently adapt to the online trace and reduce the model error using the resulting ensemble technique.

A control method to suppress the swing vibration of a hybrid excavator using sliding mode approach

2011 ◽  
Vol 226 (5) ◽  
pp. 1237-1253 ◽  
Author(s):  
K Jin ◽  
T Park ◽  
H Lee
Keyword(s):  
System Analysis ◽  
Dynamic Models ◽  
Control Method ◽  
Sliding Mode ◽  
Robust Tracking ◽  
Parameter Variations ◽  
Identification Technique ◽  
Integral Controller ◽  
System States ◽  
Hybrid Excavator

This article presents a control method for suppressing the swing vibration of a hybrid excavator. For control design, dynamic models of typical swing motions of the hybrid excavator are derived using a system identification technique. Because the system states of theobtained models are not directly measurable, a sliding mode observer is designed to estimate the system states. A sliding mode control is designed to provide robust tracking performance against the parameter variations and uncertain non-linearities caused by changes in the working conditions. A complicated mathematical model of the hybrid excavator which captures detailed mechanical, electrical, and hydraulic characteristics is developed for system analysis and simulation. The feasibility and effectiveness of the proposed control method are verified by simulations and actual tests in comparison with a conventional proportional and integral controller.

Speech as a breakthrough signaling resource in the cognitive evolution of biological complex adaptive systems

2014 ◽  
Vol 37 (6) ◽  
pp. 563-564 ◽  
Author(s):  
Tobias A. Mattei
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
System Analysis ◽  
Complex Adaptive System ◽  
Brain Structures ◽  
Human Cognition ◽  
Evolutionary Development ◽  
Complex Adaptive ◽  
Triggering Events ◽  
The Brain

AbstractIn self-adapting dynamical systems, a significant improvement in the signaling flow among agents constitutes one of the most powerful triggering events for the emergence of new complex behaviors. Ackermann and colleagues' comprehensive phylogenetic analysis of the brain structures involved in acoustic communication provides further evidence of the essential role which speech, as a breakthrough signaling resource, has played in the evolutionary development of human cognition viewed from the standpoint of complex adaptive system analysis.

ON SOME RECENT ADVANCES IN COMPLEX SOFTWARE NETWORKS: MODELING, ANALYSIS, EVOLUTION AND APPLICATIONS

2012 ◽  
Vol 22 (02) ◽  
pp. 1250024 ◽  
Author(s):  
HONGCHUN WANG ◽  
KEQING HE ◽  
BING LI ◽  
JINHU LÜ
Keyword(s):  
Complex Networks ◽  
Real World ◽  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Point Of View ◽  
Future Research ◽  
Software Systems ◽  
Recent Advances ◽  
Modeling Analysis ◽  
Real World Applications

Complex software networks, as a typical kind of man-made complex networks, have attracted more and more attention from various fields of science and engineering over the past ten years. With the dramatic increase of scale and complexity of software systems, it is essential to develop a systematic approach to further investigate the complex software systems by using the theories and methods of complex networks and complex adaptive systems. This paper attempts to briefly review some recent advances in complex software networks and also develop some novel tools to further analyze complex software networks, including modeling, analysis, evolution, measurement, and some potential real-world applications. More precisely, this paper first describes some effective modeling approaches for characterizing various complex software systems. Based on the above theoretical and practical models, this paper introduces some recent advances in analyzing the static and dynamical behaviors of complex software networks. It is then followed by some further discussions on potential real-world applications of complex software networks. Finally, this paper outlooks some future research topics from an engineering point of view.

scholarly journals Towards a Requirements Specification Multi-View Framework for Self-Adaptive Systems

2015 ◽  
Author(s):  
Juan C. Muñoz-Fernández ◽  
Gabriel Tamura ◽  
Raúl Mazo ◽  
Camille Salinesi
Keyword(s):  
Adaptive Systems ◽  
Software Tool ◽  
Software Systems ◽  
Functional Requirements ◽  
Requirements Modeling ◽  
Sufficient Power ◽  
Depth Analysis ◽  
Context Variables ◽  
Difficult Challenge ◽  
Self Adaptive

The analysis of self-adaptive systems (SAS) requirements involves addressing uncertainty from several sources. Despite advances in requirements for SAS, uncertainty remains an extremely difficult challenge. In this paper, we propose REFAS, a framework to model the requirements of self-adaptive software systems. Our aim with REFAS is to address and reduce uncertainty and to provide a language with sufficient power of expression to specify the different aspects of self-adaptive systems, relative to functional and non-functional requirements. The REFAS modeling language includes concepts closely related to these kind of requirements and their fulfillment, such as context variables, claims, and soft dependencies. Specifically, the paper´s contribution is twofold. First, REFAS supports different viewpoints and concerns related to requirements modeling, with key associations between them. Moreover, the modeler can define additional models and views by exploiting the REFAS meta-modeling capability, in order to capture additional aspects contributing to reduce uncertainty. Second, REFAS promotes in-depth analysis of all of the modeled concerns with aggregation and association capabilities, especially with context variables. Furthermore, we also define a process that enforces modeling requirements, considering different aspects of uncertainty. We demonstrate the applicability of REFAS by using the VariaMos software tool, which implements the REFAS meta-model, views, and process.

On the Rim Between Business Processes and Software Systems

2019 ◽  
pp. 170-196 ◽  
Author(s):  
Maria Estrela Ferreira da Cruz ◽  
Ricardo J. Machado ◽  
Maribel Yasmina Santos
Keyword(s):  
Software Development ◽  
Business Process ◽  
Process Model ◽  
Process Management ◽  
Business Processes ◽  
Process Models ◽  
Software Systems ◽  
Business Process Model ◽  
Constant Change ◽  
Development Processes

The constant change and rising complexity of organizations, mainly due to the transforming nature of their business processes, has driven the increase of interest in business process management by organizations. It is recognized that knowing business processes can help to ensure that the software under development will meet the business needs. Some of software development processes (like unified process) already refer to business process modeling as a first effort in the software development process. A business process model usually is created under the supervision, clarification, approval, and validation of the business stakeholders. Thus, a business process model is a proper representation of the reality (as is or to be), having lots of useful information that can be used in the development of the software system that will support the business. The chapter uses the information existing in business process models to derive software models specially focused in generating a data model.

Building Complex Adaptive Systems

2008 ◽  
pp. 229-256 ◽  
Author(s):  
Jan Sudeikat ◽  
Wolfgang Renz
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Software Systems ◽  
Computational Techniques ◽  
Multi Agent Systems ◽  
Software Applications ◽  
Agent Oriented Software Engineering ◽  
Complex Adaptive ◽  
Multi Agent ◽  
Self Organizing

Agent Oriented Software-Engineering (AOSE) proposes the design of distributed software systems as collections of autonomous and pro-active actors, so-called agents. Since software applications results from agent interplay in Multi-Agent Systems (MAS), this design approach facilitates the construction of software applications that exhibit self-organizing and emergent dynamics. In this chapter, we examine the relation between self-organizing MAS and Complex Adaptive Systems (CAS), highlighting the resulting challenges for engineering approaches. We argue that AOSE developers need to be aware of the possible causes of complex system dynamics, which result from underlying feedback loops. In this respect current approaches to develop SO-MAS are analyzed, leading to a novel classification scheme of typically applied computational techniques. To relieve development efforts and bridge the gap between top-down engineering and bottom-up emerging phenomena, we discuss how multi-level analysis, so-called mesoscopic modeling, can be used to comprehend MAS dynamics and guide agent design, respectively iterative redesign.

Addressing Privacy in Traditional and Cloud-Based Systems

2017 ◽  
pp. 1900-1930
Author(s):  
Christos Kalloniatis ◽  
Evangelia Kavakli ◽  
Stefanos Gritzalis
Keyword(s):  
Credit Card ◽  
System Analysis ◽  
Systems Design ◽  
Personal Data ◽  
Research Area ◽  
Security And Privacy ◽  
Software Systems ◽  
Privacy Requirements ◽  
Credit Card Data ◽  
Privacy Violation

A major challenge in the field of software engineering is to make users trust the software that they use in their everyday activities for professional or recreational reasons. Amid the main criteria that formulate users' trust is the way that that their privacy is protected. Indeed, privacy violation is an issue of great importance for active online users that daily accomplish several transactions that may convey personal data, sensitive personal data, employee data, credit card data and so on. In addition, the appearance of cloud computing has elevated the number of personally identifiable information that users provide in order to gain access to various services, further raising user concerns as to how and to what extend information about them is communicated to others. The aim of this work is to elevate the modern practices for ensuring privacy during software systems design. To this end, the basic privacy requirements that should be considered during system analysis are introduced. Additionally, a number of well-known methods that have been introduced in the research area of requirements engineering which aim on eliciting and modeling privacy requirements during system design are introduced and critically analyzed. The work completes with a discussion of the additional security and privacy concepts that should be considered in the context of cloud-based information systems and how these affect current research.

Addressing Privacy in Traditional and Cloud-Based Systems

2015 ◽  
pp. 1631-1659
Author(s):  
Christos Kalloniatis ◽  
Evangelia Kavakli ◽  
Stefanos Gritzalis
Keyword(s):  
Credit Card ◽  
System Analysis ◽  
Systems Design ◽  
Personal Data ◽  
Research Area ◽  
Security And Privacy ◽  
Software Systems ◽  
Privacy Requirements ◽  
Credit Card Data ◽  
Privacy Violation

A major challenge in the field of software engineering is to make users trust the software that they use in their everyday activities for professional or recreational reasons. Amid the main criteria that formulate users' trust is the way that that their privacy is protected. Indeed, privacy violation is an issue of great importance for active online users that daily accomplish several transactions that may convey personal data, sensitive personal data, employee data, credit card data and so on. In addition, the appearance of cloud computing has elevated the number of personally identifiable information that users provide in order to gain access to various services, further raising user concerns as to how and to what extend information about them is communicated to others. The aim of this work is to elevate the modern practices for ensuring privacy during software systems design. To this end, the basic privacy requirements that should be considered during system analysis are introduced. Additionally, a number of well-known methods that have been introduced in the research area of requirements engineering which aim on eliciting and modeling privacy requirements during system design are introduced and critically analyzed. The work completes with a discussion of the additional security and privacy concepts that should be considered in the context of cloud-based information systems and how these affect current research.

METRIC SELECTION FOR SOFTWARE DEFECT PREDICTION

2011 ◽  
Vol 21 (02) ◽  
pp. 237-257 ◽  
Author(s):  
HUANJING WANG ◽  
TAGHI M. KHOSHGOFTAAR ◽  
JASON VAN HULSE ◽  
KEHAN GAO
Keyword(s):  
Empirical Study ◽  
Prediction Models ◽  
Characteristic Curve ◽  
Life Cycles ◽  
Defect Prediction ◽  
Software Systems ◽  
Software Projects ◽  
Ensemble Technique ◽  
Defect Prediction Models ◽  
Software Practitioners

Real-world software systems are becoming larger, more complex, and much more unpredictable. Software systems face many risks in their life cycles. Software practitioners strive to improve software quality by constructing defect prediction models using metric (feature) selection techniques. Finding faulty components in a software system can lead to a more reliable final system and reduce development and maintenance costs. This paper presents an empirical study of six commonly used filter-based software metric rankers and our proposed ensemble technique using rank ordering of the features (mean or median), applied to three large software projects using five commonly used learners. The classification accuracy was evaluated in terms of the AUC (Area Under the ROC (Receiver Operating Characteristic) Curve) performance metric. Results demonstrate that the ensemble technique performed better overall than any individual ranker and also possessed better robustness. The empirical study also shows that variations among rankers, learners and software projects significantly impacted the classification outcomes, and that the ensemble method can smooth out performance.

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