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The ComFoRT Reasoning Framework
[chapter]
<span title="">2005</span>
<i title="Springer Berlin Heidelberg">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a>
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Another is the use of a simpler language for expressing verification properties, such as a pattern language [11] . ...
A third is a technique for confirming that design-level (i.e., CCL designs) verification results are satisfied by eventual component implementations by proving a conformance relation between the model ...
It provides a model checker, Copper, that implements a suite of complementary complexity management techniques to address state space explosion. But ComFoRT is more than a model checker. ...
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The Application of Machine Learning in Self-Adaptive Systems: A Systematic Literature Review
<span title="">2020</span>
<i title="Institute of Electrical and Electronics Engineers (IEEE)">
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machine learning technique can be used in a software system to make them adaptive and self-configuring. ...
Machine learning is typically used to discover software patterns and to detect software defects. Furthermore, the increasing complexity of software systems also contributes to the trend. ...
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Software reliability models based on machine learning techniques: A review
<span title="">2022</span>
<i title="AIP Publishing">
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This paper examines emerging literature focused on machine learning approaches of software reliability models. ...
using machine learning methods. ...
learning is an approach designed and designed to enable computers to model system behavior using information systems statistical data. ...
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Automata-Based Software Reliability Model: The Key to Reliable Software
<span title="2013-11-30">2013</span>
<i title="Science and Engineering Research Support Society">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kx4szfp7xvfn7laozkx3mc4iqe" style="color: black;">International Journal of Software Engineering and Its Applications</a>
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Section 3 introduces the formal finite state machine model and discusses its applications in software systems. ...
Section 5 traces the different extensions and applications of finite state machine (FSM) models in designing and testing reliable software systems. ...
The state-space approach is better said a generative approach that can allow modeling of dynamic, complex systems [23] . ...
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Towards Better Adaptive Systems by Combining MAPE, Control Theory, and Machine Learning
[article]
<span title="2021-03-19">2021</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
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Recently, we also observe a rapidly growing interest in applying machine learning (ML) to support different adaptation mechanisms. ...
Two established approaches to engineer adaptive systems are architecture-based adaptation that uses a Monitor-Analysis-Planning-Executing (MAPE) loop that reasons over architectural models (aka Knowledge ...
Monitoring is used to update these models with data about the current state of the software, the environment in which it is running, and the goals of the software. ...
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Conventional Usage of Finite State Machine over Petri Net inWeb Service Change Management Framework
<span title="">2013</span>
<i title="Elsevier BV">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zy6wu5tesbbynfuiadfw6zh6fu" style="color: black;">Information Engineering Research Institute procedia</a>
</i>
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Finite state in analyzin modeling a existing ch change eva when a cha managemen exacting the the represen managemen © 2013 Pu Selection ...
From the evaluation of the objective factors, it is inferred that finite state machine suits well than petri nets for the change management model, as emergency changes need to handled in an efficient way ...
process control and Simulation, finite state machine plays an efficient role in representing the evaluation of change implemented. ...
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FAULT TOLERATING MECHANISM IN DISTRIBUTED COMPUTING ENVIRONMENT
<span title="2020-08-01">2020</span>
<i title="IJEAST">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/namhphsg6rdvtofp27o3scimoy" style="color: black;">International Journal of Engineering Applied Sciences and Technology</a>
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Under machine learning, an artificial neural network (ANN) captures, manipulates, and updates the states and behaviors of the sub-systems in the servers and worker's machines. ...
To speed up computation in such a situation a fault tolerating infrastructure is implemented by adopting a machine learning approach. ...
The machine learning model can manage such kind of problem easily and appropriately. ...
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Toward Energy-Aware Scheduling Using Machine Learning
[chapter]
<span title="2012-07-30">2012</span>
<i title="John Wiley & Sons, Inc.">
Energy-Efficient Distributed Computing Systems
</i>
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Machine learning techniques supply a new vision of the modeling process, letting us to find these system models without the explicit requirement of experts and the ability of being able to update the model ...
To solve these problems, one very relevant solution is machine learning, which allows the creation of decision and classification models of very complex systems from the examples of the same system, in ...
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Approximate and Probabilistic Computing: Design, Coding, Verification (Dagstuhl Seminar 15491)
<span title="2016-04-06">2016</span>
<i title="Schloss Dagstuhl Leibniz-Zentrum für Informatik GmbH">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/u2phfyhrhje7xnnubtp3vfklcu" style="color: black;">Dagstuhl Reports</a>
</i>
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The aim of this seminar was to bring together academic and industrial researchers from the areas of probabilistic model checking, quantitative software analysis, probabilistic programming, and approximate ...
These complex systems require sophisticated algorithms to deliver accurate answers quickly, at scale, and with energy efficiency, and approximation is often the only way to meet these competing goals. ...
Smoothed Model Checking: A Machine Learning Approach to Probabilistic Model Checking under Uncertainty
Dimitrios Milios (University of Edinburgh, GB)
License Creative Commons BY 3.0 Unported license ...
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Lessons Learned from Model Checking a NASA Robot Controller
<span title="">2004</span>
<i title="Springer Nature">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fyhr5xuigbfmdabfoqp2f7lbum" style="color: black;">Formal methods in system design</a>
</i>
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This paper reports as a case study an attempt to model check the control subsystem of an operational NASA robotics system. ...
Several significant flaws in the original software system were identified and corrected during the model checking process. The case study presents the entire process in a semi-historical mode. ...
But application of model checking to software systems is still in an early stage of development. ...
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Use of Genetic Algorithm in Network Security
<span title="2012-09-25">2012</span>
<i title="Foundation of Computer Science">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/b637noqf3vhmhjevdfk3h5pdsu" style="color: black;">International Journal of Computer Applications</a>
</i>
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A client server environment is made use of. General Terms Genetic algorithm, Network security, Crossover technique. ...
A motivation was experienced for the need of a strong network security policy framework. In this paper a strong network model for security function is presented. ...
Total
no
of
networking
parameter checked in previous
system
Efficiency of System =
* 100
Total no of networking
parameter
checked in our
system
8
Efficiency of System =
* 100
11
Efficiency ...
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<a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5120/8438-2221">doi:10.5120/8438-2221</a>
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Quality-aware Approach for Engineering Self-adaptive Software Systems
[article]
<span title="2014-02-11">2014</span>
<i >
arXiv
</i>
<span class="release-stage" >pre-print</span>
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<span title="2014-01-02">2014</span>
<i >
Computer Science & Information Technology ( CS & IT )
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<span class="release-stage">unpublished</span>
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5121/csit.2014.4117">doi:10.5121/csit.2014.4117</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/u5pe2jaq7jex3p5xmsxmyehtem">fatcat:u5pe2jaq7jex3p5xmsxmyehtem</a> </span>
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In this paper, an approach for building an external adaptation engine for self-adaptive software systems is proposed. ...
In order to improve the quality of self-adaptive software systems, this research addresses two challenges in self-adaptive software systems. ...
Developing a self-adaptive software system is subjected to many challenges like handling the complexity of the adaptation space of the managed system. ...
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Learning-Based Run-Time Power and Energy Management of Multi/Many-Core Systems: Current and Future Trends
<span title="2017-09-01">2017</span>
<i title="American Scientific Publishers">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vz36d3qaezfb7enlkagvfzo7me" style="color: black;">Journal of Low Power Electronics</a>
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This article provides an extensive survey of learning-based run-time power/energy management approaches. The survey includes a taxonomy of the learning-based approaches. ...
However, effective power/energy management is required during system operations due to several reasons such as to increase the operational time of battery operated systems, reduce the energy cost of datacenters ...
Experimental data used in this paper can be found at DOI: http://doi.org/10.5258/SOTON/D0109. ...
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Using Data Mining Technique For Scholarship Disbursement
<span title="2015-08-05">2015</span>
<i title="Zenodo">
Zenodo
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Tree-based data mining classification technique is used in other to determine the generic rule to be used to disburse the scholarship. ...
The tree-based classification is adopted because of its efficiency, effectiveness, and easy to comprehend features. ...
Machine Learning domain ANN approaches is measured to be a baseline technique for data-driven modeling. The higher Machine Learning techniques comprise of Support Vector Machines. ...
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Formal Verification of Evolutionary Changes
[chapter]
<span title="">2019</span>
<i title="Springer International Publishing">
Managed Software Evolution
</i>
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In this chapter, we elaborate how formal verification techniques can be used to ensure safety properties of automated production systems during their evolution. ...
, generalised test tables, and model checking of holistic (multidomain) models. ...
Furthermore, old revisions allow obtaining precise models of the system efficiently using observations and model learning techniques. ...
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