Intent-Based Networking aims to automate network management by allowing users to express desired outcomes rather than manually configuring network resources. For its fulfilment, a user intent should be translated into...
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ISBN:
(纸本)9798350393767;9798350393774
Intent-Based Networking aims to automate network management by allowing users to express desired outcomes rather than manually configuring network resources. For its fulfilment, a user intent should be translated into machine-executable actions, which are then implemented in the infrastructure, and their outcome continuously monitored. However, such an automated loop may be hindered by conflicts that arise within an intent or between multiple intents throughout their lifecycle. In this work, we propose a Prolog-based declarative model and reasoning methodology to detect and resolve conflicts arising from new incoming intents. By leveraging and extending an open-source Prolog prototype designed for intent processing and translation into Virtual Network Function chains, we show its conflict detection and resolution capabilities through an illustrative application use case.
This paper describes our research into the expansion of the spreadsheet paradigm by the incorporation of solvers for systems of linear and finite-domain constraints. An extended spreadsheet system, called Intellisheet...
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ISBN:
(纸本)0780371984
This paper describes our research into the expansion of the spreadsheet paradigm by the incorporation of solvers for systems of linear and finite-domain constraints. An extended spreadsheet system, called Intellisheet, allows the entry of expressions that represent linear and finite-domain constraints, along with arithmetic expressions, in individual cells. The systems of constraints that have been entered are automatically solved by constraint solvers and the resulting solutions are displayed in the cells that contain the expressions or in other assigned cells. Intellisheet's GUI also has some special features to facilitate constraint programming. Incorporating constraint solvers extends the scope of the spreadsheet paradigm to declarative programming and provides an easier way to solve a broad class of problems, including linear optimization and discrete problems.
A process is a collection of steps, carried out using data, by either human or automated agents, to achieve a specific goal. The agents in our process are insiders;they have access to different data and annotations on...
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ISBN:
(纸本)9781479951031
A process is a collection of steps, carried out using data, by either human or automated agents, to achieve a specific goal. The agents in our process are insiders;they have access to different data and annotations on data moving in between the process steps. At various points in a process, they can carry out attacks on privacy and/or security of the process through their interactions with different data and annotations, via the steps which they control. These attacks are sometimes difficult to identify as the rogue steps are hidden among the majority of the usual non-malicious steps of the process. We define process models and attack models as dataflow-based directed graphs. An attack A is successful on a process P if there is a mapping relation from A to P that satisfies a number of conditions. These conditions encode the idea that an attack model needs to have a corresponding similarity match in the process model to be successful. We propose a declarative approach to vulnerability analysis. We encode the match conditions using a set of logic rules that define what a valid attack is. Then we implement an approach to generate all possible ways in which agents can carry out a valid attack A on a process P, thus informing the process modeler of vulnerabilities in P. The agents, in addition to acting by themselves, can also collude to carry out an attack. Once A is found to be successful against P, we automatically identify improvement opportunities in P and exploit them, eliminating ways in which A can be carried out against it. The identification uses information about which steps in P are most heavily attacked, and try to find improvement opportunities in them first, before moving onto the lesser attacked ones. We then evaluate the improved P to check if our improvement is successful. This cycle of process improvement and evaluation iterates until A is completely thwarted in all possible ways.
Researchers in the field of Mining Software Repositories perform studies about the evolution of software projects. To this end, they use the version control system storing the changes made to a single software project...
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ISBN:
(纸本)9781479919345
Researchers in the field of Mining Software Repositories perform studies about the evolution of software projects. To this end, they use the version control system storing the changes made to a single software project. Such studies are concerned with the source code characteristics in one particular revision, the commit data for that revision, how the code evolves over time and what concrete, fine-grained changes were applied to the source code between two revisions. Although tools exist to analyse an individual concern, scripts and manual work is required to combine these tools to perform a single experiment. We present a general-purpose history querying tool named QWALKEKO that enables expressing these concerns in a single uniform language, and having them detected in a git repository. We have validated our work by means of replication studies as well as through MSR studies of our own.
GUIs often contain structures that are incidental, not properly manipulatable through well-defined APIs. For example, modifying a list of items in a GUI's model may require extraneous bookkeeping operations in the...
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ISBN:
(纸本)9781450381741
GUIs often contain structures that are incidental, not properly manipulatable through well-defined APIs. For example, modifying a list of items in a GUI's model may require extraneous bookkeeping operations in the view, such as adding and removing event handlers, and updating the menu structure. Observing GUIs in practice gives an indication that programmers may find it difficult or tedious to implement complete and convenient sets of operations for manipulating various structures: useful operations for adding, inserting, swapping, or reordering elements are often missing, inconsistent, or limited. This paper introduces a DSL for programming operations that manipulate such incidental structures. The programmer specifies structures via relations between elements, concretely by defining methods that unestablish and establish a relation. This gives the programmer an ability to describe structural transformations via rules that control which relations should hold before and after a rule is applied. The API for structure manipulation is generated from these rules. Our DSL can give an abstract view on ad-hoc structures, making it easier to provide the necessary set of operations for their convenient manipulation.
作者：
Gondal, GZNUST
Inst Informat Technol New Lalazar Rawalpindi Pakistan
Technical Analysis is a financial risk management practice that has been in use since the advent of stock market and Pattern Recognition is an indivisible part of it. There has been a lot of research in to pattern rec...
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ISBN:
(纸本)0780382781
Technical Analysis is a financial risk management practice that has been in use since the advent of stock market and Pattern Recognition is an indivisible part of it. There has been a lot of research in to pattern recognition in time series. Existing pattern recognition techniques lacks dynamic extensibility. They do not provide any interfaces in order to include new patterns for recognition dynamically. This limits the operability of these techniques to a particular domain. This research devises a new technique for domain independent pattern recognition while giving sufficient speed and accuracy. This enables it to be used by critical Decision Support Systems for time series of different domains. The system emulates human visual cognition process by implementing the concept of Perceptually Important Points Identification (PIPI). Perceptually Important Points (PEP) represents minimal set of data points which are necessary to form a pattern. For dynamic inclusion of patterns a Pattern definition Language (PDL) has been conceptualized for defining patterns in time series by using declarative programming paradigm. This also results in domain independent pattern recognition without needing any modification.
In this paper we demonstrate several examples of solving challenging algorithmic problems from the Google Code Jam programming contest with the Prolog-based (ECLPSe)-P-i system using declarative techniques: constraint...
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ISBN:
(纸本)9781450331968
In this paper we demonstrate several examples of solving challenging algorithmic problems from the Google Code Jam programming contest with the Prolog-based (ECLPSe)-P-i system using declarative techniques: constraint logic programming and linear (integer) programming. These problems were designed to be solved by inventing clever algorithms and efficiently implementing them in a conventional imperative programming language, but we present relatively simple declarative programs in (ECLPSe)-P-i that are fast enough to find answers within the time limit imposed by the contest rules. We claim that declarative programming with (ECLPSe)-P-i is better suited for solving certain common kinds of programming problems offered in Google Code Jam than imperative programming. We show this by comparing the mental steps required to come up with both kinds of solutions.
declarative programming is a paradigm that allows programmers to specify what they want to compute, leaving how to compute it to a solver. Our declarative programming language, Dyna, is designed to compactly specify c...
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ISBN:
(纸本)9781450350716
declarative programming is a paradigm that allows programmers to specify what they want to compute, leaving how to compute it to a solver. Our declarative programming language, Dyna, is designed to compactly specify computations like those that are frequently encountered in machine learning. As a declarative language, Dyna's solver has a large space of (correct) strategies available to it. We describe a reinforcement learning framework for adaptively choosing among these strategies to maximize efficiency for a given workload. Adaptivity in execution is especially important for software that will run under a variety of workloads, where no fixed policy works well. We hope that reinforcement learning will identify good policies reasonably quickly-offloading the burden of writing efficient code from human programmers.
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