354 results about "Dependency graph" patented technology

Configuring a node. A method includes determining a current state of a target node. The current state of the target node refers to objects currently deployed or running in the remote target node. It includes at least one of an operating system, one or more applications, or configuration setting at the target node. The method further includes determining a desired state for the target node to change the current state. The method further includes accessing a dependency graph based on the version of an agent running on the target node. The dependency graph is supplied to a state machine. The state machine is particular to the target node. The state machine using the current state of the target node, the desired state and the dependency graph, performs operations to drive the target node toward its goal.

A system, method and database development tool are disclosed for automatically generating the complete dependency graph for use in debugging stored code objects in a database, by using a recursive dependency tracking algorithm which takes into consideration the indirect dependencies on triggers as well as the dependencies on implementations of object oriented code objects which are represented as separate objects in the database catalog.

The system for end-to-end content publishing using XML with an object dependency graph is based on the following two design principles: First, separation of content and style: Information stored in the content management system is independent on how it is going to be presented. The presentation style is encapsulated elsewhere and can be used to customize the look and feel based on the end-user preferences as well as the delivery methods and devices. Second, reusability of information content: By encapsulating common information in fragments and subfragments and making these fragments insertable in other fragments, thereby avoid scattering and duplication of information. This enables a user to restrict the edit operations to a limited number of relevant fragments, to affect global changes. In addition, the present invention provides data consistency and data integrity in the content management.

Embodiments of a system and method for providing class dependency graph-based class loading and reloading may be used to segregate namespaces in a graph-centric way, and may provide a set of normalized topologies that may be used to efficiently support hot-swapping of programmatic logic such as classes, applets, and beans, among other applications. Embodiments may provide a domain-independent, flexible and robust namespace segregation technique that is based on the dependency between the various classes and not on details like the roles the classes play. The problem of segregating namespaces is formulated as a graph theory problem, and a solution is sought through graph techniques. The graph may be normalized by identifying and grouping interdependent classes and non-interdependent classes in separate groups. A directed dependency relationship of the groups may be determined using the relationships between the member classes of the groups.

Disclosed is a network hardening mechanism. The mechanism: generates a dependency graph from a multitude of exploits; constructs a goal conditions expression which may then be used to determine set(s) of safe network configurations. A subset of these safe network configuration sets may then be selected for implementation using hardening costs as a criterion.

A system and a priori method of discovering dependencies between relational database column pairs and application of discoveries to query optimization is provided. For each candidate column pair remaining after simultaneously generating column pairs, pruning pairs not satisfying specified heuristic constraints, and eliminating pairs with trivial instances of correlation, a random sample of data values is collected. A candidate column pair is tested for the existence of a soft functional dependency (FD), and if a dependency is not found, statistically tested for correlation using a robust chi-squared statistic. Column pairs for which either a soft FD or a statistical correlation exists are prioritized for recommendation to a query optimizer, based on any of: strength of dependency, degree of correlation, or adjustment factor; statistics for recommended columns pairs are tracked to improve selectivity estimates. Additionally, a dependency graph representing correlations and dependencies as edges and column pairs as nodes is provided.

The inference of a dependency graph that represents a graph of solves that leads from input model parameter(s) to output model parameters using analytics. In one embodiment, the dependency graph is part of visually driven analytics in which the output model parameter(s) are used to formulate data-drive scenes. As the identity of the input and / or output model parameter(s) change, or as the analytics themselves change, the dependency graph may also change. This might trigger a resolve of the analytics. In one embodiment, the intermediate parameters involved in the dependency graph may be viewed and evaluated by the user.

Improved scheduling of instructions within a loop for execution by a computer system having hardware lookahead is provided. A dependence graph is constructed which contains all the nodes of a dependence graph corresponding to the loop, but which only contains loop-independent dependence edges. A start node simulating a previous iteration of the loop may be added to the dependence graph, and an end node simulating a next iteration of the loop may also added to the dependence graph. A loop-independent edge between a source node and the start node is added to the dependence graph, and a loop-independent edge between a sink node and the end node is added to the dependence graph. Loop-carried edges which satisfy a computed lower bound on the time required for a single loop iteration are eliminated from a dependence graph, and loop-carried edges which do not satisfy the computed lower bound are replaced by a pair of loop-independent edges. Instructions may be scheduled for execution based on the dependence graph.

A dependency analysis unit creates a dependency graph showing dependencies between instructions acquired from an assembler code generation unit. A precedence constraint rank calculation unit assigns predetermined weights to arcs in the graph, and adds up weights to calculate a precedence constraint rank of each instruction. When a predecessor and a successor having a dependency and an equal precedence constraint rank cannot be processed in parallel due to a resource constraint, a resource constraint evaluation unit raises the precedence constraint rank of the predecessor. A priority calculation unit sets the raised precedence constraint rank as a priority of the predecessor. An instruction selection unit selects an instruction having a highest priority. An execution timing decision unit places the selected instruction in a clock cycle. The selection by the instruction selection unit and the placement by the execution timing decision unit are repeated until all instructions are placed in clock cycles.

A problem determination system and method reduces the time and effort required by system administrators to trouble shot transaction processing difficulties in a large distributed I / T environment by monitoring system component performance and computing operational performance threshold limits based on dependency graphs for the system. Using this data, a prioritized list of suspect components for the I / T system is generated.

A dependency graph includes nodes representing states of infrastructure elements in a managed system, and impacts and events among the infrastructure elements in a managed system that are related to delivery of a service by the managed system. Events are received that cause change among the states in the dependency graph. An event occurs in relation to one of the infrastructure elements of the dependency graph. Each individual node that was affected by the event is analyzed and ranked based on (i) states of the nodes which impact the individual node, and (ii) the states of the nodes which are impacted by the individual node, to provide a score for event(s) which is associated with the individual node. Plural events are ranked based on the scores. The root cause of the events with respect to the service is provided based on the events which were ranked.

Machine data is collected from multiple sources of an operating environment such as an information technology system, factory floor, or the like, into a data intake and query system, in one embodiment. Metrics representative of the environment are included in or derived from the data. Users may interact with an interface to depict a representation of various metrics and interdependencies and that depiction is reflected in a computer storage model. Changes to the computer storage model based on the user interaction may also result in training of a machine learning model according to the user interaction, the machine learning model configured to determine a prediction, classification or clustering of a result of a first search query by utilizing a result of at least a second search query as input to the machine learning model.

Machine data is collected from multiple sources of an operating environment such as an information technology system, factory floor, or the like, into a data intake and query system, in one embodiment. Metrics representative of the environment are included in or derived from the data. Users may interact with an interface to depict a representation of various metrics and interdependencies and that depiction is reflected in a computer storage model. Changes to the computer storage model based on the user interaction may also result in automatic changes to control information reflected in the computer storage model that directs the processing of various monitoring functions associated with the metrics.

The invention provides a system and a method for arranging cloud resources. The system comprises a cloud resource pool, an input module, an arranging engine and a resource state machine, wherein the cloud resource pool is used for providing the resources needing to arrange, and the resources are organized as different resource pools by using pooling method and are stored in a classified manner; the input module is used for inputting relative parameters according to an arranging template, wherein the arranging template is established in advance according to different business requirements; the arranging engine is used for analyzing the relative parameters, obtaining a dependency graph of the resources and processing the resources in a multi-path manner according to the dependency graph; the resource state machine is used for maintaining the state of the resources. The system and the method of the invention are used for dynamically deploying the resources according to a requirement type and a degree of an application to the resources to achieve optimal combination of the application and the resources. Simultaneously, the method and the system of the invention improve operation and maintenance efficiency of a data centre and reduce cost and management complexity.

Methods and systems for optimizing a build order of component source modules comprises creating a dependency graph based on dependency information. Historical build information associated with previous build failures is then used to calculate relative failure factors for paths of the dependency graph; and the relative failure factors are used to determine an order of traversal of the dependency graph during a build process in which component binary modules are built from the component source modules.

A system and method of discovering dependencies between relational database column pairs and application of discoveries to query optimization is provided. For each candidate column pair remaining after simultaneously generating column pairs, pruning pairs not satisfying specified heuristic constraints, and eliminating pairs with trivial instances of correlation, a random sample of data values is collected. A candidate column pair is tested for the existence of a soft functional dependency (FD), and if a dependency is not found, statistically tested for correlation using a robust chi-squared statistic. Column pairs for which either a soft FD or a statistical correlation exists are prioritized for recommendation to a query optimizer, based on any of: strength of dependency, degree of correlation, or adjustment factor; statistics for recommended columns pairs are tracked to improve selectivity estimates. Additionally, a dependency graph representing correlations and dependencies as edges and column pairs as nodes is provided.

Methods and systems for intrusion attack recovery include monitoring two or more hosts in a network to generate audit logs of system events. One or more dependency graphs (DGraphs) is generated based on the audit logs. A relevancy score for each edge of the DGraphs is determined. Irrelevant events from the DGraphs are pruned to generate a condensed backtracking graph. An origin is located by backtracking from an attack detection point in the condensed backtracking graph.

A method for aspect categorization includes receiving an input text sequence and identifying aspect terms and sentiment phrases in the input text sequence, where present. For an identified aspect term, identifying sentiment dependencies in which the aspect term is in a syntactic dependency with one of the identified sentiment phrases, and identifying pseudo-dependencies from a dependency graph of the input text sequence. The dependency graph includes a sequence of nodes. In a pseudo-dependency, a node representing the aspect term precedes or follows a node representing a semantic anchor in the dependency graph without an intervening other aspect term. Features for the aspect term are extracted from at least one of identified sentiment dependencies and identified pseudo-dependencies. With a classifier trained to output at least one of category labels and polarity labels for aspect terms, classifying the identified aspect term based on the extracted features.

A method for generating a natural language response to a customer inquiry includes parsing sentences in a corpus of natural language dialogs between a respective customer and an agent to extract dependencies. Each parsed sentence is represented by a dependency graph, based on the extracted dependencies. Dependency templates are generated, at least some of which are each generated from two or more of the extracted dependency graphs (e.g., using variables which each represent a group of words referring to a same topic) and are stored in a knowledge base. In response to the customer inquiry, one of the stored dependency templates is identified and a natural language response to the inquiry is generated, using the identified dependency template. The natural language response is generated based on words extracted from the natural language dialogs that are linked, in memory, to the identified dependency template.

Typed dependency graphs represent digital assets as nodes in a graph. The digital assets, data files, and required software applications are represented as connected nodes. Nodes of the graph are connected by typed links, specifying the type of dependency relationship between digital assets, data files, and / or software applications associated with nodes. Type attributes can represent one-way dependencies, two-way dependencies, version relationships, variant relationships, subcomponent relationships, aggregation relationships, and software application / digital asset dependencies. Typed dependency graphs may be automatically created by parsing asset data or data files to determine the characteristics of assets and their relationships with other assets, data files, and software applications. Typed dependency graphs may be traversed based on the type of links, with the result defining a component, subcomponent, version, and / or variant.

A problem determination system and method reduces the time and effort required by system administrators to trouble shot transaction processing difficulties in a large distributed I / T environment by monitoring system component performance and computing operational performance threshold limits based on dependency graphs for the system. Using this data, a prioritized list of suspect components for the I / T system is generated.

The invention discloses a pipeline parallelization method for coarse-grained streaming applications. The pipeline parallelization method includes performing classic data profiling and dependency analysis on serial C-codes to acquire a task dependence graph, performing dependence transformation on the task dependence graph to acquire a directed acyclic graph, building a system feature graph, performing task scheduling on the directed acyclic graph according to the system feature graph and judging whether a task scheduling result meets performance requirements or not, if not, then aggregating and splitting task of the directed acyclic graph to acquire a new directed acyclic graph, selecting and calculating the highest-cost task of the new directed acyclic graph to acquire a new calculated hot spot region, returning to performing the dependency analysis again, segmenting and modifying the serial C-codes according to the task scheduling result so as to obtain parallelized C-codes, encoding to generate parallel executable files through an encoder, and loading the parallel executable files to a target hardware platform to execute. The pipeline parallelization method is adaptable to multilayer nested loop structures and capable of extracting parallelism of the multilayer loop.

The present invention describes a method of efficiently optimizing instruction scheduling and register allocation in a post optimizer. The method removes false register dependencies between pipelined instructions by building an incremental (partial) interference graph of register allocation for scheduled instructions. False dependency graph indicates the amount of parallelism in the data flow graph. The incremental interference graph uses a mix of virtual and physical registers. The interference graph is built incrementally as an instruction schedular schedules each instruction. The optimization is done incrementally on localized code. The physical register mapping is maximized and virtual registers are created on demand basis.

Transactional memory implementations may be extended to include special transaction communicator objects through which concurrent transactions can communicate. Changes by a first transaction to a communicator may be visible to concurrent transactions before the first transaction commits. Although isolation of transactions may be compromised by such communication, the effects of this compromise may be limited by tracking dependencies among transactions, and preventing any transaction from committing unless every transaction whose changes it has observed also commits. For example, mutually dependent or cyclically dependent transactions may commit or abort together. Transactions that do not communicate with each other may remain isolated. The system may provide a communicator-isolating transaction that ensures isolation even for accesses to communicators, which may be implemented using nesting transactions. True (e.g., read-after-write) dependencies, ordering (e.g., write-after-write) dependencies, and / or anti-dependencies (e.g., write-after-read dependencies) may be tracked, and a resulting dependency graph may be perused by the commit protocol.

A method, apparatus, system, and article of manufacture provide the ability to track the processing of image data in a collaborative environment. A dependency graph that represents an image composition is obtained. Metadata for each element of the dependency graph are stored in a database that is accessible across a network to multiple users. Access to the database is controlled to allow the multiple users to access the dependency graph via the database simultaneously.

The invention discloses a method for detecting redundant code defects based on static analysis, for solving the problem lacking of a mature method for detecting redundant codes and related defects currently. The method comprises the following steps of: 1, inputting a program to be tested; analyzing the program into an abstract syntax tree; 2, analyzing statements possibly including operations of explicit power and the like; detecting the operations of the explicit power and the like; 3, for locally defined variables, detecting redundant assignment statements by using an internal process analysis method; 4, traversing the abstract syntax tree of the program; searching structures including the defects on the basis of a standardized program dependency graph; detecting dead codes; 5, detecting redundant conditional expressions; 6, detecting operations of implicit power and the like; and 7, detecting redundant function parameters; and giving a defect detection report according to the six defect detection results obtained in the steps 2-7. The method disclosed by the invention is applicable for analyzing large-scale program codes.