Patent application number | Description | Published |
20080222119 | Detecting a user's location, local intent and travel intent from search queries - A search query history for a user is analyzed to determine a home location of the user. Subsequent search queries are analyzed to discern whether the search query contains local intent, meaning that the search query requests information having an area of geographic relevance. In cases where a search query has local intent, the area of geographic relevance for that search query is compared to the home location of the user to determine whether the search query suggests an intent to travel. | 09-11-2008 |
20080250327 | Content commenting and monetization - A code is included in content, which code allows a user to use a comment tool to select some or all of the content, to create and submit comments, and to view previously submitted content selections and comments in conjunction with additional content. The additional content may comprise advertisements. | 10-09-2008 |
20080256561 | Web service platform for keyword technologies - The present web service platform includes a set of application program interfaces (APIs) and a framework for adding services that correspond to the APIs. The web service platform may also support a stored procedure (sproc) that allows combining results from two or more services before transmitting results to an application. The services relate to keyword technologies. | 10-16-2008 |
20080262909 | INTELLIGENT INFORMATION DISPLAY - Computer-readable media, systems, and methods for intelligent information display are described. In embodiments, a display environment is monitored for one or more audience data and, upon receiving the one or more audience data, display information is processed in accordance with the one or more audience data and the processed display information is presented. In various embodiments, the audience data includes user gestures that indicate a communication with the intelligent information display, such as gestures indicating a mouse motion or a mouse click. In various other embodiments, the audience data includes demographic indicia such as the typical gender and/or typical age of an audience in a display environment. | 10-23-2008 |
20080282290 | Interactive Viewer for Advertisements - A system, method, and computer-readable media are presented for displaying an interactive viewer associated with an advertisement within a user interface. In one aspect, the system includes an advertisement manager for providing advertisements in response to request from clients. The system further includes a rendering component for determining if an advertisement has an associated interactive viewer, determining features associated with the advertisement, and displaying the interactive viewer including the determined features. Additionally, the system includes an event tracking module for monitoring a user's interaction with the interactive viewer, and reporting feedback regarding the interaction to the advertisement manager. | 11-13-2008 |
20080320010 | SENSITIVE WEBPAGE CONTENT DETECTION - Computer-readable media, systems, and methods for sensitive webpage content detection are described. In embodiments, a multi-class classifier is developed and one or more webpages with webpage content are received. In various embodiments, the one or more webpages are analyzed with the multi-class classifier and, in various embodiments, a sensitivity level is predicted that is associated with the webpage content of the one or more webpages. In various other embodiments, the multi-class classifier includes one or more sensitivity categories. | 12-25-2008 |
20090070310 | ONLINE ADVERTISING RELEVANCE VERIFICATION - Online relevance verification is performed to provide relevant advertisements to search queries received at a search engine. Relevance of an advertisement for a received search query is determined by comparing the content of a landing page associated with the advertisement against search results for the search query. Relevance may then be used to filter irrelevant advertisements from consideration and/or may be used in ranking advertisements during an auction process in conjunction with monetization factors. Selected advertisements may then be returned in response to the search query. | 03-12-2009 |
20090248663 | ONLINE TARGET LOCATION DETECTION - Documents are provided that are geographically relevant to a user or a request. Information describing the online activity of a user is received and location identifiers are obtained. The plurality of location identifiers provide geographic location information defining the geographic intent of the information describing the online activity of the user, the location of the computing device utilized by the user, or the user's registered geographic location. Sets of predefined rules are then applied to the received information and the plurality of location identifiers to select at least one geographic location. Documents are then returned to the user that are geographically relevant based on the selected geographic location. The received information may include search queries, and the documents may include search results and/or advertisements. | 10-01-2009 |
20090249386 | FACILITATING ADVERTISEMENT PLACEMENT OVER VIDEO CONTENT - Systems, methods, computer-readable media, and graphical user interfaces for facilitating advertisement placement over video content are provided. Images within a video are partitioned into image regions. Upon partitioning images into image regions, an intrusiveness score is determined for each image region. Based on the intrusiveness scores, optimal placement of an advertisement within the video is determined. | 10-01-2009 |
20090327265 | RELEVANCE SCORE IN A PAID SEARCH ADVERTISEMENT SYSTEM - Described is a paid search advertising technology in which advertisements associated with bidding keywords are ranked by relevance when returning one or more advertisements in a response to a query. A relevance score is computed for an advertisement based on the bidding keyword and page data (text and/or other page content) of the advertisement. The relevance score may be based on a similarity vector score computed from a keyword vector and page data vector relationship, combined with a proximity score computed from the keyword's bigram set and the page data bigram set. When a query is received, advertisements are selected based on the proximity of the query to each advertisement's bidding keyword, providing candidate scores. Each candidate score is modified (e.g., multiplied) into a final score based on its respective advertisement's relevance score. The final scores are then used to re-rank the advertisements relative to one another. | 12-31-2009 |
20100057687 | PREDICTING FUTURE QUERIES FROM LOG DATA - A system, media, and method for selecting future queries are provided. The selected future queries are used to transmit appropriate online advertising to a user that issues queries to a search engine. The search engine is coupled to a prediction component that predicts what subject the user is going to be interested in and when the user will be interested in the subject. The prediction component returns a future query using statistical language models representing a query history of the user and aggregate query histories for a community of users. | 03-04-2010 |
20100250529 | ANTICIPATING INTERESTS OF AN ONLINE USER - Methods, systems, and computer-readable media for identifying intentions related to a user's present intention are provided. The user's present intention may be determined by mapping the user's current actions to a present intent. A related intent may be determined using an intent chain. The intent chain may be generated by analyzing patterns of user activities and mapping the patterns of activities to the underlying intents. | 09-30-2010 |
20110083013 | PRIVACY VAULT FOR MAINTAINING THE PRIVACY OF USER PROFILES - Methods, systems, and computer-readable media for facilitating personalization of web content is provided, while protecting the privacy of the user data utilized to personalize the user's experience. A privacy vault may collect user data including user activity data, demographic data, and user interests submitted by a user. In one embodiment, the privacy vault operates on a user client device. The privacy vault sends the user data to a community vault that collects user data from multiple users. The community vault generates segment rules that whether a user belongs to a user segment, which expresses a user's interest. The segment rules are then communicated back to the privacy vault, which assigns one or more user segments to the user based on the user data available to the privacy vault and the segment rules. The privacy vault may communicate user segments to one or more content providers that supply personalized content that is selected based on the user segments provided. | 04-07-2011 |
20110119255 | FACILITATING ADVERTISEMENT SELECTION USING ADVERTISABLE UNITS - Systems, methods, and computer storage media having computer-executable instructions embodied thereon that facilitate advertisement selection using advertising units. An entity that is a sequence of two or more words is referenced. The entity includes substrings comprising a portion of the entity. Search data in association with the entity is compared to corresponding search data in association with the substrings of the entity. Based on the comparison, it is determined that the entity comprises an advertisable unit that functions as a unit for purposes of selecting an advertisement for display. The advertisable unit is used to select an advertisement to be presented to the user. | 05-19-2011 |
20110238468 | PREDICTING FUTURE QUERIES FROM LOG DATA - A system, media, and method for selecting future queries are provided. The selected future queries are used to transmit appropriate online advertising to a user that issues queries to a search engine. The search engine is coupled to a prediction component that predicts what subject the user is going to be interested in and when the user will be interested in the subject. The prediction component returns a future query using statistical language models representing a query history of the user and aggregate query histories for a community of users. | 09-29-2011 |
20110295688 | DEFINING USER INTENT - Methods and computer-readable media are provided for defining user intent so that user intent can be determined and advertisements and other information can be provided to a user based on that user's intent. A topical expression is identified and is associated with attributes and actions. Actions indicate steps that can be performed to achieve a task associated with the topical expression. An intent structure is then generated. The intent structure illustrates a relationship between the identified topical expression and other topical expressions. User data may then be received and mapped to the intent structures to determine present and future user intent. | 12-01-2011 |
20110313857 | USER CENTRIC REAL-TIME ADVERTISEMENT BIDDING - A client-based ad agent dynamically determines whether an advertisement campaign should bid on an impression for an end user and/or sets the bid price of the advertisement campaign for the impression. When an opportunity for an impression on a web page is identified, the ad agent accesses user data associated with an end user. The ad agent analyzes the user data to identify the relevance and/or value of serving an impression to the end user to the advertisement campaign. Based on the analysis, the ad agent controls whether the advertisement campaign bids on the impression for the end user and/or sets the bid price of the advertisement campaign for the impression. | 12-22-2011 |
20120078715 | ADVERTISING SERVICE BASED ON CONTENT AND USER LOG MINING - A system and method are disclosed for providing documents related to a search request. The search request may include a search query of one or more keywords, or the search request may be a demographic search query including one or more demographic attributes. An index containing data crawled from publisher's websites, demographic information of registered users, along with the search history of the registered users can be created. Once a search request is received, the search request can be compared to the information stored in the index, and one or more documents related to the request can be provided. | 03-29-2012 |
20120095985 | PREDICTING FUTURE QUERIES FROM LOG DATA - A system, media, and method for selecting future queries are provided. The selected future queries are used to transmit appropriate online advertising to a user that issues queries to a search engine. The search engine is coupled to a prediction component that predicts what subject the user is going to be interested in and when the user will be interested in the subject. The prediction component returns a future query using statistical language models representing a query history of the user and aggregate query histories for a community of users. | 04-19-2012 |
20120197732 | ACTION-AWARE INTENT-BASED BEHAVIOR TARGETING - Methods and computer-storage media having computer-executable instructions embodied thereon that facilitate classifying user intent with respect to an entity using intent-strength scores. A user query indicating a particular entity is received. The user's intent with respect to the particular entity is determined by assigning an intent-strength score to the user. The user's intent-strength score is determined using intent-strength scores assigned to seed patterns identified for entities in a category, as well as the received user query. In embodiments, a user's intent-strength score may be updated based on a subsequent query, or may be changed according to a function. A list of users having particular intent-strength scores for particular entities may be also be generated. | 08-02-2012 |
20120253930 | USER INTENT STRENGTH AGGREGATING BY DECAY FACTOR - This application describes a system and method for estimating user intent towards categories of content. The estimation of user intent may be based at least in part on a score for prior user actions and a decay function that is applied to that score to provide an estimate of current user intent. The estimate represents current user intent for time periods in which user actions towards a category of content are negligible or non-existent. | 10-04-2012 |
20130067445 | Determination of Function Purity for Memoization - The purity of a function may be determined after examining the performance history of a function and analyzing the conditions under which the function behaves as pure. In some cases, a function may be classified as pure when any side effects are de minimis or are otherwise considered trivial. A control flow graph may also be traversed to identify conditions in which a side effect may occur as well as to classify the side effects as trivial or non-trivial. The function purity may be used to identify functions for memoization. In some embodiments, the purity analysis may be performed by a remote server and communicated to a client device, where the client device may memoize the function. | 03-14-2013 |
20130073523 | Purity Analysis Using White List/Black List Analysis - Memoizable functions may be identified by analyzing a function's side effects. The side effects may be evaluated using a white list, black list, or other definition. The side effects may also be classified into conditions which may or may not permit memoization. Side effects that may have de minimus or trivial effects may be ignored in some cases where the accuracy of a function may not be significantly affected when the function may be memoized. | 03-21-2013 |
20130073604 | Optimized Settings in a Configuration Database with Boundaries - A set of optimizations may be defined in a configuration database. The configuration database may be defined with a set of boundaries that may define conditions under which the optimizations may be valid. When the conditions are not met, a new configuration database may be requested from an optimization server. The system may be used to distribute and manage optimizations for an application, which may be deployed in interpreted or runtime scenarios or in pre-execution or compiled scenarios. | 03-21-2013 |
20130073829 | Memory Usage Configuration Based on Observations - A computer software execution system may have a configurable memory allocation and management system. A configuration file or other definition may be created by analyzing a running application and determining an optimized set of settings for the application on the fly. The settings may include memory allocated to individual processes, memory allocation and deallocation schemes, garbage collection policies, and other settings. The optimization analysis may be performed offline from the execution system. The execution environment may capture processes during creation, then allocate memory and configure memory management settings for each individual process. | 03-21-2013 |
20130073837 | Input Vector Analysis for Memoization Estimation - A function's purity may be estimated by comparing a new input vector to previously analyzed input vectors. When a new input vector is within a confidence boundary, the new input vector may be treated as a known vector, even when that vector has not been evaluated. The input vector may reflect the input parameters passed to a function, and the function may be analyzed to determine whether to memoize with the input vector. The function may be a function that behaves as a pure function in some circumstances and with some input vectors, but not with others. By memoizing the function when possible, the function may be executed much faster, thereby improving performance. | 03-21-2013 |
20130074049 | Memoization Configuration File Consumed at Runtime - Memoization may be deployed using a configuration file or database that identifies functions to memorize, and in some cases, includes input and result values for those functions. As an application is executed, functions defined in the configuration file may be captured and memoized. During the first execution of the function, the return value may be captured and stored in the configuration file. For subsequent executions of the function, the return value may be stored in the configuration file. In some cases, the configuration file may be distributed with the return values to client computers. The configuration file may be created by one device and deployed to other devices in some deployments. | 03-21-2013 |
20130074055 | Memoization Configuration File Consumed at Compile Time - Memoization may be deployed using a configuration file or database that identifies functions to memorize, and in some cases, includes input and result values for those functions. At compile time, functions defined in the configuration file may be captured and memoized. During compilation or other pre-execution analysis, the executable code may be modified or otherwise decorated to include memoization code. The memoization code may store results from a function during the first execution, then merely look up the results when the function may be called again. The memoized value may be stored in the configuration file or in another data store. In some embodiments, the modified executable code may operate in conjunction with an execution environment, where the execution environment may optionally perform the memoization. | 03-21-2013 |
20130074056 | Memoizing with Read Only Side Effects - A function may be memoized when a side effect is a read only side effect. Provided that the read only side effect does not mutate a memory object, the side effect may be considered as an input to a function for purity and memoization analysis. When a read only side effect may be encountered during memoization analysis, the read only side effect may be treated as an input to a function for memoization analysis. In some cases, such side effects may enable an impure function to behave as a pure function for the purposes of memoization. | 03-21-2013 |
20130074057 | Selecting Functions for Memoization Analysis - A function may be selected for memoization when the function indicates that memoization may result in a performance improvement. Impure functions may be identified and ranked based on operational data, which may include length of execution. A function may be selected from a ranked list and analyzed for memoization. The memoization analysis may include side effect analysis and consistency analysis. In some cases, the optimization process may perform optimization on one function at a time so as to not overburden a running system. | 03-21-2013 |
20130074058 | Memoization from Offline Analysis - Memoization may be deployed using a configuration file or database that identifies functions to memorize, and in some cases, includes input and result values for those functions. The configuration file or database may be created by profiling target code and offline or otherwise separate analysis of the profiling results. The configuration file may be used by an execution environment to identify which functions to memorize during execution. The offline or separate analysis of the profiling results may enable more sophisticated analysis than could otherwise be performed in parallel with executing the target code, including historical analysis of multiple instances of the target code and sophisticated cost/benefit analysis. | 03-21-2013 |
20130074092 | Optimized Memory Configuration Deployed on Executing Code - A configurable memory allocation and management system may generate a configuration file with memory settings that may be deployed at runtime. An execution environment may capture a memory allocation boundary, look up the boundary in a configuration file, and apply the settings when the settings are available. When the settings are not available, a default set of settings may be used. The execution environment may deploy the optimized settings without modifying the executing code. | 03-21-2013 |
20130074093 | Optimized Memory Configuration Deployed Prior to Execution - A configurable memory allocation and management system may generate a configuration file with memory settings that may be deployed prior to runtime. A compiler or other pre-execution system may detect a memory allocation boundary and decorate the code. During execution, the decorated code may be used to look up memory allocation and management settings from a database or to deploy optimized settings that may be embedded in the decorations. | 03-21-2013 |
20130080760 | Execution Environment with Feedback Loop - An execution environment may have a monitoring, analysis, and feedback loop that may configure and tune the execution environment for currently executing workloads. A monitoring or instrumentation system may collect operational and performance data from hardware and software components within the system. A modeling system may create an operational model of the execution environment, then may determine different sets of parameters for the execution environment. A feedback loop may change various operational characteristics of the execution environment. The monitoring, analysis, and feedback loop may optimize the performance of a computer system for various metrics, including throughput, performance, energy conservation, or other metrics based on the applications that are currently executing. The performance model of the execution environment may be persisted and applied to new applications to optimize the performance of applications that have not been executed on the system. | 03-28-2013 |
20130080761 | Experiment Manager for Manycore Systems - An execution environment may have a monitoring, analysis, and feedback loop that may configure and tune the execution environment for currently executing workloads. A monitoring or instrumentation system may collect operational and performance data from hardware and software components within the system. A modeling system may create an operational model of the execution environment, then may determine different sets of parameters for the execution environment. A feedback loop may change various operational characteristics of the execution environment. The monitoring, analysis, and feedback loop may optimize the performance of a computer system for various metrics, including throughput, performance, energy conservation, or other metrics based on the applications that are currently executing. The performance model of the execution environment may be persisted and applied to new applications to optimize the performance of applications that have not been executed on the system. | 03-28-2013 |
20130081005 | Memory Management Parameters Derived from System Modeling - Optimized memory management settings may be derived from a mathematical model of an execution environment. The settings may be optimized for each application or workload, and the settings may be implemented per application, per process, or with other granularity. The settings may be determined after an initial run of a workload, which may observe and characterize the execution. The workload may be executed a second time using the optimized settings. The settings may be stored as tags for the executable code, which may be in the form of a metadata file or as tags embedded in the source code, intermediate code, or executable code. The settings may change the performance of memory management operations in both interpreted and compiled environments. The memory management operations may include memory allocation, garbage collection, and other related functions. | 03-28-2013 |
20130085882 | Offline Optimization of Computer Software - An offline optimization for computer software may involve creating optimized parameters or components for a software product, and charging customers for the optimization service. The software product may be distributed under one licensing regime and the optimization components may be distributed under a second licensing regime. In some embodiments, a low cost or no-cost monitoring system may be provided, which may interface with a remote service that optimizes the software product for its current workload. A user may pay for the remote optimization service through a subscription, pay-per-use, pay-for-performance, or other payment models. | 04-04-2013 |
20130219057 | Relationships Derived from Trace Data - An analysis system may perform network analysis on data gathered from an executing application. The analysis system may identify relationships between code elements and use tracer data to quantify and classify various code elements. In some cases, the analysis system may operate with only data gathered while tracing an application, while other cases may combine static analysis data with tracing data. The network analysis may identify groups of related code elements through cluster analysis, as well as identify bottlenecks from one to many and many to one relationships. The analysis system may generate visualizations showing the interconnections or relationships within the executing code, along with highlighted elements that may be limiting performance. | 08-22-2013 |
20130219372 | Runtime Settings Derived from Relationships Identified in Tracer Data - An analysis system may perform network analysis on data gathered from an executing application. The analysis system may identify relationships between code elements and use tracer data to quantify and classify various code elements. In some cases, the analysis system may operate with only data gathered while tracing an application, while other cases may combine static analysis data with tracing data. The network analysis may identify groups of related code elements through cluster analysis, as well as identify bottlenecks from one to many and many to one relationships. The analysis system may generate visualizations showing the interconnections or relationships within the executing code, along with highlighted elements that may be limiting performance. | 08-22-2013 |
20130227529 | Runtime Memory Settings Derived from Trace Data - An analysis system may perform network analysis on data gathered from an executing application. The analysis system may identify relationships between code elements and use tracer data to quantify and classify various code elements. In some cases, the analysis system may operate with only data gathered while tracing an application, while other cases may combine static analysis data with tracing data. The network analysis may identify groups of related code elements through cluster analysis, as well as identify bottlenecks from one to many and many to one relationships. The analysis system may generate visualizations showing the interconnections or relationships within the executing code, along with highlighted elements that may be limiting performance. | 08-29-2013 |
20130227536 | Increasing Performance at Runtime from Trace Data - An analysis system may perform network analysis on data gathered from an executing application. The analysis system may identify relationships between code elements and use tracer data to quantify and classify various code elements. In some cases, the analysis system may operate with only data gathered while tracing an application, while other cases may combine static analysis data with tracing data. The network analysis may identify groups of related code elements through cluster analysis, as well as identify bottlenecks from one to many and many to one relationships. The analysis system may generate visualizations showing the interconnections or relationships within the executing code, along with highlighted elements that may be limiting performance. | 08-29-2013 |
20130239220 | Monitoring and Managing User Privacy Levels - Various embodiments pertain to techniques for measuring a user's privacy level as a user interacts with various web services. In various embodiments, entities with which the user interacts are detected and sensitive information shared by the user is logged to determine what a given entity knows about the user. In some embodiments, sensitive information that is shared by a user can be processed using a predictive algorithm to ascertain a user's level of privacy. When a user's identity is predicted by the algorithm, a user can be alerted to the loss of anonymity. In various embodiments, user-defined areas of anonymity can be used to measure a user's definition of privacy. In some embodiments, alerts can also be provided to the user when a new, previously undisclosed, piece of information is shared by the user. | 09-12-2013 |
20130283102 | Deployment of Profile Models with a Monitoring Agent - A distributed tracing system may use independent trace objectives for which a profile model may be created. The profile model may be deployed as a monitoring agent on non-instrumented devices to evaluate the profile models. As the profile models operate with statistically significant results, the sampling frequencies may be adjusted. The profile models may be deployed as a verification mechanism for testing models created in a more highly instrumented environment, and may gather performance related results that may not have been as accurate using the instrumented environment. In some cases, the profile models may be distributed over large numbers of devices to verify models based on data collected from a single or small number of instrumented devices. | 10-24-2013 |
20130283240 | Application Tracing by Distributed Objectives - A tracing system may divide trace objectives across multiple instances of an application, then deploy the objectives to be traced. The results of the various objectives may be aggregated into a detailed tracing representation of the application. The trace objectives may define specific functions, processes, memory objects, events, input parameters, or other subsets of tracing data that may be collected. The objectives may be deployed on separate instances of an application that may be running on different devices. In some cases, the objectives may be deployed at different time intervals. The trace objectives may be lightweight, relatively non-intrusive tracing workloads that, when results are aggregated, may provide a holistic view of an application's performance. | 10-24-2013 |
20130283241 | Periodicity Optimization in an Automated Tracing System - Periodicity similarity between two different tracer objectives may be used to identify additional input parameters to sample. The tracer objectives may be individual portions of a large tracer operation, and each of the tracer objectives may have separate set of input objects for which data may be collected. After collecting data for a tracer objective, other tracer objectives with similar periodicities may be identified. The input objects from the other tracer objectives may be added to a tracer objective and the tracer objective may be executed to determine a statistical significance of the newly added objective. An iterative process may traverse multiple input objects until exhausting possible input objects and a statistically significant set of input objects are identified. | 10-24-2013 |
20130283246 | Cost Analysis for Selecting Trace Objectives - A tracing system may perform cost analysis to identify burdensome or costly trace objectives. For a burdensome objective, two or more objectives may be created that can be executed independently. The cost analysis may include processing, storage, and network performance factors, which may be budgeted to collect data without undue performance or financial drains on the application under test. A larger objective may be recursively analyzed to break the larger objective into smaller objectives which may be independently deployed. | 10-24-2013 |
20130283247 | Optimization Analysis Using Similar Frequencies - Tracer objectives in a distributed tracing system may be compared to identify input parameters that may have a high statistical relevancy. An iterative process may traverse multiple input objects by comparing results of multiple tracer objectives and scoring possible input objects as being possibly statistically relevant. With each iteration, statistically irrelevant input objects may be discarded from a tracer objective and other potentially relevant objects may be added. The iterative process may converge on a set of statistically relevant input objects for a given measured value without a priori knowledge of an application being traced. | 10-24-2013 |
20130283281 | Deploying Trace Objectives using Cost Analyses - A tracing management system may use cost analyses and performance budgets to dispatch tracing objectives to instrumented systems that may collect trace data while running an application. The tracing management system may analyze individual tracing workloads for processing, storage, and network performance costs, and select workloads to deploy based on a resource budget that may be set for a particular device. In some cases, complementary tracing objectives may be selected that maximize consumption of resources within an allocated budget. The budgets may allocate certain resources for tracing, which may be a mechanism to limit any adverse effects from tracing when running an application. | 10-24-2013 |
20150082285 | RUNTIME SETTINGS DERIVED FROM RELATIONSHIPS IDENTIFIED IN TRACER DATA - An analysis system may perform network analysis on data gathered from an executing application. The analysis system may identify relationships between code elements and use tracer data to quantify and classify various code elements. In some cases, the analysis system may operate with only data gathered while tracing an application, while other cases may combine static analysis data with tracing data. The network analysis may identify groups of related code elements through cluster analysis, as well as identify bottlenecks from one to many and many to one relationships. The analysis system may generate visualizations showing the interconnections or relationships within the executing code, along with highlighted elements that may be limiting performance. | 03-19-2015 |