Abstract: Example embodiments disclosed herein relate to determining whether a protective measure meeting criteria has been performed on data. Execution of an application under test (AUT) is monitored. A message that a field of the AUT should be considered sensitive is received. Data is determined to be entered into the field. The data is monitored during execution of the AUT to determine whether the protective measure that meets the criteria has been performed on the data.

Abstract: Relationship extraction can include applying unsupervised relationship learning to a logic knowledge base and a plurality of entity groups recognized from a document to provide a probabilistic model. Relationship extraction can include performing joint inference on the probabilistic model to make simultaneous statistical judgments about a respective relationship between at least two entities in one of the plurality of entity groups. Relationship extraction can include extracting a relationship between at least two entities in one of the plurality of entity groups based on the joint inference.

Abstract: In one example of the disclosure, an expected measurement range is identified for each of a set of metrics. Actual value measurements are obtained for each of the metrics. Each of the identified expected measurement ranges and the actual value measurements are normalized according to a common scale. A graph is caused to be displayed. The graph includes a baseline band representative of the normalized measurement ranges, and includes the normalized actual value measurements plotted relative to the baseline band.

Abstract: A technique includes receiving a plurality of metrics for a plurality of tasks associated with developing an application, where each of the metrics is associated with one of the tasks and indicates a progress of the associated task. The technique includes receiving weights, where each weight is associated with one of the tasks and indicates a user assigned importance of the associated task. The technique includes displaying with the tool an indicator to allow regulation of task development, where the displaying includes causing the tool to prioritize the tasks for future development of the application based at least in part on the metrics and the weights.

Abstract: Performance testing based on variable length segmentation and clustering of time series data is disclosed. One example is a system including a training module, a performance testing module, and an interface module. The training module generates a trained model to learn characteristics of a system of interest from training time series data by segmenting the training time series data into homogeneous windows of variable length, clustering the segments to identify patterns, and associating each cluster with a cluster score. The performance testing module analyzes system characteristics from testing time series data by receiving the testing time series data, and determining a performance metric for the testing time series data by analyzing the testing time series data based on the trained model. The interface module is communicatively linked to the performance testing module, and provides the performance metric via an interactive graphical user interface.

Abstract: According to examples, a system and method may identify differences in scripts for testing applications. Particularly, a processor may receive results of a replay of multiple scripts. Each script of the multiple scripts may include information relating to activities between at least one client device and at least one server device over a network. The results may be compared, and based on the comparison, a difference between the scripts may be identified.

Abstract: In some examples, a plurality of multi-dimensional data samples representing respective behaviors of entities in a computing environment are sorted, where the sorting is based on values of dimensions of each respective multi-dimensional data sample. For a given multi-dimensional data sample, a subset of the plurality of multi-dimensional data samples is selected based on the sorting. An anomaly indication is computed for the given multi-dimensional data sample based on applying a function on the multi-dimensional data samples in the subset. It is determined whether the given multi-dimensional data sample represents an anomalous entity in the computing environment based on the computed anomaly indication.

Abstract: In one example in accordance with the present disclosure, a method may include receiving an initial document object model (DOM) corresponding to an HTML page structure including a plurality of executable JavaScript code and simulating user interaction with an executable JavaScript code belonging to the plurality in the HTML page structure. The method may include adjusting the initial DOM based on the simulated user interaction, generating byte code corresponding to the adjust DOM and analyzing the byte code using a set of static rules.

Abstract: Distances between geographic real-world entities modeled as geometric shapes are measured. At least two shapes are positioned in a coordinate space based on their respective sets of points. A non-empty quadrant set from a plurality of non-empty quadrant sets formed of non-empty quadrants in the coordinate space is identified such that the non-empty quadrants of the identified quadrant set associated with each of the at least two shapes satisfy a predetermined condition and a distance between portions of the at least two shapes in the non-empty quadrants of the identified non-empty quadrant set is an optimal value for the requested distance. The distance between the portions of the shapes in the identified quadrant set is determined to be the requested distance.

Abstract: In some examples, with respect to zone based key version encoding, data that is to be encrypted may be ascertained, and a key, including a key version, that is to be used to encrypt the ascertained data may be ascertained. Encrypted data may be generated by encrypting the ascertained data based on the ascertained key, and a zone representing the key version may be determined. Further, encrypted zoned data may be generated by applying the determined zone to the encrypted data to encode the key version, and the encrypted zoned data including the encoded key version may be stored.

Abstract: A synchronous operation method receives a call request from program code executing on an execution engine. The program code has an associated event loop handling asynchronous event calls and callbacks within the program code. Handlers of the event loop associated with the asynchronous event calls and the callbacks within the program code, except a handler of the event loop associated with the synchronous operation method, are temporarily disabled. The synchronous operation method performs an operation specified within the call request, while the event loop is running with the handlers in question temporarily disabled. The synchronous operation method, upon completion, calls back its handler with results of performance of the operation, and the disabled handlers are reenabled.

Abstract: Examples disclosed herein provide notifications to a user of a communications device. The communications device groups electronic communications received from different communications services according to senders of the electronic communications. The communications device sorts a list of one or more of the senders according to the electronic communications received. The communications device displays the sorted list via a graphical user interface of the communications device. For each sender on the list, the communications device displays an indication of a number of electronic communications received from the sender.

Abstract: A technique for visualizing topics includes depicting topic bubbles including pixels. In one example, selected topics are identified from records based on scoring candidate terms in the records according to a user-specified metric and a metric selected from among frequencies of occurrence of records pertaining to the respective candidate terms, and negativity of sentiment expressed with respect to the candidate terms in the records. A visualization is generated including bubbles representing topics, the bubbles including pixels representing corresponding records. A bubble has a shape dependent upon a number of records and a time interval represented by the bubble. Visual indicators are assigned to the pixels in a given bubble according to values of an attribute expressed in the corresponding records for the topic represented by the given bubble, resulting in the analysis of the selected topics being less time consuming and labor intensive.

Abstract: In one example in accordance with tie present disclosure, a method for security vulnerability detection includes indexing a variety of internet sources comprising third party submitted information, to extract security vulnerabilities based on the third party submitted information. The method includes generating a security vulnerabilities list comprising security vulnerabilities from the internet source and generating a software components list comprising a software component used in an application. The method includes determining that a security vulnerability in the security vulnerabilities list affects the software component and determining a risk score of the security vulnerability. The method includes presenting the security vulnerability, the risk score and the software component via a user interface.

Abstract: Examples relate to accessing resources across multiple tenants. One example enables determination, from a list of requests, a request to perform which accesses a resource, responsive to a determination that the resource on a server is available for use for an application. The request to be performed may be determined, for example, by determining a first priority score for a first tenant associated with a first request based on usage of the resource by the first tenant, wherein the first tenant comprises a first set of users, determining a second priority score for a tenant associated with a second request based on usage of the resource by the second tenant, wherein the second tenant comprises a second set of users, and, responsive to the first priority score being lower than the second priority score, selecting the first request as the request to be performed.

Abstract: According to an example, in a method for managing storage of data from an input table, a projection definition that includes an expression to be executed on data contained in a column of the input table may be accessed. The expression on the data contained in the column of the input table may be executed to obtain results data, which may be stored in an expression projection, in which the expression projection includes a column that provides physical storage for the results data. The results data may be stored in the expression projection, segmented, and encoded. In addition, the expression projection may be stored in a node.

Abstract: The state of an application is capture in a conversation by accessing an electronic document representation of a user interface at a time corresponding to a post to the conversation. The user interface is of an application associated with the conversation. The representation is processed to generate an image representative of a state of the application at the time. The image or a representation thereof is caused to be displayed in the post to reflect the state of the application at selected point along a timeline defined by the conversation.

Abstract: In some examples, for a given authentication event between a plurality of devices in a network, a system identifies a set of events, at the devices, that are temporally related to the given authentication event. The system extracts features from the set of events by aggregating event data of the set of events. The system provides the extracted features to a classifier that detects unauthorized authentication events.

Abstract: According to an example, aggregation based event identification may include aggregating each of a plurality of source events by an event type of event types that represent dusters of the source events and/or a host of a source event of the source events to generate a reduced number of the source events. Aggregation based event identification may further include analyzing a characteristic for each of the reduced number of the source events, and assigning, based on the analysis of the characteristic for each of the reduced number of the source events, a characteristic weight to each of the reduced number of the source events. Further, aggregation based event identification may include aggregating the characteristic weights for each of the reduced number of the source events to determine an aggregated event issue weight for each of the reduced number of the source events.

Abstract: In some examples, a system extracts features from event data representing events in a computing environment, trains ensembles of machine-learning models for respective analytics modules of a plurality of different types of analytics modules, and detects, by the different types of analytics modules using the respective trained ensembles of machine-learning models, an anomalous entity in response to further event data.