Hewlett-Packard Development Company, L.p.

Hewlett Packard Enterprise Development LP

Micro Focus Lcc

Entit Software LLC

Shunra Software Ltd.

Yair Horovitz

Ithai Levi

Noam Fraenkel

Doron Shaked

Ira Cohen

Amichai Nitsan

Ron Maurer

Eli Mordechai

Moshe Eran Kraus

Dror Schwartz

Sagi Monza

Igor Nor

Fernando Vizer

Meidan Zemer

Ofer Eliassaf

Olga Kogan-Katz

Leonid Pekel

Gal Ofel

Nitsan Amichai

Nurit Peres

Gal Alon

Igor Giller

Marina Lyan

Zohar Adler

Salman Yaniv Sayers

Maria Smolkov

Gil Perel

Peretz Regev

Shlomo Jacobson

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.

Graphs with normalized actual value measurements and baseline bands representative of normalized measurement ranges

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.

Aggregation based event identification

In some examples, a first pair of parameters in respective first and second log message streams associated with respective first and second source components and a second pair of parameters in the respective first and second log message streams may be identified. The first pair may be identical and the second pair may be identical. It may be determined that first pair of parameters was simultaneously generated and that the second pair of parameters was simultaneously generated in the first and in the second log message streams. A linkage score may be determined between the first and the second source components. The linkage score may be based on the determination that each of the respective first and the second pairs of parameters was simultaneously generated. It may be determined that that the first and second source components are topologically linked based on the linkage score.

Determining topology using log messages

Dependency monitoring can include monitoring a first application and a second application for un-expected behavior. Dependency monitoring can also include receiving a description of a number of dependencies between a number of applications wherein the description of the number of dependencies is created before monitoring of the first application and the second application begins. Dependency monitoring can include sending a message to an information technology (IT) personnel, wherein the message identifies a dependency from the number of dependencies between the first application and the second application based on the description of the number of dependencies.

Dependency monitoring

Examples disclosed herein relate to generating a fingerprint representing a response of an application to a simulation of a fault of an external service. Examples include causing simulation of a fault of an external service in a simulation of the external service, and generating a testing application fingerprint representing a response of an application to the simulation of the fault of the external service during the testing of the application.

Generating a fingerprint representing a response of an application to a simulation of a fault of an external service

Methods, computer-readable media, and systems are provided for usability testing. Usability testing can include recording, via a testing toot, actions of a user of an application and interactions of the user with the application. Usability testing can also include comparing, via the testing tool, the actions and interactions of the user with a baseline flow of actions for the application. Usability testing can include identifying, via the testing tool, a usability problem with the application based on the comparison.

Usability testing

Executable software specification generation can include recording interactions with a user-interface (UI) mockup for a particular program and generating a number of executable software specification for the particular program based on the interactions with the UI mockup.

Executable software specification generation

A method for automatic revision of an automation script includes obtaining a sequence of at least one classified recorded action and an automation script, the automation script including a sub-sequence of the sequence of classified recorded actions, wherein each action is included in the automation script in accordance with the classification of that action. At least a portion of the automation script is executed. Upon failure of an action of the portion of the automation script to execute, an action of the sequence of classified recorded actions is reclassified, it is verified if the action that failed to execute executes successfully after the reclassifying, and the automation script is revised. Relating computer program product and data processing system are also disclosed.

Automatic classification adjustment of recorded actions for automation script

Example embodiments disclosed herein relate to enhancing test scripts with dynamic data. The disclosed embodiments include receiving production data that reflects real user interaction with an application process. Test scripts are generated based on the production data, where the test scripts simulate behavior relating to execution of the application process. The embodiments also include automatically enhancing the test scripts with dynamic data that includes at least one of correlation data and asynchronous data.

Enhancing test scripts

User interactions with an existing software product are recorded so as to generate a list of actions performed by or triggered by the interaction. The list of actions is then used to generate requirements for a new software product under development.

Software development requirements recording

A system can comprise a memory to store machine readable instructions. The system can also comprise a processing unit to execute the machine readable instructions. The machine readable instructions can comprise an event extractor to parse a packet capture (pcap) file that includes a packet transmitted via a network between an application under test (AUT) executing on a mobile device and a server to determine a network event based on the packet. The event extractor can also generate an application programming interface (API) command file that includes an API command generated based on the network event.

Event extractor

A system and method for evaluating a portion of a response time of an application that is attributable to an element on a virtual IP network by emulating a condition on a network, running the application on the network under the emulated network conditions and measuring a portion of the response time of the application that is attributable to elements on the network under such emulated conditions. The application may be varied and response times of various network elements may be measured under one or more of the variations.

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Mazkeret Batya, Israel

Yair Horovitz