Entit Software LLC

Hewlett-packard Development Company, L.p.

Micro Focus Lcc

Ofer Eliassaf

Amir Kessner

Meidan Zemer

Oded Keret

Leonid Pekel

Gil Zieder

Moshe Eran Kraus

Ohad Assulin

Yair Horovitz

Ithai Levi

Yaron Naveh

Boris Kozorovitzky

Efrat Egozi Levi

Peretz Regev

A method for identifying a push communication pattern includes creating clusters from a communication entity's response buffers. Clusters that meet a first criterion are detected. The communication entity is identified as having a push communication pattern upon a determination that the detected clusters meet a second criterion.

Identifying a push communication pattern

A risk level of a software commit is assessed through the use of a classifier. The classifier may be generated based on attributes pertaining to previous commits and used to determine a risk level for deployment of a software commit into a production environment based on attributes extracted from the software commit.

Software commit risk level

Identifying suspicious activity in utilizing a load testing service can include establishing an amount of domain calls to a domain, modifying the amount, and blocking domain calls exceeding the amount.

Identifying suspicious activity in a load test

A method for identifying a polling communication pattern within a sequence of communication entities includes grouping the communication entities into a plurality of clusters according to a criterion. Clusters are removed from the plurality according to at least one of a time pattern analysis, cluster size, and cluster duration. The clusters remaining are identified as having a polling communication pattern.

Identifying a polling communication pattern

A method for identifying an auto-complete communication pattern within a sequence of request entities includes grouping the request entities into a plurality of clusters according to a criterion. Clusters are removed from the plurality according to at least one of pattern analysis, a cluster size, and a cluster timing. Remaining clusters are identified as having an auto-complete communication pattern.

Identifying an auto-complete communication pattern

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.

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Modiin, Israel

Ofer Eliassaf