A cable length calculation system (10) includes a controller (20) and a plurality of communication apparatuses (30) which are connected via a cable (40). A measurement master which is one communication apparatus (30) among the plurality of communication apparatuses (30) counts as a first number, the number of clock signals output by an oscillator from a time of transmitting a measurement packet until a time of receiving a response packet. A measurement slave which is a communication apparatus (30) different from the measurement master among the plurality of communication apparatuses (30) counts as a second number, the number of clock signals output by an oscillator from a time of receiving the measurement packet transmitted by the measurement master until a time of transmitting the response packet. The controller (20) calculates a length of the cable (40) between the measurement master and the measurement slave based on the first number and the second number.

A cable length calculation system (10) includes a controller (20) and a plurality of communication apparatuses (30) which are connected via a cable (40). A measurement master which is one communication apparatus (30) among the plurality of communication apparatuses (30) counts as a first number, the number of clock signals output by an oscillator from a time of transmitting a measurement packet until a time of receiving a response packet. A measurement slave which is a communication apparatus (30) different from the measurement master among the plurality of communication apparatuses (30) counts as a second number, the number of clock signals output by an oscillator from a time of receiving the measurement packet transmitted by the measurement master until a time of transmitting the response packet. The controller (20) calculates a length of the cable (40) between the measurement master and the measurement slave based on the first number and the second number.

A system and method for predicting performance for a contact center via machine learning includes invoking, by a processor, an interaction between a contact center resource and an end user, and recording, by the processor, the interaction. The processor automatically analyzes the recorded interaction for identifying attributes associated with the interaction. The processor provides the identified attributes to a machine learning model which predicts a performance score based on the identified attributes. The performance score is compared against a threshold score, and a recommendation is output by the processor based on the comparing. The end user may be a candidate contact center agent considered for hiring, and the recommendation may be to hire the candidate or advance the candidate to a next step of an interview process.

Systems and methods for a cloud management system which utilizes both technical and business metrics to achieve operational efficiencies. The systems and methods can be used to provide an elastic infrastructure model for an emergency notifications system which delivers near infinite scale with guaranteed near 100% uptime. In an embodiment, a mass recipient emulator can be utilized for testing of the notifications system with actual phone call or message exchange.

A framework in a cloud network that may allow for debugging at multiple vantage points at different layers (e.g., layer 2, layer 3, etc.). The methods may provide tracer or measurement services that filter, capture, or forward flows that may include packets, calls, or protocols to look for particular signatures.

A technology that facilitates implementation of verified routing scripts for a dynamic routing engine (DCE) of one or more automatic call distribution (ACD) systems is disclosed. Exemplary implementations may: emulate a DRE of one or more ACD systems; provide a training corpus to simulate inbound telephony calls to the DRE and simulate context of the simulated inbound telephony calls; obtain to-be-executed routing scripts; execute the routing scripts on emulated DRE with the provided training corpus to simulate inbound telephony calls to the DRE under the simulated context of the simulated inbound telephony calls; determine that the routing scripts executed within defined parameters; in response to the determination, verify the routing scripts; and provide the verified routing scripts for execution on a live DRE of one or more active ACD systems.

Automatic testing/analysis of local loops of telecommunications networks includes obtaining bits-per-tone data for a local loop of a telecommunications network and generating a bit value string from the bits-per-tone data. The bit value string is then analyzed to determine whether it includes a bit pattern indicative of an impairment of the local loop. Further approaches for automatically testing local loops of telecommunications networks include obtaining attenuation data for multiple tones carried by the local loop and determining whether the attenuation data falls below thresholds for providing a service using the local loop.

An automated contact center agent mobile device client infrastructure testing system comprising a mobile device command repository is disclosed. The system also has a mobile device control module that retrieves mobile device commands from the repository, receives instructions, data, and parameters for contact center device testing, runs predesignated contact center device test suites on at least one mobile device, receives contact center device test suite result data from mobile devices, and forwards the contact center device test suite result data received from mobile devices to a contact center device test manager system.

A system for centralized testing of web-based agent desktops has been devised. The invention uses a test control portal. The test control portal acts as the interface between the client interaction software systems testing system and analyst controlled test device, executes an extensive set of robust test directive commands with underlying routines to be used to specify test conditions without the use of programming ability on the part of the analyst, uses a robust set of report item and format choice designators to allow easy selection of a range of report content and styles.

Automatic testing/analysis of local loops of telecommunications networks includes obtaining bits-per-tone data for a local loop of a telecommunications network and generating a bit value string from the bits-per-tone data. The bit value string is then analyzed to determine whether it includes a bit pattern indicative of an impairment of the local loop. Further approaches for automatically testing local loops of telecommunications networks include obtaining attenuation data for multiple tones carried by the local loop and determining whether the attenuation data falls below thresholds for providing a service using the local loop.