Abstract: A system for providing compartmented access to secure data assets includes a mobile device, a secure access platform, and a secure data storage platform. The mobile device may be configured to generate a user interface configured to allow a user to input credentials and a request for a secure data asset on the secure data storage platform. The mobile device may transmit the credentials and the request to a secure access platform. The secure access platform may transmit the credentials to the secure data storage platform. The secure data storage platform may transfer a copy of the secure data assets to a data access module on the secure data access platform. The secure access platform may be configured to create an appling instance, receive the copy of the secure data assets, and transmit a response package based on the copy of the secure data access to the mobile device.

Abstract: A system and method of generating a reuse metric starts with a processor receiving from a client device, a program comprising modules. Processor extracts the modules from the program and generates frequency tables associated with the modules. Frequency tables includes numbers of imports associated with the modules, and import ratios associated with the modules. Processor generates, based on the frequency tables, a histogram of the modules and the import ratios. Processor generates key statistical measures based on the import ratios and the histogram. Generating the key statistical measures comprises determining histogram weights, determining a Pareto fit of the histogram, and generating a reuse metric based on the Pareto fit and a Kurtosis of the histogram weights. Processor causes the client device to display the reuse metric and the histogram. Other embodiments are disclosed herein.

Abstract: A system and method of generating a reuse metric starts with a processor receiving from a client device, a program comprising modules. Processor extracts the modules from the program and generates frequency tables associated with the modules. Frequency tables includes numbers of imports associated with the modules, and import ratios associated with the modules. Processor generates, based on the frequency tables, a histogram of the modules and the import ratios. Processor generates key statistical measures based on the import ratios and the histogram. Generating the key statistical measures comprises determining histogram weights, determining a Pareto fit of the histogram, and generating a reuse metric based on the Pareto fit and a Kurtosis of the histogram weights. Processor causes the client device to display the reuse metric and the histogram. Other embodiments are disclosed herein.

Abstract: Methods and systems for aggregating and curating data are described.

Abstract: A system for providing compartmented access to secure data assets includes a mobile device, a secure access platform, and a secure data storage platform. The mobile device may be configured to generate a user interface configured to allow a user to input credentials and a request for a secure data asset on the secure data storage platform. The mobile device may transmit the credentials and the request to a secure access platform. The secure access platform may transmit the credentials to the secure data storage platform. The secure data storage platform may transfer a copy of the secure data assets to a data access module on the secure data access platform. The secure access platform may be configured to create an appling instance, receive the copy of the secure data assets, and transmit a response package based on the copy of the secure data access to the mobile device.

Abstract: A system and method of generating a reuse metric starts with a processor receiving from a client device, a program comprising modules. Processor extracts the modules from the program and generates frequency tables associated with the modules. Frequency tables includes numbers of imports associated with the modules, and import ratios associated with the modules. Processor generates, based on the frequency tables, a histogram of the modules and the import ratios. Processor generates key statistical measures based on the import ratios and the histogram. Generating the key statistical measures comprises determining histogram weights, determining a Pareto fit of the histogram, and generating a reuse metric based on the Pareto fit and a Kurtosis of the histogram weights. Processor causes the client device to display the reuse metric and the histogram. Other embodiments are disclosed herein.

Abstract: A system includes memory hardware that stores an event logging database including entries corresponding to events processed at local servers. The processor hardware executes instructions including, in response to receiving a first message from a first local server (the first message indicates that a first event occurred), identifying a causal parent event preceding the first event. The causal parent event is a most recent event that occurred at the first local server. The instructions include identifying a temporal parent event preceding the first event. The temporal parent event is a most recent event that occurred across all of the local servers. The instructions include generating a new entry based on data from the first message and a cryptographic hash based on a hash of a first entry recording the causal parent event and a hash of a second entry recording the temporal parent event.

Abstract: A method includes maintaining an event logging database including entries corresponding to events processed at local servers. The method includes, in response to receiving a first message from a first local server, where the first message indicates that a first event occurred, identifying a causal parent event preceding the first event. The causal parent event is a most recent event that occurred at the first local server. The method includes identifying a temporal parent event preceding the first event. The temporal parent event is a most recent event that occurred across all of the plurality of local servers. The method includes generating a new entry based on data from the first message, an identifier of a first entry recording the causal parent event, and an identifier of a second entry recording the temporal parent event. The method includes adding the new entry to the event logging database.