Cascading adaptive timeline generation and solving

A non-transitory computer-readable medium comprising instructions for generating cascading adaptive timelines that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• receiving, from a computing host, an input associated with a parameter of a first plurality of project parameters;
• and
• based on the input:
• modifying the parameter to generate a modified parameter;
• generating a second plurality of project parameters comprising the modified parameter;
• generating a cascading timeline of a plurality of project features based on the second plurality of project parameters;
• solving the cascading timeline by:
• sequentially traversing timeline data records representing the plurality of project features to determine an updated start date and an updated end date for a feature of the plurality of project features based on:
• the second plurality of project parameters,
• an updated previously solved start date, and
• an updated previously solved end date for an updated previous feature of the plurality of project features;
• allocating a next feature to a lane of indexed timeline lanes based on a soonest open date;
• and
• updating latest end dates among the indexed timeline lanes;
• determining a start date and an end date of the next feature by, according to an average velocity project parameter, converting units of a Swag feature parameter or units of a story point estimate feature parameter into a number of days, and adding the number of days to the start date of the next feature;
• and
• configuring the computing host to generate, using the plurality of project features, a visualization of the cascading timeline.

A system for generating cascading adaptive timelines, the system comprising:

• one or more processors;
• and
• a non-transitory memory storing computer-executable instructions that, when executed, cause the one or more processors to perform operations comprising:
• receiving, from a computing host, an input associated with a parameter of a first plurality of project parameters;
• and
• based on the input:
• modifying the parameter to generate a modified parameter;
• generating a second plurality of project parameters comprising the modified parameter;
• generating a cascading timeline of a plurality of project features based on the second plurality of project parameters;
• solving the cascading timeline by:
• sequentially traversing timeline data records representing the plurality of project features to determine an updated start date and an updated end date for a feature of the plurality of project features based on:
• the second plurality of project parameters,
• an updated previously solved start date, and
• an updated previously solved end date for an updated previous feature of the plurality of project features;
• allocating a next feature to a lane of indexed timeline lanes based on a soonest open date;
• and
• updating latest end dates among the indexed timeline lanes;
• determining a start date and an end date of the next feature by, according to an average velocity project parameter, converting units of a Swag feature parameter or units of a story point estimate feature parameter into a number of days, and adding the number of days to the start date of the next feature;
• and
• configuring the computing host to generate, using the plurality of project features, a visualization of the cascading timeline.