Probabilistic Enhancement to the LEAP Process for Identifying Technical Debt in Iterative System Development

The List, Evaluate, Achieve, Procure (LEAP) process defines a methodology for mathematically associating the delivery of system capabilities with the temporal satisfaction of stakeholder needs while identifying technologies at high risk of imparting technical debt into the system. The original process is qualitative, relying on binary definitions of timelines for technology development – the technology either is or is not developed in a specific time period. The binary definitions allow for rapid high-level assessments of the potential for technical debt. However, they fail to capture more realistic scenarios of uncertain technology development timelines. This paper resolves these issues by introducing probability into LEAP process. This paper also provides examples of using the probability in the LEAP process and compares the probabilistic (quantitative) and binary (qualitative) models. These examples show improvements in the ability to assess the likelihood of delivering capabilities in time to meet stakeholder needs when using the probabilistic version of the LEAP process. Since the impact of technical debt is uncertain, the inclusion of probabilities within the LEAP process provides a higher fidelity decision support system for iterative release planning and system development.