Every year software development industry requires a higher number of trained software engineers who are not only skilled programmers but also talented software projects managers. To deliver high‐quality software projects, engineers require of the application of sound engineering competencies along with discipline. Obtaining those practices usually require years of experience. Companies are not prepared to invest this time on engineers resulting in a high percentage of deficient projects. Here, the authors present a bachelor‐level competency‐based approach that develops and evaluates such competencies during a challenge‐based learning experience. In this way, the rate of successful projects where software engineers are involved will be higher, as they have obtained the appropriate competencies to deliver such projects.

Professional ethics as a social requirement leads universities to rethink ethics education schemes in their curricula to provide graduates with expertise in the ethical exercise of their professions. This paper describes an Ethical Competency Development Framework (ECDF) that enables undergraduates to develop their skills to resolve conflicts of interest and ethical problems in their professions. After that, we examine the results of applying the ECDF framework in a learning experience called Semester i: Consolidating an IT Department. From Fall 2017 to Spring 2021 there were eight semester offerings of this learning experience involving a population of 139 students. We found that the ECDF helps students develop high-performance thinking in ethical competency. For future work, we will continue gathering data from this learning experience. We hope the ECDF framework will be a model for the development of ethics in other undergraduate programs.

Harvested rainwater can support small-scale horticulture, but its value depends on the joint timing of rainfall, crop demand, capture area, and finite storage. We developed RainHarvest Garden Optimizer, an open-source R/Shiny decision-support application that couples crop phenology and crop-water requirements with rainwater capture, monthly tank storage, and linear-programming crop allocation. The revised formulation explicitly represents pre-irrigation storage, end-of-month storage, overflow, and non-negative water availability, and was evaluated through spatial climatologies, observed interannual variability, factorial climatic perturbations, and one-at-a-time sensitivity analysis. Across ten climatic cells, annual precipitation ranged from 384.7 to 951.4 mm and the annual $P/E{T}_0$ ratio from 0.20 to 0.61. Under the driest climatology, reaching 95% cultivated area required substantially greater catchment and storage infrastructure than under the wettest climate, while an exceptionally dry 2023 realization at T01 reduced maximum cultivated area to 61.7% even at the largest evaluated infrastructure combination. One-at-a-time analysis identified precipitation and tank capacity as the dominant physical drivers of response: a 20% reduction in precipitation decreased cultivated area by 17.7% and the gross-revenue (GR) objective by 23.0% on average. The application is intended for strategic, pre-season planning and identifies fully irrigated feasible crop plans rather than simulating yield loss under deficit irrigation.