Optimal Development Path: An Empirical Evaluation of Tiered Dependency-Aware Sequencing - Aggregate Benchmark Results
收藏资源简介：
This repository provides the public aggregate benchmark results accompanying the research manuscript "Optimal Development Path: An Empirical Evaluation of Tiered Dependency-Aware Sequencing" by Azzeddine Ihsine and Sara Ihsine (Inovionix). The study evaluates the native Optimal Development Path (ODP) algorithm of D-POAF and four dependency-aware sequencing strategies (L0-L4). The experiments include synthetic dependency graphs and benchmark instances derived from 373 historical Jira sprints across 21 open-source projects in the TAWOS dataset. The public archive contains aggregate experimental results, comparative tables, figures, and documentation describing data provenance and access conditions. The archive does not include proprietary D-POAF platform source code, full experimental implementations, or confidential private-beta records. Detailed experimental materials may be requested from the corresponding author, Sara Ihsine ([sara.ihsine@inovionix.com](mailto:sara.ihsine@inovionix.com)), subject to access approval and applicable licensing restrictions. These results provide empirical evidence on the effectiveness and limitations of dependency-aware sequencing strategies, demonstrating how explicit prerequisite constraints can support the construction of valid, transparent, and auditable development sequences. By making declared dependencies part of the sequencing decision, the approach aims to reduce the risk of initiating Feature Blocks before their prerequisites are satisfied, a potential source of development interruptions, task switching, and rework. While these mechanisms offer a foundation for more structured development planning, their impact on actual project costs, delivery times, and operational efficiency remains to be evaluated through prospective studies involving completed D-POAF Waves.
