Software for large enterprises such as the enterprise resource planning (ERP) is more likely to be developed by a team of software developers where the functional requirements (FRs) are distributed in parallel developers. Therefore, development of pre-requisite FRs must be carefully timed to see which requirement is to be implemented first by assigning priority to some FRs over others, so that FRs can be made available on time to parallel developers. This research proposes a hybrid prioritization technique of minimal spanning trees (MST) and AHP called the spanning analytic hierarchical process (SAHP) for FRs prioritization by exploiting MST capability to prioritize large size software FRs with smaller pairwise comparisons but with more consistent results. Using Numerical Assignment (NA) technique, prioritized FRs from SAHP are assigned to priority groups such that top-priority groups contain high-priority FRs and low-priority groups contain low-priority FRs. low-priority group of FRs are dependent on high-priority groups. As a result, within each priority group, inter-dependencies in FRs are reduced for parallel developers. The proposed technique is evaluated on FRs of ODOO ERP and the results showed that SAHP reduces estimation time of parallel developers as compared to AHP and other techniques.

企业资源规划 (ERP) 等大型企业的软件更有可能由一组软件开发人员开发，其中功能需求 (FR) 分布在并行开发人员中。因此，必须仔细安排先决条件 FR 的开发时间，以便通过将优先级分配给某些 FR 而不是其他 FR 来确定首先实现哪个要求，以便 FR 可以按时提供给并行开发人员。本研究提出了一种最小生成树 (MST) 和 AHP 的混合优先级排序技术，称为生成分析层次过程 (SAHP)，用于 FR 优先级排序，通过利用 MST 功能对大型软件 FR 进行优先级排序，具有较小的成对比较但具有更一致的结果。使用数值分配（NA）技术，来自 SAHP 的优先级 FR 被分配给优先级组，使得最高优先级组包含高优先级 FR，低优先级组包含低优先级 FR。FR 的低优先级组依赖于高优先级组。因此，在每个优先级组中，并行开发人员减少了 FR 中的相互依赖性。所提出的技术在 ODOO ERP 的 FR 上进行了评估，结果表明，与 AHP 和其他技术相比，SAHP 减少了并行开发人员的估计时间。