## 3 Method for Proactive Management of Requirement Changes
### Change Risk Assessment
#### 3.2.2 Requirement Change Impact Assessment
In addition, a damping factor \(d\) [0; 1] is required to resolve infinite loops in circular dependencies. The damping factor specifies the likelihood with which random propagation occurs. In terms of content, this can be justified by the uncertainty whether all existing dependencies are detected during the dependency analysis. The more exact the results of the dependency analysis are, the smaller the difference is to \(d~{}=~{}1\). In this context, \(d~{}=~{}0.85\) has been shown to be robust [63]. The equation for the modified page rank of a requirement is as follows:  
\[PR(r_{i})~{}=~{}\frac{1~{}-~{}d}{n}~{}+~{}d\sum_{r_{j}\in E_{i}^{in}}(\sum_{r _{k}\in E_{j}^{out}}\frac{PR\big{(}r_{j}\big{)}}{v_{kj}}) \tag{1}\]  
To evaluate the impact of a requirement change, the equation must be adapted to the direction of the dependencies as well as the weighting of a requirement in a second step. The weighted Active Rank \(AR_{w}(r_{i})\) is introduced as a new characteristic value (cf. Equation (2)). In contrast to the original PageRank algorithm, the outgoing dependencies and not the incoming dependencies are meaningful for propagation. Taking this into account, \(E_{i}^{in}\) and \(E_{i}^{out}\) are swapped in the equation. The occurrence of local change effects (weight of a requirement) depends on the propagation likelihood (weight of a dependency). Therefore, the specific weighting of a requirement \(P\big{(}r_{j}\big{)}\) is multiplied by the specific weighting of the dependency \(v_{ij}\). This results in the following equation for the weighted Active Rank of a requirement:  
\[AR_{w}(r_{i})~{}=~{}\frac{1~{}-~{}d}{n}~{}+~{}d\sum_{r_{j}\in E_{i}^{out}}( \sum_{r_{k}\in E_{j}^{in}}\frac{AR_{w}(r_{j})}{P(r_{k})\cdot v_{kj}}) \tag{2}\]  
After the analysis, the requirements are ranked in descending order. The higher the rank, the greater the expected change impact. The selection of critical requirements is based on the requirement's weighted Active Rank (cf. Figure 7). Depending on the context, different approaches can be suitable. Essentially, a distinction can be made between a threshold value and a predefined number of critical requirements. When using a threshold value, all requirements are categorized as critical for which \(AR_{w}(r_{i})~{}\geq~{}S_{K}\) applies. \(S_{K}\) is determined individually depending on the risk affinity. In the case of extensive requirement sets, methods such as the Top-10 method [[PERSON] and [PERSON] 2021, p. 118 f.] can also be used to limit the application effort, in which only the 10 requirements with the highest \(AR_{w}(r_{i})\) are categorized as critical. In addition to the selection based on the weighted Active Rank, users and subject matter experts have the option of classifying requirements as critical for individual reasons. This is useful, for example, if experience indicate a need for change with regard to a requirement or if a significant change impact is expected despite low connectivity. The analysis of the requirement network serves the complete evaluation of change effects of all requirements as well as the selection of critical requirements. This selection is necessary to reduce the application effort for the expert evaluation of the collective change impact to a practical level. The collective impact cannot be evaluated automatically, since a consideration of the requirement content is just as necessary as the inclusion of context-specific influencing variables (for instance, enterprise structure, contractual agreements or restrictions from the product lifecycle stage realization/production). Both the results of the analysis of the requirement network and an additional guideline for identifying affected development activities are used for determination of the collective change impact of a requirement (cf. Figure 8). The guideline was developed based on the systems engineering process landscape [65] and includes all activities potentially affected by a change. This ensures completeness of the analysis and reduces subjectivity of assessment.