Using Genetic Algorithms to Search for Key Stakeholders in Large-Scale Software Projects

Abstract

Large software projects have many stakeholders. In order for the resulting software system and architecture to be aligned with the enterprise and stakeholder needs, key stakeholders must be adequately consulted and involved in the project. This work proposes the use of genetic algorithms to identify key stakeholders and their actual influence in requirements elicitation, given the stakeholders’ requirements and the actual set of requirements implemented in the project. The proposed method is applied to a large real-world software project. Results show that search is able to identify key stakeholders accurately. Results also indicate that many different good solutions exist. This implies that a stakeholder has the potential to play a key role in requirements elicitation, depending on which other stakeholders are already involved. This work demonstrates the true complexity of requirements elicitation – all stakeholders should be consulted, but not all of them should be treated as key stakeholders, even if they appear to be significant based on their role in the domain.

Social networks and crowdsourcing for stakeholder analysis in system of systems projects

“…Both tools suffer from the inability to scale to the large number of stakeholders that a system of systems might have. In addition, prioritization is likely to be biased towards the personal perspective of the analyst [17].…”

“…The idea is to be open and inclusive, so that each stakeholder participates in the stakeholder analysis process. As stakeholders are socially related to one another, they can be identified and prioritized using their relations [17]. Because of the complexity of systems of systems and large number of stakeholders involved, it is only with the participation of stakeholders and an intelligent aggregation of all their views that stakeholder analysis for systems of systems can be conducted effectively [17].…”

“…The proposed method identifies an initial set of stakeholders, asks the stakeholders to recommend other stakeholders, builds a social network with stakeholders as nodes and their recommendations as links, and prioritizes stakeholders using social network measures such as betweenness centrality and in-degree centrality [17,20]. The method is shown to be effective in identifying and prioritizing stakeholders in large software projects [17], and is supported by web-based application that we have developed called StakeSource 1 [20,21].…”

Quest for Requirements: Scrutinizing Advanced Search Queries for Cloud Services with Fuzzy Galois Lattices

“…Lim et al [20] present ideas on asynchronous and distributed stakeholder identification, assuming that key stakeholders are known, and further users can be identified based on domain knowledge. However, such approaches do not easily extend to the cloud context, since the audience for services is most often unknown and globally distributed.…”

Multilayered analysis of co-development of business information systems

“…Such sociometric relationships [8] can be revealed through various data collection methods, ranging from prescribed communication lines, and subjective judgements of reputation, to the observation of decision or general interaction processes [9]. For example, Lim et al [10] have developed a method for analyzing social networks of stakeholders of information systems based on recommendations. For identifying key players in such networks, the concept of centrality [11] plays an important role.…”