Due to dynamic nature of current software development methods, changes in requirements are embraced and given proper consideration. However, this triggers the rank reversal problem which involves re-prioritizing requirements based on stakeholders’ feedback. It incurs significant cost because of time elapsed in large number of human interactions. To solve this issue, a Semi-Automated Framework for soFtware Requirements priOritizatioN (SAFFRON) is presented in this paper. For a particular requirement, SAFFRON predicts appropriate stakeholders’ ratings to reduce human interactions. Initially, item-item collaborative filtering is utilized to estimate similarity between new and previously elicited requirements. Using this similarity, stakeholders who are most likely to rate requirements are determined. Afterwards, collaborative filtering based on latent factor model is used to predict ratings of those stakeholders. The proposed approach is implemented and tested on RALIC dataset. The results illustrate consistent correlation, similar to state of the art approaches, with the ground truth. In addition, SAFFRON requires 13.5-27 less human interaction for reprioritizing requirements.
In @cite_8 , the authors supported stakeholder prioritization by ranking requirements based on the weight of their attributes provided by the relevant stakeholders. All the requirements must be mutually independent. This proposed approach deals with rank reversal and dependency issues. But the method of collecting requirement weight did not consider budget and time constraints.
@cite_8
281966469 109392617 1995790095 2088119904
Multiple-criteria decision making (MCDM) is widely used in ranking choices from a set of available alternatives with respect to multiple criteria. To analytically rank requirements under various criteria, we propose a tool called requirements prioritizer (RP) which has the capacity of keeping records of project stakeholders with their relative weights against each requirement, utilized by the system to compute an ordered list of prioritized requirements. The proposed approach offers a novel way of involving stakeholders in the entire decision making process irrespective of their numbers in an automated fashion. In this proposed approach, the relative weights assigned by each stakeholder are normalized and aggregated. The output of the system consists of prioritized requirements with an automatically generated graph showing the relative values of requirements across project stakeholders in a chronological order. Software requirements prioritization is the act of ranking user’s requirements in order to plan for release phases. The essence of prioritizing requirements is to avoid breach of contract, trust or agreement during software development process. This is crucial because, not all the specified requirements could be implemented in a single release due to inadequate skilled programmers, time, budget, and schedule constraints. Major limitations of existing prioritization techniques are rank reversals, scalability, ease of use, computational complexities and accuracy among others. Consequently, an innovative model that is capable of addressing these problems is presented. To achieve our aim, synthesized weights are computed for criteria that make up requirements and functions were defined to display prioritized requirements based on the global weights of attributes across project stakeholders. An empirical case scenario is described to illustrate the adaptability processes of the proposed approach. Requirements elicitation is the software engineering activity in which stakeholder needs are understood. It involves identifying and prioritizing requirements-a process difficult to scale to large software projects with many stakeholders. This paper proposes StakeRare, a novel method that uses social networks and collaborative filtering to identify and prioritize requirements in large software projects. StakeRare identifies stakeholders and asks them to recommend other stakeholders and stakeholder roles, builds a social network with stakeholders as nodes and their recommendations as links, and prioritizes stakeholders using a variety of social network measures to determine their project influence. It then asks the stakeholders to rate an initial list of requirements, recommends other relevant requirements to them using collaborative filtering, and prioritizes their requirements using their ratings weighted by their project influence. StakeRare was evaluated by applying it to a software project for a 30,000-user system, and a substantial empirical study of requirements elicitation was conducted. Using the data collected from surveying and interviewing 87 stakeholders, the study demonstrated that StakeRare predicts stakeholder needs accurately and arrives at a more complete and accurately prioritized list of requirements compared to the existing method used in the project, taking only a fraction of the time. The order in which requirements are implemented in a system affects the value delivered to the final users in the successive releases of the system. Requirements prioritization aims at ranking the requirements so as to trade off user priorities and implementation constraints, such as technical dependencies among requirements and necessarily limited resources allocated to the project. Requirement analysts possess relevant knowledge about the relative importance of requirements. We use an Interactive Genetic Algorithm to produce a requirement ordering which complies with the existing priorities, satisfies the technical constraints and takes into account the relative preferences elicited from the user. On a real case study, we show that this approach improves non interactive optimization, ignoring the elicited preferences, and that it can handle a number of requirements which is otherwise problematic for state of the art techniques.