An Efficient Risk Analysis based Risk Priority in Requirement Engineering using Modified Goal Risk Model

Abstract

Risk analysis is traditionally considered a critical activity for the whole software system"s lifecycle. Risks are identified by considering technical aspects (e.g., failures of the system, unavailability of services, etc.) and handled by suitable countermeasures through a refined design. A modified Tropos goal model was developed in which the evidence of satisfaction and denial of the goal is calculated from the likelihood of the events corresponding to the goals. Relations are defined between multiple goals and events, which define the importance of a particular goal. The event may be considered as a risk according to their likelihood value. So the inter relation values of the goals and events gives the impact of that event on the particular goal. In order to analyze the risk in achieving some particular goals, a set of candidate solutions are generated. The candidate solutions are evaluated on the basis of a risk affinitive value of the goals according to their events. The risk affinitive value is calculated from the different set of risk parameters, which is set like high, medium and low. The risk parameters clearly evaluate the affinity of that event to a particular set of goals. A priority based parameter is added to the proposed approach to sort out the risk values. According to the proposed approach distinct cost to risk values are achieved. Finally, the candidate solutions with low cost are selected.

A framework for knowledge management in requirements engineering

“…Pilat and Kaindl (2011) adopt a spiral process to transform tacit knowledge into explicit and vice versa, with the idea of overcoming the problem of knowledge exchange and emphasising the importance of eliciting the requirements from that reciprocity. For Venkatesh and Kumar (2013), this proposal dominates the communication between the stakeholders, which solves part of the problem of the transfer and the exchange of knowledge when these parties are reluctant to do so. Olmos and Rodas (2014) argue that the process is incomplete, costly and time-consuming to implement; in addition, it does not achieve the transformation or the transfer of knowledge in the dimension that is required in RE.…”

Requirement Engineering – Analysis of Risk with Goal Method

“…The data set solutions obtained from the Tropos goal model are considered as the initial population which is subjected for the optimization. The cost calculation is conducted as the fitness function genetic algorithms for dataset solution are formed of six source node value [10]. The cost analysis to extract the cost effective dataset solutions among the extracted dataset solutions, the impact of each process in the software development in the case of the SDC is obtained by the association of the node to the source node value cost analysis is subjected to extract cost effective dataset among the extracted solutions, calculating the association of the node to the source node as a set of three tuples.…”