Problem description (as is state) The Qt trial has several input channels for requirements: ● Community raised issues on the public RM tool (xxxx://xxxxxxxxxx.xx.xx) ● Commercial customers raise requirements directly to the company ● The Qt Company’s internal long term planning process. ● The open developer community’s long term planning process on public mailing lists. There are problems that include, for example: ● All decision-making data is not public by default, which encumbers combining and prioritising the requirements input channels. However, we see an opportunity here for augmenting the processes with both decision support systems research and intelligent recommendations. ● Management and decision-making is burdened by duplicate or very similar issues in the requirements database. This also results in inaccuracies in defining the requirements. ● Issues are being allocated to wrong people, or other incorrectly set properties or attribute values cause unnecessary work. ● End users do not necessarily know what the correct place for reporting issues is. ● Related issues and other similar tacit relationships are not being grouped, which makes understanding the whole and ensuring integrity and correctness challenging. As distinct problems none of the above are severe, yet as the problems accumulate they cause management overhead and unnecessary work to developers.
Problem description (as is state) Users are engaged using different channels and different ways. For understanding customer’s opinions, social media analysis has been advertised as one of the most promising methods. Wind Tre needs to xxxxxx massive user involvement and automated identification and extraction of requirements from user-generated content (e.g., Twitter, Facebook, and other social networks). Moreover Wind Tre would reduce interpretation conflicts among the stakeholders through a real-time synchronization capacity between enterprise and users, so that a speed-up of the decision process and overall company’s efficiency are achieved. Identify and extract requirements from user requests and monitor the pulse of the communities to identify acute issues to enable early risk assessment will enable Wind Tre to understands the customer’s needs. Taking collective decisions for enabling innovations on the basis of massive amount of requirements knowledge is a complex and challenging endeavour. OpenReq in supporting group decisions of stakeholders in requirement evaluation processes in a context where requirements themselves are inferred using intelligent systems technologies for many different input types. Allows: ● Automatically propose prioritization indicators for requirements derived from the user discussions (e.g., weight a requirement by the number of related user requests). ● Automatically propose prioritization indicators from usage behaviour (e.g., recommend a higher importance for issues related to highly used services.) ● Support stakeholders in the preparation for a group decision The trial will evaluate the usefulness of OpenReq in supporting group decisions of stakeholders in requirement evaluation processes in a context where requirements themselves are inferred using intelligent systems technologies for many different input types.
