Citation: Position Papers of the 2019 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 19, pages 59–66 (2019)
Abstract. Once an automotive OEM decided to source a new component, a Request for Quotation (RFQ) is send to potential suppliers. Among other documents the RFQ contains a Component Requirements Specification (CRS), which describes the properties of the desired component. As a next step, the supplier has to evaluate the requirements and other boundary conditions of the RFQ and to provide an offer to the OEM. In case the supplier already developed a similar component in the past, it is possible to compare the CRS of the predecessor product with the actual CRS, to estimate the additional development effort. This activity is known as the delta analysis. Since no sufficient tool support is offered, this activity is still a predominantly manual task. The main challenge arises from the fact, that specification documents within the RFQ are provided in different office formats, written by different authors and therefore cannot be compared automatically with the CRS from the predecessor product. In our previous work, we presented the Requirements to Boilerplates Converter (R2BC), which automatically converts random natural language requirements into a predefined syntax. The aim of the approach is to facilitate a subsequent toolbased delta analysis. Consequently, we hereby introduce our proprietary developed Delta Analyzer (DA). This tool is based on Natural Language Processing (NLP) and allows to compare automatically two random specification documents. Moreover, the DA prioritizes requirements deltas according to their impact on development effort. As an output of the DA requirements engineers receive a delta report, which outlines the major differences between the requirements of the two CRS.We validate our approach by experiments on real-life specification documents.
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