NLG4RE:How NL generation can support validation in RE

Context and motivation: All too frequently functional requirements (FRs) for a (software) system are unclear. Written in natural language, FRs are underspecified for software developers; when written in formal language, FRs are insufficiently comprehensible for users. This is a well-known problem in RE. As long as this either/or dichotomy exists, FRs cannot be a “basis for common agreement among all parties involved”, as Barry Boehm puts it.Question/problem: On the one hand, FRs should unambiguously specify the functional behaviour of the system to be written or adapted, and on the other hand be fully understandable by the customer that must agree with them. What is required to achieve this goal?Principal ideas/results: A specification must describe the Statics as well as the Dynamics. In our approach it consists of a Conceptual Data Model (the data structure, i.e., the Statics) plus a set of System Sequence Descriptions (SSDs) representing the processes (i.e., the Dynamics). SSDs schematically depict the interactions between the primary actor (user), the system (as a black box), and other actors (if any), including the messages between them. We provide a set of rules to generate natural language expressions from both the ConceptualData Model and the SSDs that are understandable by the user (‘Informalisation of formal requirements’). Generating understandable representations of a specification is relevant for requirements validation tasks.Contribution to validation: We introduce a form of Natural Language Generation (the NLG in the title) by defining a grammar and mapping rules to precise and unambiguous expressions in natural language, in order to improve understandability of the FRs and the data model by the user community

Meta-analyze dichotomous data: Do the calculations with Log Odds Ratios and report Risk Ratios or Risk Differences

This paper describes a method to convert meta-analytic results in (log) Odds Ratio to either Risk Ratio or Risk Difference. It has been argued that odds ratios are mathematically superior for meta-analysis, but risk ratios and risk differences are shown to be easier to interpret. Therefore, the proposed method enables the calculation of meta-analytic results in (log) odds ratio and to transform them afterwards in risk ratio and risk difference. This transformation is based on the assumption of equal significance of the results. It is implemented Meta-Essentials: Workbooks for meta-analyses

Unraveling the dimensions of supplier involvement and their effects on NPD performance: a meta-analysis

We study the relationship between supplier involvement in New Product Development and performance. The current literature is scattered and fragmented with studies reporting mixed empirical evidence for a variety of concepts related to ‘Early Supplier Involvement’. We conduct a systematic review and meta‐analysis of the existing literature to reconcile conflicted findings, revise and refine theoretical perspectives, and provide evidence‐based scholarly and practical implications. To achieve these aims, we unravel the general relationship by considering three factors. First, we delineate different types of performance outcomes, mainly related to NPD efficiency (e.g., speed) and NPD effectiveness (e.g., product quality). Second, we distinguish between the moment and the extent of supplier involvement, related to different theoretical perspectives on external knowledge integration. Third, we disentangle multiple levels of analysis that are seemingly obscured in the literature, specifically the project and organizational levels. We find that extensive supplier involvement has positive effects on NPD efficiency and effectiveness, whereas earlier supplier involvement only to some degree affects NPD efficiency and not effectiveness. In conclusion, our meta‐analysis based on 11,420 observations from 51 studies provides strong theoretical and practical insights on the important phenomenon of supplier involvement