Requirements Engineering (RE) has undergone several transitions over the years, from traditional methods to agile approaches emphasising increased automation. In many software development projects, requirements are expressed in natural language and embedded within large volumes of text documents. At the same time, RE activities aim to define software systems' functionalities and constraints. However, manually executing these tasks is time-consuming and prone to errors. Numerous research efforts have proposed tools and technologies for automating RE activities to address this challenge, which are documented in published works. This review aims to examine empirical evidence on automated RE and analyse its impact on the RE sub-domain and software development. To achieve our goal, we conducted a Systematic Literature Review (SLR) following established guidelines for conducting SLRs. We aimed to identify, aggregate, and analyse papers on automated RE published between 1996 and 2022. We outlined the output of the support tool, the RE phase covered, levels of automation, development approach, and evaluation approaches. We identified 85 papers that discussed automated RE from various perspectives and methodologies. The results of this review demonstrate the significance of automated RE for the software development community, which has the potential to shorten development cycles and reduce associated costs. The support tools primarily assist in generating UML models (44.7%) and other activities such as omission of steps, consistency checking, and requirement validation. The analysis phase of RE is the most widely automated phase, with 49.53% of automated tools developed for this purpose. Natural language processing technologies, particularly POS tagging and Parser, are widely employed in developing these support tools. Controlled experimental methods are the most frequently used (48.2%) for evaluating automated RE tools, while user studies are the least employed evaluation method (8.2%). This paper contributes to the existing body of knowledge by providing an updated overview of the research literature, enabling a better understanding of trends and state-of-the-art practices in automated RE for researchers and practitioners. It also paves the way for future research directions in automated requirements engineering.

This paper defines a catalogue of patterns for the specification and design of model transformations, and provides a systematic scheme and classification of these patterns, together with pattern application examples in leading model transformation languages such as ATL, QVT, GrGen.NET, and others. We consider patterns for improving transformation modularization and efficiency and for reducing data storage requirements. We define a metamodel-based formalization of model transformation design patterns, and measurement-based techniques to guide the selection of patterns. We also provide an evaluation of the effectiveness of transformation patterns on a range of different case studies.

A model transformation verification task may involve a number of different transformations, from one or more of a wide range of different model transformation languages, each transformation may have a particular transformation style, and there are a number of different verification properties which can be verified for each language and style of transformation. Transformations may operate upon many different modelling languages. This diversity of languages and properties indicates the need for a suitably generic framework for model transformation verification, independent of particular model transformation languages, and able to provide support for systematic procedures for verification across a range of languages, and for a range of properties. In this paper we describe the elements of such a framework, and apply this framework to some example transformation verification problems. The paper is novel in covering a wide range of different verification techniques for a wide range of MT languages, within an integrated framework.