Abstract
Nowadays, more organizations adopt agile methodologies to guarantee short and frequent delivery times. A plethora of novel approaches and concepts regarding requirements engineering in this context are emerging. User stories are usually informally described as general explanations of software features, written from end-users perspective, while acceptance criteria are high-level conditions that enable their verification. This paper focuses on the art of writing user stories and acceptance criteria, but also on their relationships with other related concepts, such as quality requirements. In the pursuance of deriving guidelines and linguistic patterns to facilitate the writing of requirements specifications, a systematic literature review was conducted to provide a cohesive and comprehensive analysis of such concepts. Despite considerable research on the subject, no formalized model and systematic approach to assist this writing. We provide a coherent analysis of these concepts and related linguistic patterns supported by a running example of specifications built on top of ITLingo RSL, a publicly available tool to enforce the rigorous writing of specification artefacts. We consider that adopting and using the guidelines and patterns from the present discussion contribute to writing better and more consistent requirements.

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Abstract
OVER A DECADE ago, Jeff Offutt noted, The field of mutation analysis has been growing, both in the number of published papers and the number of active researchers.(33) This trend has since continued, as confirmed by a survey of recent literature.(36) Mutation analysis is the use of well-defined rules defined on syntactic descriptions to make systematic changes to the syntax or to objects developed from the syntax.(33) It has been successfully used in research for assessing test efficacy and as a building block for testing and debugging approaches. It systematically generates syntactic variations, called mutants, of an original program based on a set of mutation operators, which are well-defined program transformation rules. The most common use case of mutation analysis is to assess test efficacy. In this use case, mutants represent faulty versions of the original program, and the ratio of detected mutants quantifies a test suite's efficacy. Empirical evidence supports the use of systematically

Abstract
The main purpose for conducting this research is to analyze the core advantages and disadvantages of automatic assessment tools. With this in mind, we considered two different web sites of two distinct Portuguese Universities and compare the accessibility and usability issues found, aiming at identifying core problems through errors / warnings. This outcome will help us understand the weaknesses of such automatic tools and, thus, suggest features that could be added to improve their analysis. These findings will serve as a basis for a proposal of a new type of platform capable of making any web or mobile application accessible to all types of users, regardless of their impairments (e.g., blindness, deafness, motor or intellectual disabilities). © 2022 IEEE.

Abstract
This work focuses on the issues encountered when using current evaluation tools to assess the accessibility and usability of web and mobile applications. Therefore, we present a case study, where we tested three accessibility assessment tools against the official website of Portuguese Institute for Employment and Vocational (IEFP), used by millions of users nationwide. Indeed, we found that individual tools still provide limited coverage of success criteria and, thus, user verification is consistently needed. In this regard, we also aim at proposing a new tool called IncWeb, that can automatically alter any web or mobile application into a usable and fully accessible one, in a way that is transparent to the user and adapted to his type of disability. As such, this work emphasizes the importance of having appropriate tools to facilitate the lives of people with disabilities and/or special needs, presenting not only the problems of other assessment tools, but also proposing a new paradigm-changing solution to overcome those known challenges. © 2022 Elsevier B.V.. All rights reserved.

Abstract
Research data management (RDM) practices are critical for ensuring research success. Data can assume diverse formats and data in image format have been understudied in RDM. To understand image management habits in research, we have conducted semi-structured interviews with researchers from four research domains. Most researchers do not formally manage their images, nor do they develop RDM plans. They assume that image management is not a topic discussed at project meetings. In turn, they tend to perform some individual practices, depending on the context and their own opinion, such as creating captions to describe the images and organizing and storing the images in specific locations. However, they see these habits as necessary and admit that they will start to do so in a formal and collaborative way with the working group. These results provide valuable information on practical aspects of the use and production of images in research.