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2022 Journal article Open Access OPEN

Drivers, barriers and impacts of digitalisation in rural areas from the viewpoint of experts
Ferrari A., Bacco M., Gaber K., Jedlitschka A., Hess S., Kaipainen J., Koltsida P., Toli E., Brunori G.
[Context] The domain of rural areas, including rural communities, agriculture, and forestry, is going through a process of deep digital transformation. Digitalisation can have positive impacts on sustainability in terms of greater environmental control, and community prosperity. At the same time, it can also have disruptive effects, with the marginalisation of actors that cannot cope with the change. When developing a novel system for rural areas, requirements engineers should carefully consider the specific socio-economic characteristics of the domain, so that potential positive effects can be maximised, while mitigating negative impacts. [Objective] The goal of this paper is to support requirements engineers with a reference catalogue of drivers, barriers and potential impacts associated to the introduction of novel ICT solutions in rural areas. [Method] To this end, we interview 30 cross-disciplinary experts in digitalisation of rural areas, and we analyse the transcripts to identify common themes. [Results] According to the experts, main drivers are economic, with the possibility of reducing costs, and regulatory, as institutions push for more precise tracing and monitoring of production; barriers are the limited connectivity, but also distrust towards technology and other socio-cultural aspects; positive impacts are socio-economic (e.g., reduction of manual labor, greater productivity), while negative ones include potential dependency from technology, with loss of hands-on expertise, and marginalisation of certain actors (e.g., small farms, subjects with limited education). [Conclusion] This paper contributes to the literature with a domain-specific catalogue that characterises digitalisation in rural areas. The catalogue can be used as a reference baseline for requirements elicitation endeavours in rural areas, to support domain analysis prior to the development of novel solutions, as well as fit-gap analysis for the adaptation of existing technologies.Source: Information and software technology 145 (2022). doi:10.1016/j.infsof.2021.106816
DOI: 10.1016/j.infsof.2021.106816
Project(s): DESIRA via OpenAIRE

See at: ISTI Repository Open Access | ISTI Repository Open Access | ISTI Repository Open Access | CNR ExploRA Open Access | www.sciencedirect.com Open Access


2022 Conference article Open Access OPEN

A zero-shot learning approach to classifying requirements: preliminary study
Alhoshan W., Zhao L., Ferrari A., Letsholo K. J.
Context and motivation: Natural Language Processing (NLP) techniques are constantly improving their capabilities, and deep learning approaches are now used in the daily practice of several application domains. Requirements engineering (RE) research has traditionally incorporated NLP solutions to ad-dress its fundamental tasks, such as classification, tracing, and defect detection. Question/problem: However, RE research often suffers from a lack of annotated datasets, and this makes it difficult to fully exploit supervised NLP techniques in general, and deep-learning ones in the specific, thereby losing the potential advantages offered by these techniques. Principal ideas/results: To address the problem of limited annotated datasets, we propose to use zero-shot classification, and apply this learning paradigm to RE tasks that can be treated as classification problems. We experimented with the task of distinguishing between two types of NFR requirements: usability and security requirement and obtained encouraging weighted F-scores over 80% and almost perfect recall rates from a number of the tested models, without any training data and fine-tuning. Contribution: This work paves the basis for further research in the application of zero-shot learning, and towards the solution of the long-standing problem of dataset annotation in RE.Source: REFSQ 2022 - 28th International Working Conference on Requirement Engineering: Foundation for Software Quality, pp. 52–59, Birmingham, UK, 21-24/03/2022
DOI: 10.1007/978-3-030-98464-9_5

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2022 Conference article Open Access OPEN

Towards explainable formal methods: from LTL to natural language with neural machine translation
Cherukuri H., Ferrari A., Spoletini P.
[Context and motivation] Requirements formalisation facilitates reasoning about inconsistencies, detection of ambiguities and identification of critical issues in system models. Temporal logic formulae are the natural choice when it comes to formalise requirements associated to desired system behaviours. [Ques tion/problem] Understanding and mastering temporal logic require a formal background. Means are therefore needed to make temporal logic formulae interpretable by engineers, domain experts and other stakeholders involved in the development process. [Principal ideas/results] In this paper, we propose to use a neural machine translation tool, named OPENNMT, to translate Linear Temporal Logic (LTL) formulae into corresponding natural language descriptions. Our results show that our translation system achieves an average BLEU (BiLingual Evaluation Understudy) score of 93.53%, which corresponds to high-quality translations. [Contribution] Our neural model can be applied to assess if requirements have been correctly formalised. This can be useful to requirements analysts, who may have limited confidence with LTL, and to other stakeholders involved in the requirements verification process. Overall, our research preview contributes to bridging the gap between formal methods and requirements engineering, and opens to further research in explainable formal methods.Source: REFSQ 2022 - 28th International Working Conference on Requirement Engineering: Foundation for Software Quality, pp. 79–86, Birmingham, UK, 21-24/03/2022
DOI: 10.1007/978-3-030-98464-9_7
Project(s): 4SECURAIL via OpenAIRE

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2022 Journal article Open Access OPEN

On the relationship between similar requirements and similar software: a case study in the railway domain
Abbas M., Ferrari A., Shatnawi A., Enoiu E., Saadatm M., Sundmark D.
Recommender systems for requirements are typically built on the assumption that similar requirements can be used as proxies to retrieve similar software. When a stakeholder proposes a new requirement, natural language processing (NLP)-based similarity metrics can be exploited to retrieve existing requirements, and in turn, identify previously developed code. Several NLP approaches for similarity computation between requirements are available. However, there is little empirical evidence on their effectiveness for code retrieval. This study compares different NLP approaches, from lexical ones to semantic, deep-learning techniques, and correlates the similarity among requirements with the similarity of their associated software. The evaluation is conducted on real-world requirements from two industrial projects from a railway company. Specifically, the most similar pairs of requirements across two industrial projects are automatically identified using six language models. Then, the trace links between requirements and software are used to identify the software pairs associated with each requirements pair. The software similarity between pairs is then automatically computed with JPLag. Finally, the correlation between requirements similarity and software similarity is evaluated to see which language model shows the highest correlation and is thus more appropriate for code retrieval. In addition, we perform a focus group with members of the company to collect qualitative data. Results show a moderately positive correlation between requirements similarity and software similarity, with the pre-trained deep learning-based BERT language model with preprocessing outperforming the other models. Practitioners confirm that requirements similarity is generally regarded as a proxy for software similarity. However, they also highlight that additional aspects come into play when deciding software reuse, e.g., domain/project knowledge, information coming from test cases, and trace links. Our work is among the first ones to explore the relationship between requirements and software similarity from a quantitative and qualitative standpoint. This can be useful not only in recommender systems but also in other requirements engineering tasks in which similarity computation is relevant, such as tracing and change impact analysis.Source: Requirements engineering (Lond., Internet) (2022). doi:10.1007/s00766-021-00370-4
DOI: 10.1007/s00766-021-00370-4

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2022 Journal article Open Access OPEN

Formal Methods in railways: a systematic mapping study
Ferrari A., Ter Beek M. H.
Formal methods are mathematically based techniques for the rigorous development of software-intensive systems. The railway signaling domain is a field in which formal methods have traditionally been applied, with several success stories. This article reports on a mapping study that surveys the landscape of research on applications of formal methods to the development of railway systems. Following the guidelines of systematic reviews, we identify 328 relevant primary studies, and extract information about their demographics, the characteristics of formal methods used and railway-specific aspects. Our main results are as follows: (i) we identify a total of 328 primary studies relevant to our scope published between 1989 and 2020, of which 44% published during the last 5 years and 24% involving industry; (ii) the majority of studies are evaluated through Examples (41%) and Experience Reports (38%), while full-fledged Case Studies are limited (1.5%); (iii) Model checking is the most commonly adopted technique (47%), followed by simulation (27%) and theorem proving (19.5%); (iv) the dominant languages are UML (18%) and B (15%), while frequently used tools are ProB (9%), NuSMV (8%) and UPPAAL (7%); however, a diverse landscape of languages and tools is employed; (v) the majority of systems are interlocking products (40%), followed by models of high-level control logic (27%); (vi) most of the studies focus on the Architecture (66%) and Detailed Design (45%) development phases. Based on these findings, we highlight current research gaps and expected actions. In particular, the need to focus on more empirically sound research methods, such as Case Studies and Controlled Experiments, and to lower the degree of abstraction, by applying formal methods and tools to development phases that are closer to software development. Our study contributes with an empirically based perspective on the future of research and practice in formal methods applications for railways. It can be used by formal methods researchers to better focus their scientific inquiries, and by railway practitioners for an improved understanding of the interplay between formal methods and their specific application domain.Source: ACM computing surveys (2022). doi:10.1145/3520480
DOI: 10.1145/3520480
Project(s): 4SECURAIL via OpenAIRE, ASTRail via OpenAIRE

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2022 Journal article Open Access OPEN

Exploring the ERTMS/ETCS full moving block specification: an experience with formal methods
Basile D., Ter Beek M. H., Ferrari A., Legay A.
Shift2Rail is a joint undertaking funded by the EU via its Horizon 2020 program and by main railway stakeholders. Several Shift2Rail projects aim to investigate the application of formal methods to new ERTMS/ETCS railway signalling systems that promise to move European railway forward by guaranteeing high capacity, low cost and improved reliability. We explore the ERTMS/ETCS level 3 full moving block specifications stemming from different Shift2Rail projects using UPPAAL and statistical model checking. The results range from novel rigorously formalised requirements to an operational model formally verified against scenarios with multiple trains on a single railway line. From the gained experience, we have distilled future research goals to improve the formal specification and verification of real-time systems, and we discuss some barriers concerning a possible uptake of formal methods and tools in the railway industrySource: International journal on software tools for technology transfer (Internet) 24 (2022): 351–370. doi:10.1007/s10009-022-00653-3
DOI: 10.1007/s10009-022-00653-3
Project(s): 4SECURAIL via OpenAIRE, ASTRail via OpenAIRE

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2021 Report Open Access OPEN

Formal methods in railways: a systematic mapping study
Ferrari A., Ter Beek M. H.
Formal methods are mathematically-based techniques for the rigorous development of software-intensive systems. The railway signaling domain is a field in which formal methods have traditionally been applied, with several success stories. This article reports on a mapping study that surveys the landscape of research on applications of formal methods to the development of railway systems. Our main results are as follows: (i) we identify a total of 328 primary studies relevant to our scope published between 1989 and 2020, of which 44% published during the last 5 years and 24% involving industry; (ii) the majority of studies are evaluated through Examples (41%) and Experience Reports (38%), while full-fledged Case Studies are limited (1.5%); (iii) Model checking is the most commonly adopted technique (47%), followed by simulation (27%) and theorem proving (19.5%); (iv) the dominant languages are UML (18%) and B (15%), while frequently used tools are ProB (9%), NuSMV (8%) and UPPAAL (7%); however, a diverse landscape of languages and tools is employed; (v) the majority of systems are interlocking products (40%), followed by models of high-level control logic (27%); (vi) most of the studies focus on the Architecture (66%) and Detailed Design (45%) development phases. Based on these findings, we highlight current research gaps and expected actions. In particular, the need to focus on more empirically sound research methods, such as Case Studies and Controlled Experiments, and to lower the degree of abstraction, by applying formal methods and tools to development phases that are closer to software development. Our study contributes with an empirically based perspective on the future of research and practice in formal methods applications for railways.Source: ISTI-TR-2021/006, 2021
DOI: 10.32079/isti-tr-2021/006
Project(s): 4SECURAIL via OpenAIRE, ASTRail via OpenAIRE

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2021 Report Open Access OPEN

Systematic evaluation and usability analysis of formal tools for railway system design
Ferrari A., Mazzanti F., Basile D., Ter Beek M. H.
Formal methods and supporting tools have a long record of success in the development of safety-critical systems. However, no single tool has emerged as the dominant solution for system design. Each tool differs from the others in terms of the modeling language used, its verification capabilities and other complementary features, and each development context has peculiar needs that require different tools. This is particularly problematic for the railway industry, in which formal methods are highly recommended by the norms, but no actual guidance is provided for the selection of tools. To guide companies in the selection of the most appropriate formal tools to adopt in their contexts, a clear assessment of the features of the currently available tools is required. To address this goal, this paper considers a set of 13 formal tools that have been used for railway system design, and it presents a systematic evaluation of such tools and a preliminary usability analysis of a subset of 7 tools, involving railway practitioners. The results are discussed considering the most desired aspects by industry and earlier related studies. While the focus is on the railway domain, the overall methodology can be applied to similar contexts. Our study thus contributes with a systematic evaluation of formal tools and it shows that despite the poor graphical interfaces, usability and maturity of the tools are not major problems, as claimed by contributions from the literature. Instead, support for process integration is the most relevant obstacle for the adoption of most of the tools.Source: ISTI-2021-TR/007, 2021
DOI: 10.32079/isti-tr-2021/007
Project(s): 4SECURAIL via OpenAIRE, ASTRail via OpenAIRE

See at: CNR ExploRA Open Access


2021 Contribution to book Open Access OPEN

Preface: 4th Workshop on Natural Language Processing for Requirements Engineering (NLP4RE 2021)
Abualhaija S., Aydemir F. B., Ferrari A., Guo J.
The Natural Language Processing for Requirements Engineering Workshop (NLP4RE) was established in 2018 as a venue to foster communication between researchers and practitioners interested in the field. The 2021 edition was held virtually in Essen, due to the COVID-19 pandemic, and saw the presentation of 10 papers covering different aspects of NLP4RE, including information extraction (e.g., rationale, causality), requirements classification and chat-bots. The workshop saw a lively participation, with over 25 participants during the keynote and about 20 participants during the paper presentation sessions.Source: REFSQ 2021: Joint Proceedings of Workshops, OpenRE, Posters and Tools Track, and Doctoral Symposium, edited by F. B. Aydemir, C. Gralha, 2021

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2021 Conference article Open Access OPEN

Is requirements similarity a good proxy for software similarity? An empirical investigation in industry
Abbas M., Ferrari A., Shatnawi A., Enoiu E. P., Saadatmand M.
[Context and Motivation] Content-based recommender systems for requirements are typically built on the assumption that similar requirements can be used as proxies to retrieve similar software. When a new requirement is proposed by a stakeholder, natural language processing (NLP)-based similarity metrics can be exploited to retrieve existing requirements, and in turn identify previously developed code. [Question/problem] Several NLP approaches for similarity computation are available, and there is little empirical evidence on the adoption of an effective technique in recommender systems specifically oriented to requirements-based code reuse. [Principal ideas/results] This study compares different state-of-the-art NLP approaches and correlates the similarity among requirements with the similarity of their source code. The evaluation is conducted on real-world requirements from two industrial projects in the railway domain. Results show that requirements similarity computed with the traditional tf-idf approach has the highest correlation with the actual software similarity in the considered context. Furthermore, results indicate a moderate positive correlation with Spearman's rank correlation coefficient of more than 0.5. [Contribution] Our work is among the first ones to explore the relationship between requirements similarity and software similarity. In addition, we also identify a suitable approach for computing requirements similarity that reflects software similarity well in an industrial context. This can be useful not only in recommender systems but also in other requirements engineering tasks in which similarity computation is relevant, such as tracing and categorization.Source: REFSQ 2021 - 27th International Working Conference on Requirements Engineering: Foundation for Software Quality, pp. 3–18, Online conference, 12-15/04/2021
DOI: 10.1007/978-3-030-73128-1_1

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2021 Conference article Open Access OPEN

SaPeer approach for training requirements analysts: an application tailored to a low-resource context
Vilela J., Ferrari A.
[Context and Motivation] Role-playing is a typical pedagogical strategy frequently applied in requirements engineering education and training (REET). The technique was proven to be successful for teaching different requirements engineering (RE) activities, and the SaPeer role-playing approach was recently proposed to train students in requirements elicitation interviews. SaPeer was shown to be effective and useful in the context of a high-resource RE module involving seven tutors, and a three-weeks individual assignment. [Question/Problem] RE lectures are frequently conducted as part of software engineering courses, or in short RE modules, and there is often limited time to teach RE in general, and interviews in particular. Therefore, SaPeer needs to be adapted to these constrained contexts, and adequately assessed. [Principal idea/Results] In this paper, we present the application of SaPeer to a low-resource context. We tailor the approach to a one-week group assignment, involving one tutor only, and we apply it to a class of 24 students. By comparing our results with the original study, we find that students struggle in similar areas, and especially in question omission and planning. A qualitative analysis of the feedback of the students shows the appreciation for the interview experience, and offers specific recommendations for improving the educational material. [Contribution] We contribute to the literature in REET with the first tailored application of SaPeer. Our study extends the scope of SaPeer and offers the possibility of adopting it in other constrained contexts.Source: REFSQ 2021 - 27th International Working Conference on Requirements Engineering: Foundation for Software Quality, pp. 191–207, Online conference, 12-15/04/2021
DOI: 10.1007/978-3-030-73128-1_14

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2021 Journal article Open Access OPEN

Natural Language Processing for Requirements Engineering
Zhao L., Alhoshan W., Ferrari A., Letsholo K. J., Ajagbe M. A., Chioasca E. V., Batista-Navarro R. T.
Natural Language Processing for Requirements Engineering (NLP4RE) is an area of research and development that seeks to apply natural language processing (NLP) techniques, tools, and resources to the requirements engineering (RE) process, to support human analysts to carry out various linguistic analysis tasks on textual requirements documents, such as detecting language issues, identifying key domain concepts, and establishing requirements traceability links. This article reports on a mapping study that surveys the landscape of NLP4RE research to provide a holistic understanding of the field. Following the guidance of systematic review, the mapping study is directed by five research questions, cutting across five aspects of NLP4RE research, concerning the state of the literature, the state of empirical research, the research focus, the state of tool development, and the usage of NLP technologies. Our main results are as follows: (i) we identify a total of 404 primary studies relevant to NLP4RE, which were published over the past 36 years and from 170 different venues; (ii) most of these studies (67.08%) are solution proposals, assessed by a laboratory experiment or an example application, while only a small percentage (7%) are assessed in industrial settings; (iii) a large proportion of the studies (42.70%) focus on the requirements analysis phase, with quality defect detection as their central task and requirements specification as their commonly processed document type; (iv) 130 NLP4RE tools (i.e., RE specific NLP tools) are extracted from these studies, but only 17 of them (13.08%) are available for download; (v) 231 different NLP technologies are also identified, comprising 140 NLP techniques, 66 NLP tools, and 25 NLP resources, but most of them-particularly those novel NLP techniques and specialized tools-are used infrequently; by contrast, commonly used NLP technologies are traditional analysis techniques (e.g., POS tagging and tokenization), general-purpose tools (e.g., Stanford CoreNLP and GATE) and generic language lexicons (WordNet and British National Corpus). The mapping study not only provides a collection of the literature in NLP4RE but also, more importantly, establishes a structure to frame the existing literature through categorization, synthesis and conceptualization of the main theoretical concepts and relationships that encompass both RE and NLP aspects. Our work thus produces a conceptual framework of NLP4RE. The framework is used to identify research gaps and directions, highlight technology transfer needs, and encourage more synergies between the RE community, the NLP one, and the software and systems practitioners. Our results can be used as a starting point to frame future studies according to a well-defined terminology and can be expanded as new technologies and novel solutions emerge.Source: ACM computing surveys 54 (2021). doi:10.1145/3444689
DOI: 10.1145/3444689

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2021 Contribution to journal Open Access OPEN

Requirements engineering: foundation for software quality (REFSQ2020)
Ferrari A., Madhavji N. H., Pasquale L.
Source: Information and software technology 137 (2021). doi:10.1016/j.infsof.2021.106636
DOI: 10.1016/j.infsof.2021.106636

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2021 Conference article Open Access OPEN

NLP for Requirements Engineering: tasks, techniques, tools, and technologies
Ferrari A., Zhao L., Alhoshan W.
Requirements engineering (RE) is one of the most natural language-intensive fields within the software engineering area. Therefore, several works have been developed across the years to automate the analysis of natural language artifacts that are relevant for RE, including requirements documents, but also app reviews, privacy policies, and social media content related to software products. Furthermore, the recent diffusion of game- changing natural language processing (NLP) techniques and plat- forms has also boosted the interest of RE researchers. However, a reference framework to provide a holistic understanding of the field of NLP for RE is currently missing. Based on the results of a recent systematic mapping study, and stemming from a previous ICSE tutorial by one of the authors, this technical briefing gives an overview of NLP for RE tasks, available techniques, supporting tools and NLP technologies. It is oriented to both researchers and practitioners, and will gently guide the audience towards a clearer view of how NLP can empower RE, providing pointers to representative works and specialised tools.Source: ICSE-Companion - 43rd IEEE/ACM International Conference on Software Engineering, pp. 322–323, Online conference, 25-28/05/2021
DOI: 10.1109/icse-companion52605.2021.00137

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2021 Journal article Open Access OPEN

Systematic evaluation and usability analysis of formal methods tools for railway signaling system design
Ferrari A., Mazzanti F., Basile D., Ter Beek M. H.
Formal methods and supporting tools have a long record of success in the development of safety-critical systems. However, no single tool has emerged as the dominant solution for system design. Each tool differs from the others in terms of the modeling language used, its verification capabilities and other complementary features, and each development context has peculiar needs that require different tools. This is particularly problematic for the railway industry, in which formal methods are highly recommended by the norms, but no actual guidance is provided for the selection of tools. To guide companies in the selection of the most appropriate formal methods tools to adopt in their contexts, a clear assessment of the features of the currently available tools is required. To address this goal, this paper considers a set of 13 formal methods tools that have been used for the early design of railway systems, and it presents a systematic evaluation of such tools and a preliminary usability analysis of a subset of 7 tools, involving railway practitioners. The results are discussed considering the most desired aspects by industry and earlier related studies. While the focus is on the railway signaling domain, the overall methodology can be applied to similar contexts. Our study thus contributes with a systematic evaluation of formal methods tools and it shows that despite the poor graphical interfaces, usability and maturity of the tools are not major problems, as claimed by contributions from the literature. Instead, support for process integration is the most relevant obstacle for the adoption of most of the tools. Our contribution can be useful to R&D engineers from railway signaling companies and infrastructure managers, but also to tool developers and academic researchers alike.Source: IEEE transactions on software engineering (2021). doi:10.1109/TSE.2021.3124677
DOI: 10.1109/tse.2021.3124677
Project(s): 4SECURAIL via OpenAIRE, ASTRail via OpenAIRE

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2021 Journal article Open Access OPEN

CaRE: a refinement calculus for requirements engineering based on argumentation theory
Elrakaiby Y., Borgida A., Ferrari A., Mylopoulos J.
The Requirements Engineering (RE) process starts with initial requirements elicited from stakeholders--however conflicting, unattainable, incomplete and ambiguous--and successively refines them until a consistent, complete, valid, and unambiguous specification is reached. This is achieved by balancing stakeholders' viewpoints and preferences to reach compromises through negotiation. Several frameworks have been developed to support this process in a structured way, such as KAOS, i*, and RationalGLR. However, none provides the means to model the dialectic negotiation inherent to the RE process, so that the derivation of specifications from requirements is fully explicit and traceable. To address this gap, we propose CaRE, a refinement calculus for requirements engineering based on argumentation theory. CaRE casts the RE refinement problem as an iterative argument between all relevant stakeholders, who point out defects (ambiguity, incompleteness, etc.) of existing requirements, and then propose suitable refinements to address them, thereby leading to the construction of a refinement graph. This graph is then a conceptual model of the RE process. The semantics of refinement graphs is provided using Argumentation Theory, enabling reasoning over the RE process and the automatic computation of software specifications. An alternate semantics is also presented based on abduction and using Horn Theory. The application of CaRE is showcased with an extensive example from the railway domain, and a prototype tool for identifying specifications in a refinement graph is presented.Source: Software and systems modeling (Print) (2021). doi:10.1007/s10270-021-00943-5
DOI: 10.1007/s10270-021-00943-5

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2021 Conference article Open Access OPEN

The rise and fall of COVID-19 contact-tracing apps: when NFRs collide with pandemic
Bano M., Arora C., Zowghi D., Ferrari A.
To complement the manual contact-tracing methods, a flood of coronavirus-related apps was launched in the first half of 2020. Despite the incredible promises made by the governments, contact-tracing apps did not live up to expectations. We analyzed the government commissioned contact-tracing apps from four countries in order to understand the non-functional requirements (NFRs) and socio-technical factors that hindered the success of these apps. We used the user reviews from the app stores for iOS and Android versions, and identified top news articles related to each app. We analyzed the timeline of events through news article along with the app reviews, NFR analysis, cultural comparison, and political influences. Our investigation revealed that the dominant factors behind the negligible success of these apps are complex and entangled with the cultural and political dimensions rather than being just technical. The multilayer diversity of the target users also impacted the design and development of contact-tracing apps in an extremely challenging situation. Our analysis brings into light important elements that are not normally considered as NFR but should be studied in the design of crisis management apps.Source: RE 2021 - 29th IEEE International Requirements Engineering Conference, pp. 106–116, Online conference, 20-24/09/2021
DOI: 10.1109/re51729.2021.00017

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2021 Conference article Open Access OPEN

From ideas to expressed needs: an empirical study on the evolution of requirements during elicitation
Debnath S., Spoletini P., Ferrari A.
Requirements are elicited from the customer and other stakeholders through an iterative process of interviews, prototyping, and other interactive sessions. Many communication phenomena may emerge in these early iterations, that lead initial ideas to be transformed, renegotiated, or reframed. Understanding how this process takes place can help in solving possible communication issues as well as their consequences. In this work, we perform an exploratory study of descriptive nature to understand in which way requirements get transformed from initial ideas into documented needs. To this end, we select 30 subjects that act as requirements analysts, and we perform a set of elicitation sessions with a fictional customer. The customer is required to study a sample requirements document for a system beforehand and to answer the questions of the analysts about the system. After the elicitation sessions, the analysts produce user stories for the system. These are compared with the original ones by two researchers to assess to which extent and in which way the initial requirements evolved throughout the interactive sessions. Our results show that between 30% and 38% of the produced user stories include content that can be fully traced to the initial ones, while the rest of the content is dedicated to new requirements. We also show what types of requirements are introduced through the elicitation process, and how they vary depending on the analyst. Our work contributes to theory in requirements engineering, with empirically grounded, quantitative data, concerning the impact of elicitation activities with respect to initial ideas.Source: RE 2021 - 29th IEEE International Requirements Engineering Conference, pp. 233–244, Online conference, 20-24/09/2021
DOI: 10.1109/re51729.2021.00028

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2020 Conference article Open Access OPEN

Using NLP to support terminology extraction and domain scoping: report on the H2020 DESIRA project
Bacco F. M., Brunori G., Dell'Orletta F., Ferrari A.
The ongoing phenomenon of digitisation is changing social and work life, with tangible effects on the socio-economic context. Understanding the impact, opportunities, and threats of digital transformation requires the identication of viewpoints from a large diversity of stakeholders, from policy makers to domain experts, and from engineers to common citizens. The DESIRA (Digitisation: Economic and Social Impacts in Rural Areas) EU H2020 project1 considers rural areas, with a strong focus on agricultural and forestry activities, and aims at assessing the impact of digital technologies in those domains by involving a large number of stakeholders, all across Europe, around 20 focal questions. Given the involvement of stakeholders with diverse background and skills, a primary goal of the project is to develop domain-specic and interactive reference taxonomies (i.e., structured classications of terms) to facilitate common understanding of technologies in use in each domain at today. The taxonomies, which aims at easing the learning of the meaning of technical and domain-specic terms, are going to be exploited by the stakeholders in 20 Living Labs built around the focal questions. This report paper focuses on the semi-automatic development of the taxonomies through natural language processing (NLP) techniques based on context-specic term extraction. Furthermore, we crawl Wikipedia to enrich the taxonomies with additional categories and denitions. We plan to validate the taxonomies through fieeld studies within the Living Labs.Source: Third Workshop on Natural Language Processing for Requirements Engineering, pp. 1–5, Pisa, Italy, 24 March 2020
Project(s): DESIRA via OpenAIRE

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2020 Conference article Open Access OPEN

IoT as a digital game changer in rural areas: the DESIRA conceptual approach
Bacco M., Brunori G., Ferrari A., Koltsida P., Toli E.
Digital transformation is a process encompassing significant changes in both social and economical domains because of the adoption of digital technologies. The EU H2020 DESIRA (Digitisation: Economic and Social Impacts in Rural Areas) project is working on defining a methodology and creating a knowledge base to characterize digital transformation. The goal is to support those in charge of responding to digitization-related challenges in rural areas, especially considering agriculture and forestry. This work presents preliminary activities in the project aiming to identify (i) Digital Game Changers, like Internet of Things (IoT), facilitating the digital transformation; and (ii) a robust set of exemplary Application Scenarios (ASs). This task will support forthcoming activities aiming to assess the socio-economic impact of digital transformation in rural areas.Source: 2020 Global Internet of Things Summit (GIoTS), Dublin (virtual), 3-5/06/2020
DOI: 10.1109/giots49054.2020.9119674
Project(s): DESIRA via OpenAIRE

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