2011
Report
Unknown
CBTC preliminary report
Ferrari A.
CBTC are modern railway signaling systems used in urban railway lines for light rail (e.g., tranvia), heavy rail (e.g., metro) and APM (Automated People Mover, e.g., Airport metros). Sometimes, they can be deployed also on commuter lines (rails going to suburban areas, e.g., S-Bhan). This document summarizes the main features that a generic CBTC shall support, based on the current IEEE standards and on the currently analyzed implementationsSource: ISTI Technical reports, 2011
Ferrari A.
CBTC are modern railway signaling systems used in urban railway lines for light rail (e.g., tranvia), heavy rail (e.g., metro) and APM (Automated People Mover, e.g., Airport metros). Sometimes, they can be deployed also on commuter lines (rails going to suburban areas, e.g., S-Bhan). This document summarizes the main features that a generic CBTC shall support, based on the current IEEE standards and on the currently analyzed implementationsSource: ISTI Technical reports, 2011
See at: CNR ExploRA
2011
Report
Unknown
Evaluation of the IBM rhapsody tool for modeling automatic train protection (ATP) systems: the restrictive signal confirmation (RSC) button
Ferrari A., Illiashenko Oleg, Parfenov Sergii
The current document reports the evaluation of the IBM Rational Rhapsody tool for the modeling of Automatic Train Protection (ATP) systems software. The focus of the activity is on the Restrictive Signal Confirmation (RSC) button, a typical control component that, through not used in every ATP system, is considered a good representative of the expected functionality of an ATP software.Source: ISTI Technical reports, 2011
Ferrari A., Illiashenko Oleg, Parfenov Sergii
The current document reports the evaluation of the IBM Rational Rhapsody tool for the modeling of Automatic Train Protection (ATP) systems software. The focus of the activity is on the Restrictive Signal Confirmation (RSC) button, a typical control component that, through not used in every ATP system, is considered a good representative of the expected functionality of an ATP software.Source: ISTI Technical reports, 2011
See at: CNR ExploRA
2016
Conference article
Open Access
Empowering requirements elicitation interviews with vocal and biofeedback analysis
Spoletini P., Brock C., Shahwar R., Ferrari A.
Interviews with stakeholders are the most commonly used elicitation technique, as they are considered one of the most effective ways to transfer knowledge between requirements analysts and customers. During these interviews, ambiguity is a major obstacle for knowledge transfer, as it can lead to incorrectly understood needs and domain aspects and may ultimately result in poorly defined requirements. To address this issue, previous work focused on how ambiguity is perceived on the analyst side, i.e., when the analyst perceives an expression of the customer as ambiguous. However, this work did not consider how ambiguity can affect customers, i.e., when questions from the analyst are perceived as ambiguous. Since customers are not in general trained to cope with ambiguity, it is important to provide analysts with techniques that can help them to identify these situations. To support the analysts in this task, we propose to explore the relation between a perceived ambiguity on the customer side, and changes in the voice and bio parameters of that customer. To realize our idea, we plan to (1) study how changes in the voice and bio parameters can be correlated to the levels of stress, confusion, and uncertainty of an interviewee and, ultimately, to ambiguity and (2) investigate the application of modern voice analyzers and wristbands in the context of customer-analyst interviews. To show the feasibility of the idea, in this paper we present the result of our first step in this direction: an overview of different voice analyzers and wristbands that can collect bio parameters and their application in similar contexts. Moreover, we propose a plan to carry our research out.Source: 2016 IEEE 24th International Requirements Engineering Conference, pp. 371–376, Beijing, China, 12-16 September 2016
DOI: 10.1109/re.2016.56
Metrics:
Spoletini P., Brock C., Shahwar R., Ferrari A.
Interviews with stakeholders are the most commonly used elicitation technique, as they are considered one of the most effective ways to transfer knowledge between requirements analysts and customers. During these interviews, ambiguity is a major obstacle for knowledge transfer, as it can lead to incorrectly understood needs and domain aspects and may ultimately result in poorly defined requirements. To address this issue, previous work focused on how ambiguity is perceived on the analyst side, i.e., when the analyst perceives an expression of the customer as ambiguous. However, this work did not consider how ambiguity can affect customers, i.e., when questions from the analyst are perceived as ambiguous. Since customers are not in general trained to cope with ambiguity, it is important to provide analysts with techniques that can help them to identify these situations. To support the analysts in this task, we propose to explore the relation between a perceived ambiguity on the customer side, and changes in the voice and bio parameters of that customer. To realize our idea, we plan to (1) study how changes in the voice and bio parameters can be correlated to the levels of stress, confusion, and uncertainty of an interviewee and, ultimately, to ambiguity and (2) investigate the application of modern voice analyzers and wristbands in the context of customer-analyst interviews. To show the feasibility of the idea, in this paper we present the result of our first step in this direction: an overview of different voice analyzers and wristbands that can collect bio parameters and their application in similar contexts. Moreover, we propose a plan to carry our research out.Source: 2016 IEEE 24th International Requirements Engineering Conference, pp. 371–376, Beijing, China, 12-16 September 2016
DOI: 10.1109/re.2016.56
Metrics:
See at:
ISTI Repository 
| doi.org 
| ieeexplore.ieee.org | CNR ExploRA
2017
Conference article
Restricted
Requirements Elicitation: A Look at the Future Through the Lenses of the Past
Spoletini P., Ferrari A.
Requirements elicitation is the initial step of the requirements engineering process and aims at gathering all the relevant requirements through the direct or indirect interactions between requirements analysts and stakeholders. Even if the requirements elicitation problem is not new and has been approached many times over the years, it is still considered one of the most challenging of the requirements engineering process. In the proposed presentation, we aim at analyzing the journey of the research on requirements elicitation through the 25 years of the Requirements Engineering conference not only by considering the different proposed approaches and their evolution, but also by evaluating the role of requirements elicitation in the conference. Moreover, we will present the lessons learnt during this analysis and will use them as a starting point to present the current trends and outline possible future directions.Source: Requirements Engineering Conference (RE), 2017 IEEE 25th International, pp. 476–477, 04
DOI: 10.1109/re.2017.35
Metrics:
Spoletini P., Ferrari A.
Requirements elicitation is the initial step of the requirements engineering process and aims at gathering all the relevant requirements through the direct or indirect interactions between requirements analysts and stakeholders. Even if the requirements elicitation problem is not new and has been approached many times over the years, it is still considered one of the most challenging of the requirements engineering process. In the proposed presentation, we aim at analyzing the journey of the research on requirements elicitation through the 25 years of the Requirements Engineering conference not only by considering the different proposed approaches and their evolution, but also by evaluating the role of requirements elicitation in the conference. Moreover, we will present the lessons learnt during this analysis and will use them as a starting point to present the current trends and outline possible future directions.Source: Requirements Engineering Conference (RE), 2017 IEEE 25th International, pp. 476–477, 04
DOI: 10.1109/re.2017.35
Metrics:
See at:
doi.org | CNR ExploRA
2017
Conference article
Restricted
Panel: Context-Dependent Evaluation of Tools for NL RE Tasks: Recall vs. Precision, and beyond
Berry D. M., Cleland-Huang J., Ferrari A., Walid M., John M., Didar Z.
Context and Motivation Natural language processing has been used since the 1980s to construct tools for performing natural language (NL) requirements engineering (RE) tasks. The RE field has often adopted information retrieval (IR) algorithms for use in implementing these NL RE tools. Problem Traditionally, the methods for evaluating an NL RE tool have been inherited from the IR field without adapting them to the requirements of the RE context in which the NL RE tool is used. Principal Ideas This panel discusses the problem and considers the evaluation of tools for a number of NL RE tasks in a number of contexts. Contribution The discussion is aimed at helping the RE field begin to consistently evaluate each of its tools according to the requirements of the tool's task.Source: Requirements Engineering Conference (RE), 2017 IEEE 25th International, pp. 570–573, 04
DOI: 10.1109/re.2017.64
Metrics:
Berry D. M., Cleland-Huang J., Ferrari A., Walid M., John M., Didar Z.
Context and Motivation Natural language processing has been used since the 1980s to construct tools for performing natural language (NL) requirements engineering (RE) tasks. The RE field has often adopted information retrieval (IR) algorithms for use in implementing these NL RE tools. Problem Traditionally, the methods for evaluating an NL RE tool have been inherited from the IR field without adapting them to the requirements of the RE context in which the NL RE tool is used. Principal Ideas This panel discusses the problem and considers the evaluation of tools for a number of NL RE tasks in a number of contexts. Contribution The discussion is aimed at helping the RE field begin to consistently evaluate each of its tools according to the requirements of the tool's task.Source: Requirements Engineering Conference (RE), 2017 IEEE 25th International, pp. 570–573, 04
DOI: 10.1109/re.2017.64
Metrics:
See at:
doi.org | ieeexplore.ieee.org | CNR ExploRA
2018
Journal article
Open Access
Using machine learning to predict soil bulk density on the basis of visual parameters: Tools for in-field and post-field evaluation
Bondi G., Creamer R., Ferrari A., Fenton O., Wall D.
Soil structure is a key factor that supports all soil functions. Extracting intact soil cores and horizon specific samples for determination of soil physical parameters (e.g. bulk density (Bd) or particle size distribution) is a common practice for assessing indicators of soil structure. However, these are often difficult to measure, since they require expensive and time consuming laboratory analyses. Our aim was to provide tools, through the use of machine learning techniques, to estimate the value of Bd based solely on soil visual assessment, observed by operators directly in the field. The first tool was a decision tree model, derived through a decision tree learning algorithm, which allows discrimination among three Bd ranges. The second tool was a linear equation model, derived through a linear regression algorithm, which predicts the numerical value of soil Bd. These tools were validated on a dataset of 471 soil horizons, belonging to 201 soil profile pits surveyed in Ireland. Overall, the decision tree model showed an accuracy of ~ 60%, while the linear equation model has a correlation coefficient of about 0.65 compared to the measured Bd values. For both models, the most relevant property affecting soil structural quality appears to be the humic characteristics of the soil, followed by soil porosity and pedogenic formation. The two tools are parsimonious and can be used by soil surveyors and analysts who need to have an approximate in-situ estimate of the structural quality for various soil functional applications.Source: Geoderma (Amst.) 318 (2018): 137–147. doi:10.1016/j.geoderma.2017.11.035
DOI: 10.1016/j.geoderma.2017.11.035
Metrics:
Bondi G., Creamer R., Ferrari A., Fenton O., Wall D.
Soil structure is a key factor that supports all soil functions. Extracting intact soil cores and horizon specific samples for determination of soil physical parameters (e.g. bulk density (Bd) or particle size distribution) is a common practice for assessing indicators of soil structure. However, these are often difficult to measure, since they require expensive and time consuming laboratory analyses. Our aim was to provide tools, through the use of machine learning techniques, to estimate the value of Bd based solely on soil visual assessment, observed by operators directly in the field. The first tool was a decision tree model, derived through a decision tree learning algorithm, which allows discrimination among three Bd ranges. The second tool was a linear equation model, derived through a linear regression algorithm, which predicts the numerical value of soil Bd. These tools were validated on a dataset of 471 soil horizons, belonging to 201 soil profile pits surveyed in Ireland. Overall, the decision tree model showed an accuracy of ~ 60%, while the linear equation model has a correlation coefficient of about 0.65 compared to the measured Bd values. For both models, the most relevant property affecting soil structural quality appears to be the humic characteristics of the soil, followed by soil porosity and pedogenic formation. The two tools are parsimonious and can be used by soil surveyors and analysts who need to have an approximate in-situ estimate of the structural quality for various soil functional applications.Source: Geoderma (Amst.) 318 (2018): 137–147. doi:10.1016/j.geoderma.2017.11.035
DOI: 10.1016/j.geoderma.2017.11.035
Metrics:
See at:
ISTI Repository | Geoderma | NARCIS | www.sciencedirect.com | CNR ExploRA
2019
Journal article
Open Access
Requirements Engineering (RE) for Social Good RE Cares
Dekhtyar A., Hayes J. H., Hadar I., Combs E., Ferrari A., Gregory S., Horkoff J., Levy M., Nayebi M., Paech B., Payne J., Primrose M., Spoletini P., Clarke S., Brophy C., Amyot D., Maalej W., Ruhe G., Cleland-Huang J., Zowghi D.
As researchers and teachers and practitioners, we "software types" excel at multitasking. This, in part, led us to ask the question: Can one attend a software engineering conference and do something good for society? We found the answer to be a resounding yes. In this article, we present our first experience of running RE Cares, a conference collocated event. This event included a workshop, conference sessions, and a hackathon for developing an application to support emergency field activity for Mutual Aid Alberta, a nonprofit organization coordinating natural disaster responses in the Canadian province.Source: IEEE software 36 (2019). doi:10.1109/MS.2018.2874327
DOI: 10.1109/ms.2018.2874327
Metrics:
Dekhtyar A., Hayes J. H., Hadar I., Combs E., Ferrari A., Gregory S., Horkoff J., Levy M., Nayebi M., Paech B., Payne J., Primrose M., Spoletini P., Clarke S., Brophy C., Amyot D., Maalej W., Ruhe G., Cleland-Huang J., Zowghi D.
As researchers and teachers and practitioners, we "software types" excel at multitasking. This, in part, led us to ask the question: Can one attend a software engineering conference and do something good for society? We found the answer to be a resounding yes. In this article, we present our first experience of running RE Cares, a conference collocated event. This event included a workshop, conference sessions, and a hackathon for developing an application to support emergency field activity for Mutual Aid Alberta, a nonprofit organization coordinating natural disaster responses in the Canadian province.Source: IEEE software 36 (2019). doi:10.1109/MS.2018.2874327
DOI: 10.1109/ms.2018.2874327
Metrics:
See at:
IEEE Software | ISTI Repository | IEEE Software | CNR ExploRA
2019
Journal article
Open Access
Teaching requirements elicitation interviews: an empirical study of learning from mistakes
Bano M., Zowghi D., Ferrari A., Spoletini P., Donati B.
Interviews are the most widely used elicitation technique in requirements engineering (RE). However, conducting a requirements elicitation interview is challenging. The mistakes made in design or conduct of the interviews can create problems in the later stages of requirements analysis. Empirical evidence about effective pedagogical approaches for training novices on conducting requirements elicitation interviews is scarce. In this paper, we present a novel pedagogical approach for training student analysts in the art of elicitation interviews. Our study is conducted in two parts: first, we perform an observational study of interviews performed by novices, and we present a classification of the most common mistakes made; second, we utilize this list of mistakes and monitor the students' progress in three set of interviews to discover the individual areas for improvement. We conducted an empirical study involving role-playing and authentic assessment in two semesters on two different cohorts of students. In the first semester, we had 110 students, teamed up in 28 groups, to conduct three interviews with stakeholders. We qualitatively analysed the data to identify and classify the mistakes made from their first interview only. In the second semester, we had 138 students in 34 groups and we monitored and analysed their progress in all three interviews by utilizing the list of mistakes from the first study. First, we identified 34 unique mistakes classified into seven high-level themes, namely question formulation, question omission, interview order, communication skills, analyst behaviour, customer interaction, teamwork and planning. In the second study, we discovered that the students struggled mostly in the areas of question formulation, question omission and interview order and did not manage to improve their skills throughout the three interviews. Our study presents a novel and repeatable pedagogical design, and our findings extend the body of knowledge aimed at RE education and training by providing an empirically grounded categorization of mistakes made by novices. We offer an analysis of the main pain points in which instructors should pay more attention during their design and training.Source: Requirements engineering (Lond., Print) 24 (2019): 259–289. doi:10.1007/s00766-019-00313-0
DOI: 10.1007/s00766-019-00313-0
Metrics:
Bano M., Zowghi D., Ferrari A., Spoletini P., Donati B.
Interviews are the most widely used elicitation technique in requirements engineering (RE). However, conducting a requirements elicitation interview is challenging. The mistakes made in design or conduct of the interviews can create problems in the later stages of requirements analysis. Empirical evidence about effective pedagogical approaches for training novices on conducting requirements elicitation interviews is scarce. In this paper, we present a novel pedagogical approach for training student analysts in the art of elicitation interviews. Our study is conducted in two parts: first, we perform an observational study of interviews performed by novices, and we present a classification of the most common mistakes made; second, we utilize this list of mistakes and monitor the students' progress in three set of interviews to discover the individual areas for improvement. We conducted an empirical study involving role-playing and authentic assessment in two semesters on two different cohorts of students. In the first semester, we had 110 students, teamed up in 28 groups, to conduct three interviews with stakeholders. We qualitatively analysed the data to identify and classify the mistakes made from their first interview only. In the second semester, we had 138 students in 34 groups and we monitored and analysed their progress in all three interviews by utilizing the list of mistakes from the first study. First, we identified 34 unique mistakes classified into seven high-level themes, namely question formulation, question omission, interview order, communication skills, analyst behaviour, customer interaction, teamwork and planning. In the second study, we discovered that the students struggled mostly in the areas of question formulation, question omission and interview order and did not manage to improve their skills throughout the three interviews. Our study presents a novel and repeatable pedagogical design, and our findings extend the body of knowledge aimed at RE education and training by providing an empirically grounded categorization of mistakes made by novices. We offer an analysis of the main pain points in which instructors should pay more attention during their design and training.Source: Requirements engineering (Lond., Print) 24 (2019): 259–289. doi:10.1007/s00766-019-00313-0
DOI: 10.1007/s00766-019-00313-0
Metrics:
See at:
ISTI Repository | ISTI Repository | Requirements Engineering | link.springer.com | CNR ExploRA
2019
Conference article
Open Access
Learning requirements elicitation interviews with role-playing, self-assessment and peer-review
Ferrari A., Spoletini P., Bano M., Zowghi D.
Interviews are largely used in the practice of requirements elicitation. Nevertheless, performing an effective interview often depends on soft-skills, and on knowledge acquired through experience. When it comes to requirements engineering education and training (REET), limited resources and few well-founded pedagogical approaches are available to allow students to acquire and improve their skills as interviewers. This paper presents a novel pedagogical approach that combines role-playing, peer-review and self-assessment to enable students to reflect on their mistakes, and improve their interview skills. We evaluate the approach through a controlled quasi-experiment. The study shows that the approach significantly reduces the amount of mistakes made by the students. Feedback from the participants confirms the usefulness and easiness of the proposed training. This work contributes to the body of knowledge of REET with an empirically evaluated method for teaching inter-views. Furthermore, we share the pedagogical material used, to enable other educators to apply and possibly tailor the approach.Source: IEEE Requirements Engineering Conference, pp. 28–39, Jeju Island, Corea, 23-27/09/2019
DOI: 10.1109/re.2019.00015
Metrics:
Ferrari A., Spoletini P., Bano M., Zowghi D.
Interviews are largely used in the practice of requirements elicitation. Nevertheless, performing an effective interview often depends on soft-skills, and on knowledge acquired through experience. When it comes to requirements engineering education and training (REET), limited resources and few well-founded pedagogical approaches are available to allow students to acquire and improve their skills as interviewers. This paper presents a novel pedagogical approach that combines role-playing, peer-review and self-assessment to enable students to reflect on their mistakes, and improve their interview skills. We evaluate the approach through a controlled quasi-experiment. The study shows that the approach significantly reduces the amount of mistakes made by the students. Feedback from the participants confirms the usefulness and easiness of the proposed training. This work contributes to the body of knowledge of REET with an empirically evaluated method for teaching inter-views. Furthermore, we share the pedagogical material used, to enable other educators to apply and possibly tailor the approach.Source: IEEE Requirements Engineering Conference, pp. 28–39, Jeju Island, Corea, 23-27/09/2019
DOI: 10.1109/re.2019.00015
Metrics:
See at:
ISTI Repository | doi.org | ieeexplore.ieee.org | CNR ExploRA
2019
Contribution to book
Open Access
Ambiguity in Requirements Engineering: Towards a Unifying Framework
Gervasi V., Ferrari A., Zowghi D., Spoletini P.
A long stream of research in RE has been devoted to analyzing the occurrences and consequences of ambiguity in requirements documents. Ambiguity often occurs in documents, most often in natural language (NL) ones, but occasionally also in formal specifications, be it because of abstraction, or of imprecise designation of which real-world entities are denotated by certain expressions. In many of those studies, ambiguity has been considered a defect to be avoided. In this paper, we investigate the nature of ambiguity, and advocate that the simplistic view of ambiguity as merely a defect in the document does not do justice to the complexity of this phenomenon. We offer a more extensive analysis, based on the multiple linguistic sources of ambiguity, and present a list of real-world cases, both in written matter and in oral interviews, that we analyze based on our framework. We hope that a better understanding of the phenomenon can help in the analysis of practical experiences and in the design of more effective methods to detect, mark and handle ambiguity.Source: From Software Engineering to Formal Methods and Tools, and Back Essays Dedicated to Stefania Gnesi on the Occasion of Her 65th Birthday, edited by ter Beek M.H.; Fantechi A.; Semini L., pp. 191–210, 2019
DOI: 10.1007/978-3-030-30985-5_12
Metrics:
Gervasi V., Ferrari A., Zowghi D., Spoletini P.
A long stream of research in RE has been devoted to analyzing the occurrences and consequences of ambiguity in requirements documents. Ambiguity often occurs in documents, most often in natural language (NL) ones, but occasionally also in formal specifications, be it because of abstraction, or of imprecise designation of which real-world entities are denotated by certain expressions. In many of those studies, ambiguity has been considered a defect to be avoided. In this paper, we investigate the nature of ambiguity, and advocate that the simplistic view of ambiguity as merely a defect in the document does not do justice to the complexity of this phenomenon. We offer a more extensive analysis, based on the multiple linguistic sources of ambiguity, and present a list of real-world cases, both in written matter and in oral interviews, that we analyze based on our framework. We hope that a better understanding of the phenomenon can help in the analysis of practical experiences and in the design of more effective methods to detect, mark and handle ambiguity.Source: From Software Engineering to Formal Methods and Tools, and Back Essays Dedicated to Stefania Gnesi on the Occasion of Her 65th Birthday, edited by ter Beek M.H.; Fantechi A.; Semini L., pp. 191–210, 2019
DOI: 10.1007/978-3-030-30985-5_12
Metrics:
See at:
arpi.unipi.it | ISTI Repository | doi.org | link.springer.com | CNR ExploRA
2018
Conference article
Open Access
Natural Language Requirements Processing: from Research to Practice
Ferrari A.
Automated manipulation of natural language requirements, for classification, tracing, defect detection, information extraction, and other tasks, has been pursued by requirements engineering (RE) researchers for more than two decades. Recent technological advancements in natural language processing (NLP) have made it possible to apply this research more widely within industrial settings. This technical briefing targets researchers and practitioners, and aims to give an overview of what NLP can do today for RE problems, and what could do if specific research challenges, also emerging from practical experiences, are addressed. The talk will: survey current research on applications of NLP to RE problems; present representative industrially-ready techniques, with a focus on defect detection and information extraction problems; present enabling technologies in NLP that can play a role in RE research, including distributional semantics representations; discuss criteria for evaluation of NLP techniques in the RE context; outline the main challenges for a systematic application of the techniques in industry. The crosscutting topics that will permeate the talk are the need for domain adaptation, and the essential role of the human-in-the-loop.Source: International Conference on Software Engineering, pp. 536–537, 27/05/2018
DOI: 10.1145/3183440.3183467
Metrics:
Ferrari A.
Automated manipulation of natural language requirements, for classification, tracing, defect detection, information extraction, and other tasks, has been pursued by requirements engineering (RE) researchers for more than two decades. Recent technological advancements in natural language processing (NLP) have made it possible to apply this research more widely within industrial settings. This technical briefing targets researchers and practitioners, and aims to give an overview of what NLP can do today for RE problems, and what could do if specific research challenges, also emerging from practical experiences, are addressed. The talk will: survey current research on applications of NLP to RE problems; present representative industrially-ready techniques, with a focus on defect detection and information extraction problems; present enabling technologies in NLP that can play a role in RE research, including distributional semantics representations; discuss criteria for evaluation of NLP techniques in the RE context; outline the main challenges for a systematic application of the techniques in industry. The crosscutting topics that will permeate the talk are the need for domain adaptation, and the essential role of the human-in-the-loop.Source: International Conference on Software Engineering, pp. 536–537, 27/05/2018
DOI: 10.1145/3183440.3183467
Metrics:
See at:
ISTI Repository | dl.acm.org | doi.org | CNR ExploRA
2018
Conference article
Open Access
CaRE: A refinement calculus for requirements engineering based on argumentation semantics
Elrakaiby Y., Ferrari A., Mylopoulos J.
The requirements problem consists of transforming stakeholder requirements - however informal, ambiguous, conflicting, unattainable, imprecise and incomplete - into a consistent, complete and realizable specification through a systematic process. We propose a refinement calculus for requirements engineering (CaRE) for solving this problem, which takes into account the typically dialectic nature of requirements activities. The calculus casts the requirement problem as an iterative argument between stakeholders and requirements engineers, where posited requirements are attacked for being ambiguous, incomplete, etc. and refined into new requirements that address the defect pointed out by the attack. Refinements are carried out by operators provided by CaRE that refine (e.g., strengthen, weaken, decompose) existing requirements, to build a refinement graph. The semantics of the operators is provided by means of argumentation theory. Examples are given to illustrate the elements of our proposal.Source: Requirements Engineering Conference, pp. 364–369, 20/08/2018
DOI: 10.1109/re.2018.00-24
Metrics:
Elrakaiby Y., Ferrari A., Mylopoulos J.
The requirements problem consists of transforming stakeholder requirements - however informal, ambiguous, conflicting, unattainable, imprecise and incomplete - into a consistent, complete and realizable specification through a systematic process. We propose a refinement calculus for requirements engineering (CaRE) for solving this problem, which takes into account the typically dialectic nature of requirements activities. The calculus casts the requirement problem as an iterative argument between stakeholders and requirements engineers, where posited requirements are attacked for being ambiguous, incomplete, etc. and refined into new requirements that address the defect pointed out by the attack. Refinements are carried out by operators provided by CaRE that refine (e.g., strengthen, weaken, decompose) existing requirements, to build a refinement graph. The semantics of the operators is provided by means of argumentation theory. Examples are given to illustrate the elements of our proposal.Source: Requirements Engineering Conference, pp. 364–369, 20/08/2018
DOI: 10.1109/re.2018.00-24
Metrics:
See at:
ISTI Repository | ulir.ul.ie | doi.org | ieeexplore.ieee.org | CNR ExploRA
2018
Conference article
Open Access
Learning from mistakes: An empirical study of elicitation interviews performed by novices
Bano M., Zowghi D., Ferrari A., Spoletini P., Donati B.
Interviews are the most widely used elicitation technique in requirements engineering. However, conducting effective requirements elicitation interviews is challenging, due to the combination of technical and soft skills that requirements analysts often acquire after a long period of professional practice. Empirical evidence about training the novices on conducting effective requirements elicitation interviews is scarce. [Objectives] We present a list of most common mistakes that novices make in requirements elicitation interviews. The objective is to assist the educators in teaching interviewing skills to student analysts. [Re-search Method] We conducted an empirical study involving role-playing and authentic assessment with 110 students, teamed up in 28 groups, to conduct interviews with a customer. One re-searcher made observation notes during the interview while two researchers reviewed the recordings. We qualitatively analyzed the data to identify the themes and classify the mistakes. [Results and conclusion] We identified 34 unique mistakes classified into 7 high level themes. We also give examples of the mistakes made by the novices in each theme, to assist the educationists and trainers. Our research design is a novel combination of well-known pedagogical approaches described in sufficient details to make it re-peatable for future requirements engineering education and training research.Source: 26th IEEE International Requirements Engineering Conference RE 2018, pp. 182–193, Banff, AB, Canada, 20-24 August, 2018
DOI: 10.1109/re.2018.00027
Metrics:
Bano M., Zowghi D., Ferrari A., Spoletini P., Donati B.
Interviews are the most widely used elicitation technique in requirements engineering. However, conducting effective requirements elicitation interviews is challenging, due to the combination of technical and soft skills that requirements analysts often acquire after a long period of professional practice. Empirical evidence about training the novices on conducting effective requirements elicitation interviews is scarce. [Objectives] We present a list of most common mistakes that novices make in requirements elicitation interviews. The objective is to assist the educators in teaching interviewing skills to student analysts. [Re-search Method] We conducted an empirical study involving role-playing and authentic assessment with 110 students, teamed up in 28 groups, to conduct interviews with a customer. One re-searcher made observation notes during the interview while two researchers reviewed the recordings. We qualitatively analyzed the data to identify the themes and classify the mistakes. [Results and conclusion] We identified 34 unique mistakes classified into 7 high level themes. We also give examples of the mistakes made by the novices in each theme, to assist the educationists and trainers. Our research design is a novel combination of well-known pedagogical approaches described in sufficient details to make it re-peatable for future requirements engineering education and training research.Source: 26th IEEE International Requirements Engineering Conference RE 2018, pp. 182–193, Banff, AB, Canada, 20-24 August, 2018
DOI: 10.1109/re.2018.00027
Metrics:
See at:
ISTI Repository | opus.lib.uts.edu.au | doi.org | ieeexplore.ieee.org | CNR ExploRA
2020
Conference article
Open Access
Inspectors academy: pedagogical design for requirements inspection training
Bano M., Zowghi D., Ferrari A., Spoletini P.
The core aim of requirements inspection is to ensure the high quality of already elicited requirements in the Software Requirements Specification. Teaching requirements inspection to novices is challenging, as inspecting requirements needs several skills as well as knowledge of the product and process that is hard to achieve in a classroom environment. Published studies about pedagogical design specifically for teaching requirements inspection are scarce. Our objective is to present the design and evaluation of a postgraduate course for requirements inspection training. We conducted an empirical study with 138 postgraduate students, teamed up in 34 groups to conduct requirements inspection. We performed qualitative analysis on the data collected from students' reflection reports to assess the effects of the pedagogical design in terms of benefits and challenges. We also quantitatively analyze the correlation between the students' performance in conducting inspections and their ability of writing specifications. From the analysis of students' reflections, several themes emerged such as their difficulty of working with limited information, but also revealed the benefits of learning teamwork and writing good requirements. This qualitative analysis also provides recommendations for improving the related activities. The results revealed a moderate positive correlation between the performance in writing specification and inspection.Source: RE 2020 - 28th IEEE Requirements Engineering Conference, pp. 215–226, Zurich, Switzerland, 31/08/2020-04/09/2020
DOI: 10.1109/re48521.2020.00032
Metrics:
Bano M., Zowghi D., Ferrari A., Spoletini P.
The core aim of requirements inspection is to ensure the high quality of already elicited requirements in the Software Requirements Specification. Teaching requirements inspection to novices is challenging, as inspecting requirements needs several skills as well as knowledge of the product and process that is hard to achieve in a classroom environment. Published studies about pedagogical design specifically for teaching requirements inspection are scarce. Our objective is to present the design and evaluation of a postgraduate course for requirements inspection training. We conducted an empirical study with 138 postgraduate students, teamed up in 34 groups to conduct requirements inspection. We performed qualitative analysis on the data collected from students' reflection reports to assess the effects of the pedagogical design in terms of benefits and challenges. We also quantitatively analyze the correlation between the students' performance in conducting inspections and their ability of writing specifications. From the analysis of students' reflections, several themes emerged such as their difficulty of working with limited information, but also revealed the benefits of learning teamwork and writing good requirements. This qualitative analysis also provides recommendations for improving the related activities. The results revealed a moderate positive correlation between the performance in writing specification and inspection.Source: RE 2020 - 28th IEEE Requirements Engineering Conference, pp. 215–226, Zurich, Switzerland, 31/08/2020-04/09/2020
DOI: 10.1109/re48521.2020.00032
Metrics:
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ISTI Repository | ISTI Repository | doi.org | ieeexplore.ieee.org | CNR ExploRA
2020
Conference article
Open Access
The Way it Makes you Feel Predicting Users' Engagement during Interviews with Biofeedback and Supervised Learning
Girardi D., Ferrari A., Novielli N., Spoletini P., Fucci D., Huichapa T.
Capturing users' engagement is crucial for gathering feedback about the features of a software product. In a market-driven context, current approaches to collect and analyze users' feedback are based on techniques leveraging information extracted from product reviews and social media. These approaches are hardly applicable in bespoke software development, or in contexts in which one needs to gather information from specific users. In such cases, companies need to resort to face-To-face interviews to get feedback on their products. In this paper, we propose to utilize biofeedback to complement interviews with information about the engagement of the user on the discussed features and topics. We evaluate our approach by interviewing users while gathering their biometric data using an Empatica E4 wristband. Our results show that we can predict users' engagement by training supervised machine learning algorithms on the biometric data. The results of our work can be used to facilitate the prioritization of product features and to guide the interview based on users' engagement.Source: IEEE Requirements Engineering Conference (RE), pp. 32–43, 31/08/2020-04/09/2020
DOI: 10.1109/re48521.2020.00016
Metrics:
Girardi D., Ferrari A., Novielli N., Spoletini P., Fucci D., Huichapa T.
Capturing users' engagement is crucial for gathering feedback about the features of a software product. In a market-driven context, current approaches to collect and analyze users' feedback are based on techniques leveraging information extracted from product reviews and social media. These approaches are hardly applicable in bespoke software development, or in contexts in which one needs to gather information from specific users. In such cases, companies need to resort to face-To-face interviews to get feedback on their products. In this paper, we propose to utilize biofeedback to complement interviews with information about the engagement of the user on the discussed features and topics. We evaluate our approach by interviewing users while gathering their biometric data using an Empatica E4 wristband. Our results show that we can predict users' engagement by training supervised machine learning algorithms on the biometric data. The results of our work can be used to facilitate the prioritization of product features and to guide the interview based on users' engagement.Source: IEEE Requirements Engineering Conference (RE), pp. 32–43, 31/08/2020-04/09/2020
DOI: 10.1109/re48521.2020.00016
Metrics:
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ISTI Repository | doi.org | ieeexplore.ieee.org | CNR ExploRA
2020
Journal article
Open Access
SaPeer and ReverseSaPeer: teaching requirements elicitation interviews with role-playing and role reversal
Ferrari A., Spoletini P., Bano M., Zowghi D.
Among the variety of the available requirements elicitation techniques, interviews are the most commonly used. Performing effective interviews is challenging, especially for students and novice analysts, since interviews' success depends largely on soft skills and experience. Despite their diffusion and their challenging nature, when it comes to requirements engineering education and training (REET), limited resources and few well-founded pedagogical approaches are available to allow students to acquire and improve their skills as interviewers. To overcome this limitation, this paper presents two pedagogical approaches, namelySaPeerandReverseSaPeer.SaPeeruses role-playing, peer review and self-assessment to enable students to experience first-hand the difficulties related to the interviewing process, reflect on their mistakes, and improve their interview skills by practice and analysis.ReverseSaPeerbuilds on the first approach and includes a role reversal activity in which participants play the role of a customer interviewed by a competent interviewer. We evaluate the effectiveness ofSaPeerthrough a controlled quasi-experiment, which shows that the proposed approach significantly reduces the amount of mistakes made by the participants and that it is perceived as useful and easy by the participants.ReverseSaPeerand the impact of role reversal are analyzed through a thematic analysis of the participant's reflections. The analysis shows that not only the students perceive the analysis as beneficial, but also that they have emotional involvement in learning. This work contributes to the body of knowledge of REET with two methods, quantitative and qualitative evaluated, respectively. Furthermore, we share the pedagogical material used, to enable other educators to apply and possibly tailor the approach.Source: Requirements engineering (Lond., Print) 25 (2020): 417–438. doi:10.1007/s00766-020-00334-0
DOI: 10.1007/s00766-020-00334-0
Metrics:
Ferrari A., Spoletini P., Bano M., Zowghi D.
Among the variety of the available requirements elicitation techniques, interviews are the most commonly used. Performing effective interviews is challenging, especially for students and novice analysts, since interviews' success depends largely on soft skills and experience. Despite their diffusion and their challenging nature, when it comes to requirements engineering education and training (REET), limited resources and few well-founded pedagogical approaches are available to allow students to acquire and improve their skills as interviewers. To overcome this limitation, this paper presents two pedagogical approaches, namelySaPeerandReverseSaPeer.SaPeeruses role-playing, peer review and self-assessment to enable students to experience first-hand the difficulties related to the interviewing process, reflect on their mistakes, and improve their interview skills by practice and analysis.ReverseSaPeerbuilds on the first approach and includes a role reversal activity in which participants play the role of a customer interviewed by a competent interviewer. We evaluate the effectiveness ofSaPeerthrough a controlled quasi-experiment, which shows that the proposed approach significantly reduces the amount of mistakes made by the participants and that it is perceived as useful and easy by the participants.ReverseSaPeerand the impact of role reversal are analyzed through a thematic analysis of the participant's reflections. The analysis shows that not only the students perceive the analysis as beneficial, but also that they have emotional involvement in learning. This work contributes to the body of knowledge of REET with two methods, quantitative and qualitative evaluated, respectively. Furthermore, we share the pedagogical material used, to enable other educators to apply and possibly tailor the approach.Source: Requirements engineering (Lond., Print) 25 (2020): 417–438. doi:10.1007/s00766-020-00334-0
DOI: 10.1007/s00766-020-00334-0
Metrics:
See at:
ISTI Repository | Requirements Engineering | link.springer.com | CNR ExploRA
2018
Journal article
Open Access
Natural language processing for requirements engineering: the best is yet to come
Dalpiaz F., Ferrari A., Franch X., Palomares C.
As part of the growing interest in natural language processing for requirements engineering (RE), RE researchers, computational linguists, and industry practitioners met at the First Workshop on Natural Language Processing for Requirements Engineering (NLP4RE 18). This article summarizes the workshop and presents an overview of the discussion held on the field's future. This article is part of a theme issue on software engineering's 50th anniversary.Source: IEEE software 35 (2018): 115–119. doi:10.1109/MS.2018.3571242
DOI: 10.1109/ms.2018.3571242
Project(s): OPENREQ
Metrics:
Dalpiaz F., Ferrari A., Franch X., Palomares C.
As part of the growing interest in natural language processing for requirements engineering (RE), RE researchers, computational linguists, and industry practitioners met at the First Workshop on Natural Language Processing for Requirements Engineering (NLP4RE 18). This article summarizes the workshop and presents an overview of the discussion held on the field's future. This article is part of a theme issue on software engineering's 50th anniversary.Source: IEEE software 35 (2018): 115–119. doi:10.1109/MS.2018.3571242
DOI: 10.1109/ms.2018.3571242
Project(s): OPENREQ
Metrics:
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Recolector de Ciencia Abierta, RECOLECTA | ISTI Repository | IEEE Software | IEEE Software | ieeexplore.ieee.org | CNR ExploRA
2020
Conference article
Open Access
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 iteratively refines them into a specification that is consistent, complete, valid and unambiguous. We propose a novel RE process in the form of a calculus where the process is envisioned as an iterative application of refinement operators, with each operator removing a defect from the current requirements. Our proposal is motivated by the dialectic and incremental nature of RE activities. The calculus, which we call CaRE, casts the RE problem as an iterative argument between stakeholders, who point out defects (ambiguity, incompleteness, etc.) of existing requirements, and then propose refinements to address those defects, thus leading to the construction of a refinement graph. This graph is then a conceptual model of an RE process enactment. The semantics of these models is provided by Argumentation Theory, where a requirement may be attacked for having a defect, which in turn may be eliminated by a refinement.Source: ER 2020 - International Conference on Conceptual Modeling, pp. 3–18, Vienna, Austria, November 03-06, 2020
DOI: 10.1007/978-3-030-62522-1_1
Metrics:
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 iteratively refines them into a specification that is consistent, complete, valid and unambiguous. We propose a novel RE process in the form of a calculus where the process is envisioned as an iterative application of refinement operators, with each operator removing a defect from the current requirements. Our proposal is motivated by the dialectic and incremental nature of RE activities. The calculus, which we call CaRE, casts the RE problem as an iterative argument between stakeholders, who point out defects (ambiguity, incompleteness, etc.) of existing requirements, and then propose refinements to address those defects, thus leading to the construction of a refinement graph. This graph is then a conceptual model of an RE process enactment. The semantics of these models is provided by Argumentation Theory, where a requirement may be attacked for having a defect, which in turn may be eliminated by a refinement.Source: ER 2020 - International Conference on Conceptual Modeling, pp. 3–18, Vienna, Austria, November 03-06, 2020
DOI: 10.1007/978-3-030-62522-1_1
Metrics:
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ISTI Repository | doi.org | link.springer.com | CNR ExploRA
2020
Contribution to conference
Open Access
7th International Workshop on Artificial Intelligence and Requirements Engineering (AIRE'20)
Bencomo N., Ferrari A., Aydemir F. B., Rahimi M.
Source: 7th International Workshop on Artificial Intelligence and Requirements Engineering (AIRE'20), Evento online, 01/09/2020
DOI: 10.1109/aire51212.2020.00005
Metrics:
Bencomo N., Ferrari A., Aydemir F. B., Rahimi M.
Source: 7th International Workshop on Artificial Intelligence and Requirements Engineering (AIRE'20), Evento online, 01/09/2020
DOI: 10.1109/aire51212.2020.00005
Metrics:
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ieeexplore.ieee.org | ieeexplore.ieee.org | ISTI Repository | doi.org | CNR ExploRA
2019
Contribution to book
Open Access
2nd workshop on natural language processing for requirements engineering (NLP4RE'19) and NLP tool showcase
Dalpiaz F., Ferrari A., Franch X., Gregory S., Houdek F., Palomares C.
Preface to the 2nd edition of the NLP4RE workshop.Source: REFSQ-2019 Workshops, Doctoral Symposium, Live Studies Track, and Poster Track, edited by Spoletini P. et al., 2019
Dalpiaz F., Ferrari A., Franch X., Gregory S., Houdek F., Palomares C.
Preface to the 2nd edition of the NLP4RE workshop.Source: REFSQ-2019 Workshops, Doctoral Symposium, Live Studies Track, and Poster Track, edited by Spoletini P. et al., 2019
See at:
ceur-ws.org | ISTI Repository | CNR ExploRA