2015
Report
Open Access
LEARN PAD - Quality assessment strategies for contents
Ferrari A., Witschel H. F., Spagnolo G. O., Gnesi S.
In this deliverable we identify the quality assessment strategies for the natural language content as- sociated to the Business Process Models (BP Models), within the Learn PAd project. The deliverable presents an in-depth domain analysis, including literature review, interviews with public administra- tion (PA) stakeholders, and questionnaires submitted to PA stakeholders. Moreover, it defines a set of guidelines for editing natural language content in Learn PAd, and a quality model with associated rule-based and algorithmic strategies for computing the quality of such content. An experimental evaluation is presented concerning the potential usage of machine-learning techniques as a complementary tool for quality evaluation. The deliverable also introduces some technical details that pave the basis to successively create the content analysis component of the Learn PAd platform.Source: Project report, LEARN PAD, Deliverable D4.2, 2015
Project(s): LEARN PAD
Ferrari A., Witschel H. F., Spagnolo G. O., Gnesi S.
In this deliverable we identify the quality assessment strategies for the natural language content as- sociated to the Business Process Models (BP Models), within the Learn PAd project. The deliverable presents an in-depth domain analysis, including literature review, interviews with public administra- tion (PA) stakeholders, and questionnaires submitted to PA stakeholders. Moreover, it defines a set of guidelines for editing natural language content in Learn PAd, and a quality model with associated rule-based and algorithmic strategies for computing the quality of such content. An experimental evaluation is presented concerning the potential usage of machine-learning techniques as a complementary tool for quality evaluation. The deliverable also introduces some technical details that pave the basis to successively create the content analysis component of the Learn PAd platform.Source: Project report, LEARN PAD, Deliverable D4.2, 2015
Project(s): LEARN PAD
See at:
ISTI Repository 
| CNR ExploRA
2015
Report
Open Access
LEARN PAD - Formal verification of business processes
Re B., Polini A., Gnesi S., Ferrari A., Fornari F., Spagnolo G. O., Corradini F.
In this deliverable we identified the quality assessment strategies for Business Process models related to the Learn PAd project. This is discussed considering different roles impacting on the platform and strategies to be implemented for its maintaining. After an in-depth analysis of the literature this deliverable (i) reports guidelines to model Business Processes in such a way that resulting model are understandable and (ii) discusses Business Process correctness criteria. Such quality check impacts on the learnability of the Business Process for Public Administrations. The deliverable also introduces some technical details that paves the basis to successively create the Learn PAd platform model verification component.Source: Project report, LEARN PAD, Deliverable D4.1, 2015
Project(s): LEARN PAD
Re B., Polini A., Gnesi S., Ferrari A., Fornari F., Spagnolo G. O., Corradini F.
In this deliverable we identified the quality assessment strategies for Business Process models related to the Learn PAd project. This is discussed considering different roles impacting on the platform and strategies to be implemented for its maintaining. After an in-depth analysis of the literature this deliverable (i) reports guidelines to model Business Processes in such a way that resulting model are understandable and (ii) discusses Business Process correctness criteria. Such quality check impacts on the learnability of the Business Process for Public Administrations. The deliverable also introduces some technical details that paves the basis to successively create the Learn PAd platform model verification component.Source: Project report, LEARN PAD, Deliverable D4.1, 2015
Project(s): LEARN PAD
See at:
ISTI Repository | CNR ExploRA
2015
Report
Open Access
Quality assessment strategy: applying business process understandability guidelines for learning
Corradini F., Ferrrari A., Fornari F., Gnesi S., Polini A., Re B., Spagnolo G. O.
Modelling using graphical notations permits to improve communications among stakeholders. The usage and composition of the notation elements can greatly impact on the understandability of the dened models. This is an important factor to consider in complex organizations where activities are performed by the collaboration of many stakeholders. Understandability becomes even more important when models are also used to structure learning activities. In this technical we report our experience on the usage of BPMN for documenting and learning business process activities.Source: ISTI Technical reports, 2015
Project(s): LEARN PAD
Corradini F., Ferrrari A., Fornari F., Gnesi S., Polini A., Re B., Spagnolo G. O.
Modelling using graphical notations permits to improve communications among stakeholders. The usage and composition of the notation elements can greatly impact on the understandability of the dened models. This is an important factor to consider in complex organizations where activities are performed by the collaboration of many stakeholders. Understandability becomes even more important when models are also used to structure learning activities. In this technical we report our experience on the usage of BPMN for documenting and learning business process activities.Source: ISTI Technical reports, 2015
Project(s): LEARN PAD
See at:
ISTI Repository | CNR ExploRA
2015
Conference article
Open Access
CMT and FDE: tools to bridge the gap between natural language documents and feature diagrams
Ferrari A., Spagnolo G. O., Gnesi S., Dell'Orletta F.
A business subject who wishes to enter an established technological market is required to accurately analyse the features of the products of the different competitors. Such features are normally accessible through natural language (NL) brochures, or NL Web pages, which describe the products to potential customers. Building a feature model that hierarchically summarises the different features available in competing products can bring relevant benefits in market analysis. A company can easily visualise existing features, and reason about aspects that are not covered by the available solutions. However, designing a feature model starting from publicly available documents of existing products is a time consuming and error-prone task. In this paper, we present two tools, namely Commonality Mining Tool (CMT) and Feature Diagram Editor (FDE), which can jointly support the feature model definition process. CMT allows mining common and variant features from NL descriptions of existing products, by leveraging a natural language processing (NLP) approach based on contrastive analysis, which allows identifying domain-relevant terms from NL documents. FDE takes the commonalities and variabilities extracted by CMT, and renders them in a visual form. Moreover, FDE allows the graphical design and refinement of the final feature model, by means of an intuitive GUISource: 19th International Conference on Software Product Line, pp. 402–410, Nashville, TN, USA, 20-24/07/2015
DOI: 10.1145/2791060.2791117
Project(s): LEARN PAD
Metrics:
Ferrari A., Spagnolo G. O., Gnesi S., Dell'Orletta F.
A business subject who wishes to enter an established technological market is required to accurately analyse the features of the products of the different competitors. Such features are normally accessible through natural language (NL) brochures, or NL Web pages, which describe the products to potential customers. Building a feature model that hierarchically summarises the different features available in competing products can bring relevant benefits in market analysis. A company can easily visualise existing features, and reason about aspects that are not covered by the available solutions. However, designing a feature model starting from publicly available documents of existing products is a time consuming and error-prone task. In this paper, we present two tools, namely Commonality Mining Tool (CMT) and Feature Diagram Editor (FDE), which can jointly support the feature model definition process. CMT allows mining common and variant features from NL descriptions of existing products, by leveraging a natural language processing (NLP) approach based on contrastive analysis, which allows identifying domain-relevant terms from NL documents. FDE takes the commonalities and variabilities extracted by CMT, and renders them in a visual form. Moreover, FDE allows the graphical design and refinement of the final feature model, by means of an intuitive GUISource: 19th International Conference on Software Product Line, pp. 402–410, Nashville, TN, USA, 20-24/07/2015
DOI: 10.1145/2791060.2791117
Project(s): LEARN PAD
Metrics:
See at:
ISTI Repository | dl.acm.org 
| doi.org | CNR ExploRA
2015
Conference article
Open Access
Automated service selection using natural language processing
Bano M., Ferrari A., Zowghi D., Gervasi V., Gnesi S.
With the huge number of services that are available online, requirements analysts face a paradox of choice (i.e., choice overload) when they have to select the most suitable service that satisfies a set of customer requirements. Both service descriptions and requirements are often expressed in natural language (NL), and natural language pro- cessing (NLP) tools that can match requirements and service descrip- tions, while filtering out irrelevant options, might alleviate the problem of choice overload faced by analysts. In this paper, we propose a NLP approach based on Knowledge Graphs that automates the process of service selection by ranking the service descriptions depending on their NL similarity with the requirements. To evaluate the approach, we have performed an experiment with 28 customer requirements and 91 service descriptions, previously ranked by a human assessor. We selected the top- 15 services, which were ranked with the proposed approach, and found 53% similar results with respect to top-15 services of the manual ranking. The same task, performed with the traditional cosine similarity ranking, produces only 13% similar results. The outcomes of our experiment are promising, and new insights have also emerged for further improvement of the proposed technique.Source: APRES 2015 - Requirements Engineering in the Big Data Era. Second Asia Pacific Symposium, pp. 3–17, Wuhan, China, 18-20 October 2015
DOI: 10.1007/978-3-662-48634-4_1
Metrics:
Bano M., Ferrari A., Zowghi D., Gervasi V., Gnesi S.
With the huge number of services that are available online, requirements analysts face a paradox of choice (i.e., choice overload) when they have to select the most suitable service that satisfies a set of customer requirements. Both service descriptions and requirements are often expressed in natural language (NL), and natural language pro- cessing (NLP) tools that can match requirements and service descrip- tions, while filtering out irrelevant options, might alleviate the problem of choice overload faced by analysts. In this paper, we propose a NLP approach based on Knowledge Graphs that automates the process of service selection by ranking the service descriptions depending on their NL similarity with the requirements. To evaluate the approach, we have performed an experiment with 28 customer requirements and 91 service descriptions, previously ranked by a human assessor. We selected the top- 15 services, which were ranked with the proposed approach, and found 53% similar results with respect to top-15 services of the manual ranking. The same task, performed with the traditional cosine similarity ranking, produces only 13% similar results. The outcomes of our experiment are promising, and new insights have also emerged for further improvement of the proposed technique.Source: APRES 2015 - Requirements Engineering in the Big Data Era. Second Asia Pacific Symposium, pp. 3–17, Wuhan, China, 18-20 October 2015
DOI: 10.1007/978-3-662-48634-4_1
Metrics:
See at:
ISTI Repository | doi.org | link.springer.com | CNR ExploRA
2015
Conference article
Restricted
Ambiguity as a resource to disclose tacit knowledge
Ferrari A., Spoletini P., Gnesi S.
Interviews are the most common and effective means to perform requirements elicitation and support knowledge transfer between a customer and a requirements analyst. Ambiguity in communication is often perceived as a major obstacle for knowledge transfer, which could lead to unclear and incomplete requirements documents. In this paper, we analyse the role of ambiguity in requirements elicitation interviews. To this end, we have performed a set of customer-analyst interviews to observe how ambiguity occurs during requirements elicitation. From this direct experience, we have observed that ambiguity is a multi-dimensional cognitive phenomenon with a dominant pragmatic facet, and we have defined a phenomenological framework to describe the different types of ambiguity in interviews. We have also discovered that, rather than an obstacle, the occurrence of an ambiguity is often a resource for discovering tacit knowledge. Starting from this observation, we have envisioned the further steps needed in the research to exploit these findings.Source: RE 2015 - IEEE 23rd International Requirements Engineering Conference, pp. 26–35, Ottawa, ON, Canada, 24-28 August 2015
DOI: 10.1109/re.2015.7320405
Metrics:
Ferrari A., Spoletini P., Gnesi S.
Interviews are the most common and effective means to perform requirements elicitation and support knowledge transfer between a customer and a requirements analyst. Ambiguity in communication is often perceived as a major obstacle for knowledge transfer, which could lead to unclear and incomplete requirements documents. In this paper, we analyse the role of ambiguity in requirements elicitation interviews. To this end, we have performed a set of customer-analyst interviews to observe how ambiguity occurs during requirements elicitation. From this direct experience, we have observed that ambiguity is a multi-dimensional cognitive phenomenon with a dominant pragmatic facet, and we have defined a phenomenological framework to describe the different types of ambiguity in interviews. We have also discovered that, rather than an obstacle, the occurrence of an ambiguity is often a resource for discovering tacit knowledge. Starting from this observation, we have envisioned the further steps needed in the research to exploit these findings.Source: RE 2015 - IEEE 23rd International Requirements Engineering Conference, pp. 26–35, Ottawa, ON, Canada, 24-28 August 2015
DOI: 10.1109/re.2015.7320405
Metrics:
See at:
doi.org | ieeexplore.ieee.org | CNR ExploRA
2015
Report
Open Access
LEARN PAD - Platform prototype early validation results
Re B., Polini A., Corradini F., Fornari F., Sergiacomi A., Amici C., Balducci A., Carota S., Giorgio L., De Simone S., Ferrari A., Gnesi S., Spagnolo G. O., Efendioglu N., Bertolino A.
The main goal of this deliverable is to early collect end-users feedback about the platform imple- mented functionalities for the sake of the Learn PAd consortium. End-users needs and expectations are driving forces of the Learn PAd project, that is why a validation has been carried out to ensure that the early version of the Learn PAd platform properly addresses them. The early validation was carried out considering the running instance of the Learn PAd platform available (since 06 November 2015) at the address: http://testbed.learnpad.eu/. A group of users sampled from both the project demonstrators tested the Learn PAd platform and provided us with feedback and comments to improve it. Results from such validation are reported in the first part of this deliverable. Moreover, even if not explicitly requested in the DoW, a further validation was also done to check the goodness of BPMN modelling understandability guidelines that we defined in WP4. This further validation involved a questionnaire and a focus group with the aim to guarantee that the defined BP modelling understandability guidelines actually contribute to improve BP model understandability. In the second part of this deliverable we report in detail the results of the modelling guidelines valida- tion. From the guidelines validation, we can assert that models designed following BPMN modelling understandability guidelines indeed result to be better understandable than the ones generated by not following the guidelines. In fact, for such reason the BP models used in the deployed running instance of the Learn PAd platform involved in the user early validation are those conforming to the guidelines.Source: Project report, LEARN PAD, Deliverable D8.2, 2015
Project(s): LEARN PAD
Re B., Polini A., Corradini F., Fornari F., Sergiacomi A., Amici C., Balducci A., Carota S., Giorgio L., De Simone S., Ferrari A., Gnesi S., Spagnolo G. O., Efendioglu N., Bertolino A.
The main goal of this deliverable is to early collect end-users feedback about the platform imple- mented functionalities for the sake of the Learn PAd consortium. End-users needs and expectations are driving forces of the Learn PAd project, that is why a validation has been carried out to ensure that the early version of the Learn PAd platform properly addresses them. The early validation was carried out considering the running instance of the Learn PAd platform available (since 06 November 2015) at the address: http://testbed.learnpad.eu/. A group of users sampled from both the project demonstrators tested the Learn PAd platform and provided us with feedback and comments to improve it. Results from such validation are reported in the first part of this deliverable. Moreover, even if not explicitly requested in the DoW, a further validation was also done to check the goodness of BPMN modelling understandability guidelines that we defined in WP4. This further validation involved a questionnaire and a focus group with the aim to guarantee that the defined BP modelling understandability guidelines actually contribute to improve BP model understandability. In the second part of this deliverable we report in detail the results of the modelling guidelines valida- tion. From the guidelines validation, we can assert that models designed following BPMN modelling understandability guidelines indeed result to be better understandable than the ones generated by not following the guidelines. In fact, for such reason the BP models used in the deployed running instance of the Learn PAd platform involved in the user early validation are those conforming to the guidelines.Source: Project report, LEARN PAD, Deliverable D8.2, 2015
Project(s): LEARN PAD
See at:
ISTI Repository | CNR ExploRA