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See detailLeveraging Natural-language Requirements for Deriving Better Acceptance Criteria from Models
Veizaga Campero, Alvaro Mario UL; Alferez, Mauricio UL; Torre, Damiano UL et al

in Proceedings of 23rd ACM / IEEE International Conference on Model Driven Engineering Languages and Systems (MODELS) (in press)

In many software and systems development projects, analysts specify requirements using a combination of modeling and natural language (NL). In such situations, systematic acceptance testing poses a ... [more ▼]

In many software and systems development projects, analysts specify requirements using a combination of modeling and natural language (NL). In such situations, systematic acceptance testing poses a challenge because defining the acceptance criteria (AC) to be met by the system under test has to account not only for the information in the (requirements) model but also that in the NL requirements. In other words, neither models nor NL requirements per se provide a complete picture of the information content relevant to AC. Our work in this paper is prompted by the observation that a reconciliation of the information content in NL requirements and models is necessary for obtaining precise AC. We perform such reconciliation by devising an approach that automatically extracts AC-related information from NL requirements and helps modelers enrich their model with the extracted information. An existing AC derivation technique is then applied to the model that has now been enriched by the information extracted from NL requirements. Using a real case study from the financial domain, we evaluate the usefulness of the AC-related model enrichments recommended by our approach. Our evaluation results are very promising: Over our case study system, a group of five domain experts found 89% of the recommended enrichments relevant to AC and yet absent from the original model (precision of 89%). Furthermore, the experts could not pinpoint any additional information in the NL requirements which was relevant to AC but which had not already been brought to their attention by our approach (recall of 100%) [less ▲]

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See detailAn AI-assisted Approach for Checking the Completeness of Privacy Policies Against GDPR
Torre, Damiano UL; Abualhaija, Sallam UL; Sabetzadeh, Mehrdad UL et al

in in Proceedings of the 28th IEEE International Requirements Engineering Conference (RE’20) (in press)

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See detailUML Consistency Rules:a Case Study with Open-Source UML Models
Torre, Damiano UL; Labiche, Yvan; Genero, Marcela et al

in Proceedings of the 8th International Conference on Formal Methods in Software Engineering (in press)

UML models are standard artifacts used by software engineers for designing software. As software is designed, different UML diagram types (e.g., class diagrams and sequence diagrams) are produced by ... [more ▼]

UML models are standard artifacts used by software engineers for designing software. As software is designed, different UML diagram types (e.g., class diagrams and sequence diagrams) are produced by software designers. Since the various UML diagram types describe different aspects of a software system, they are not independent but strongly depend on each other, hence they must be consistent. Inconsistencies cause faults in the final software systems. It is, therefore, paramount that they get detected, analyzed, and fixed. Consistency rules are a useful tool proposed in the literature to detect inconsistencies. They categorize constraints that help in identifying inconsistencies when violated. This case study aims at collecting and analyzing UML models with OCL consistency rules proposed in the literature and at promoting the development of a reference benchmark that can be reused by the (FM-)research community. We collected 33 UML consistency rules and 206 different UML diagrams contained in 34 open-source UML models presented in the literature. We propose an FM-based encoding of the consistency rules in OCL. This encoding allows analyzing whether the consistency rules are satisfied or violated within the 34 UML models. To assess the proposed benchmark, we analyzed how the UML models, consistency rules, diagram types contained in the benchmark help in assessing the consistency of UML models, and the consistency of diagrams across the different software development phases. Our results show that the considered UML models and consistency rules allowed identifying 2731 inconsistencies and that those inconsistencies refer to different software development phases. We concluded that the considered UML models and consistency rules could be considered as an initial benchmark that can be further extended by the research community. [less ▲]

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See detailUsing Models to Enable Compliance Checking against the GDPR: An Experience Report
Torre, Damiano UL; Soltana, Ghanem UL; Sabetzadeh, Mehrdad UL et al

in Proceedings of the IEEE / ACM 22nd International Conference on Model Driven Engineering Languages and Systems (MODELS 19) (2019, September)

The General Data Protection Regulation (GDPR) harmonizes data privacy laws and regulations across Europe. Through the GDPR, individuals are able to better control their personal data in the face of new ... [more ▼]

The General Data Protection Regulation (GDPR) harmonizes data privacy laws and regulations across Europe. Through the GDPR, individuals are able to better control their personal data in the face of new technological developments. While the GDPR is highly advantageous to citizens, complying with it poses major challenges for organizations that control or process personal data. Since no automated solution with broad industrial applicability currently exists for GDPR compliance checking, organizations have no choice but to perform costly manual audits to ensure compliance. In this paper, we share our experience building a UML representation of the GDPR as a first step towards the development of future automated methods for assessing compliance with the GDPR. Given that a concrete implementation of the GDPR is affected by the national laws of the EU member states, GDPR’s expanding body of case laws and other contextual information, we propose a two-tiered representation of the GDPR: a generic tier and a specialized tier. The generic tier captures the concepts and principles of the GDPR that apply to all contexts, whereas the specialized tier describes a specific tailoring of the generic tier to a given context, including the contextual variations that may impact the interpretation and application of the GDPR. We further present the challenges we faced in our modeling endeavor, the lessons we learned from it, and future directions for research. [less ▲]

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