UIPLML: Pattern-based engineering of user interfaces of multi-platform systems

Nguyen, Thanh-Diane; Vanderdonckt, Jean; Ahmed, Shamsuddin

doi:10.1109/rcis.2016.7549348

Cited by 6 publications

(5 citation statements)

References 18 publications

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“…The UI based on patterns and UI based on models [29 ] offers an approach for instantiating and adapting all models involved in the UI design process, not just task models. The user interface pattern language markup language [30 ] is a similar approach, which is compatible with XML and can define UI patterns for multiple contexts of use. On the other hand, Vanderdonckt et al [31 ] presented a method for UI development based on the use of a generative design pattern called markup language (PLML).…”

Section: Related Workmentioning

confidence: 99%

Classifying design‐level requirements using machine learning for a recommender of interaction design patterns

Silva-Rodríguez

Nava-Muñoz

Castro³

et al. 2020

IET softw.

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Software Engineering is a discipline that encompasses processes associated with the development of interactive systems. The perceived quality of an interactive system is heavily influenced by the user interface design, which may result in many challenges. One such challenge is design‐level requirements analysis. The success of the software system is mostly dependent on how well users’ requirements have been understood and translated into appropriate functionalities. During the interactive system design process, it is common to find recurring problems in human–computer interactions, for which reusing solutions is highly feasible. Interaction design patterns seek to support designers in decision making during the design of interactive systems. Due to the design task tends to be subjective and prone to errors. This work aims at presenting and evaluating an interaction design patterns recommendation model based on design‐level requirements classification, through the application of supervised machine learning algorithms. To compare the performance of four classification algorithms, a study was carried out, in which the linear support vector machine was the most suitable to this problem. The results of this work can be used for implementing frameworks that can better support designers’ decision making when designing user interfaces.

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Section: Related Workmentioning

confidence: 99%

Classifying design‐level requirements using machine learning for a recommender of interaction design patterns

Silva-Rodríguez

Nava-Muñoz

Castro³

et al. 2020

IET softw.

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“…Several model-based tools have been developed to present and test a possible solution [8][9][10][11]. First, PD-MBUI [9] (UI based on patterns and UI based on models) proposes to integrate the patterns in the design process.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Other approaches such as [8,10,11] consider the identification of patterns based on an ontology with the same structure of the design pattern and its design patterns catalog. Despite this, some approaches specifically address the natural language processing (NLP) of requirements.…”

Section: Literature Reviewmentioning

confidence: 99%

Machine Learning Methods for Inferring Interaction Design Patterns from Textual Requirements

Silva-Rodríguez¹,

Nava-Muñoz²,

Castro³

et al. 2019

13th International Conference on Ubiquitous Computing and Ambient ‪Intelligence UCAmI 2019‬

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Ambient intelligence is one of the most exciting fields of application for pervasive, wireless, and embedded computing. However, the design and implementation of real-world systems must be conducted utilizing software engineering approaches. Some types of environments (hospitals, older adults homes, emergency scenarios, etc.) are particularly critical, especially in terms of the issues concerning expressing requirements, verifying and validating them, or ensuring functional correctness. To provide adequate ambient intelligence solutions, it is necessary to place special emphasis on obtaining, specifying, and documenting software requirements. To address this issue, our paper presents a model that integrates both requirements and design patterns. This is done through a natural language processing application in conjunction with other artificial intelligence algorithms. This work aims to support designers when analyzing text requirements and support design decisions. Our results were evaluated according to the cross-validated accuracy of predicting design patterns. The results obtained indicate that this approach could lead to good recommendations of design patterns, as it demonstrated an acceptable classification performance over the balanced dataset of requirements instances.

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“…Among the heterogeneous collections of HCI design patterns, the "Common Ground" 2.2. Fundamentals of Design Patterns [Tidwell, 1999], "Experience" [Coram and Lee, 1996], and "Amsterdam" [Welie, 1999] catalogs are very popular and widely used in the HCI domain.…”

Section: Design Pattern Domainmentioning

confidence: 99%

“…In order to overcome the weakness of PLML and its extensions, [Thanh-Diane et al, 2016] develop an XML-compliant markup language named User Interface Pattern Language Markup Language (UIPLML). UIPLML aims at defining UI design patterns for various contexts of use in order to provide information, which are required to design a UI.…”

Section: Design Pattern Languagementioning

confidence: 99%

Towards Designing and Generating User Interfaces by Using Expert Knowledge

Braham¹

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I would like to express my gratitude to my supervisors, Mr. Félix Buendia Garcia, Mr. Faeiz Gargouri and Ms. Maha Khemaja, for their valuable insights and the enormous patience that was necessary for guiding me all along the way. Their support, advice and feedback have been a fundamental part to get to the end of this journey. I want to extend my gratitude to all the members of the Computing Engineering Department (DISCA) of the Universitat Politecnica de Valencia (UPV) for the excellent working environment they provide throughout my journey. In addition, I am grateful for the academic support of the University of Sousse, the Higher Institute of Computer Science and Communication Technologies (ISITCom) and the PRINCE Laboratory.I also want to pay tribute to the members of the jury for agreeing to be a part of the court and the external reviewers for their thoughtful comments and positive feedback.A very special thanks goes out to Roua. We started our university journey at the same time and she has been my friend and support from that moment until now.Finally, thanks to Yosra and Khadija, my two sisters, and my brother Ali for their love and for keeping me always smiling. I have to appreciate the irreplaceable support of my parents, Ahmed and Saida, who have given me unstinting love, care, trust, help, and encouragement.

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UIPLML: Pattern-based engineering of user interfaces of multi-platform systems

Cited by 6 publications

References 18 publications

Classifying design‐level requirements using machine learning for a recommender of interaction design patterns

Classifying design‐level requirements using machine learning for a recommender of interaction design patterns

Machine Learning Methods for Inferring Interaction Design Patterns from Textual Requirements

Towards Designing and Generating User Interfaces by Using Expert Knowledge

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