The impact of structural complexity on the understandability of UML statechart diagrams

Cruz-Lemus, José A.; Maes, Ann; Genero, Marcela; Poels, Geert; Piattini, Mario

doi:10.1016/j.ins.2010.01.026

Cited by 55 publications

(17 citation statements)

References 39 publications

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“…A family of experiments contains multiple similar empirical studies that pursue the same goal. As Basili et al [5] observe, and as we have corroborated in previous research [11] [33], a family of experiments builds the knowledge that is needed to extract significant conclusions that can be applied in practice. That being so, the primary goal of the family was to test the usefulness of MEM in the evaluation of requirements modeling methods.…”

Section: Introductionsupporting

confidence: 57%

Evaluating requirements modeling methods based on user perceptions: A family of experiments

Abrahão

Insfrán

Carsí

et al. 2011

Information Sciences

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Numerous methods and techniques have been proposed for requirements modeling, although very few have had widespread use in practice. One drawback of requirements methods is that they lack proper empirical evaluations. This means that there is a need for evaluation methods that consider both the theoretical and practical aspects of this type of methods and techniques. In this paper, we present a method for evaluating the quality of requirements modeling methods based on user perceptions. The method consists of a theoretical model that explains the relevant dimensions of quality for requirements methods, along with a practical instrument with which to measure these quality dimensions Basically, it allows us to predict the acceptance of a particular requirements method in practice, based on the effort of applying the method, the quality of the requirements artifacts produced, and the user perceptions with regard to the quality of the method. The paper also presents an empirical test of the method that has been proposed for evaluating a Rational Unified Process (RUP) extension for requirements modelling. That test was carried out through a family of experiments conducted with students and practitioners and provides evidence of the usefulness of the evaluation method proposed.

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Section: Introductionsupporting

confidence: 57%

Evaluating requirements modeling methods based on user perceptions: A family of experiments

Abrahão

Insfrán

Carsí

et al. 2011

Information Sciences

Self Cite

View full text Add to dashboard Cite

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“…Subsequently, these subjective values are used as measures for the dependent variables (Cruz-Lemus et al 2009;Genero et al 2008). The second approach is to define a set of tasks for the experts and then record the time taken for them to complete the tasks (time-to-complete), which would serve as an indication for the dependent variable (Cruz-Lemus et al 2010;Serrano et al 2008). We do not use this second approach for three reasons: (1) we are focused on understanding the relation between the subjective perception of model analysts about maintainability and the metric values.…”

Section: Dependent Variablesmentioning

confidence: 99%

Assessing the maintainability of software product line feature models using structural metrics

2011

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A software product line is a unified representation of a set of conceptually similar software systems that share many common features and satisfy the requirements of a particular domain. Within the context of software product lines, feature models are treelike structures that are widely used for modeling and representing the inherent commonality and variability of software product lines. Given the fact that many different software systems can be spawned from a single software product line, it can be anticipated that a low-quality design can ripple through to many spawned software systems. Therefore, the need for early indicators of external quality attributes is recognized in order to avoid the implications of defective and low-quality design during the late stages of production. In this paper, we propose a set of structural metrics for software product line feature models and theoretically validate them using valid measurement-theoretic principles. Further, we investigate through controlled experimentation whether these structural metrics can be good predictors (early indicators) of the three main subcharacteristics of maintainability: analyzability, changeability, and understandability. More specifically, a four-step analysis is conducted: (1) investigating whether feature model structural metrics are correlated with feature model maintainability through the employment of classical statistical correlation techniques; (2) understanding how well each of the structural metrics can serve as discriminatory references for maintainability; (3) identifying the sufficient set of structural metrics for evaluating each of the subcharacteristics of maintainability; and (4) evaluating how well different prediction models based on the proposed structural metrics can perform in indicating the maintainability of a feature model. Results obtained from the controlled experiment support the idea that useful prediction models can be built for the purpose of evaluating feature model maintainability using early structural metrics. Some of the structural metrics show significant correlation with the subjective perception of the subjects about the maintainability of the feature models.

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“…VRs with high degrees of density and/or complexity can place a large burden on users' perceptual and cognitive faculties and thus negatively influence the performance of tasks and activities (Demetriadis and Cadoz, 2005;Pirolli et al, 2001 user's working memory (Green and Petre, 1996). VRs with a lower degree of complexity have been empirically shown to have more correct responses to tasks as well as better reaction times while identifying trends in information spaces (see Cruz-Lemus et al, 2010;Huang et al, 2009;Meyer et al 1997). Collapsing can allow users to condense a set of items into one, thereby reducing complexity and/or density and facilitating the comprehension of overall relationships and trends.…”

Section: Collapsing/expandingmentioning

confidence: 99%

Interaction Design for Complex Cognitive Activities with Visual Representations: A Pattern-Based Approach

Sedig

Parsons²

2013

THCI

109

156

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This paper is concerned with interaction design for visualization-based computational tools that support the performance of complex cognitive activities, such as analytical reasoning, sense making, decision making, problem solving, learning, planning, and knowledge discovery. In this paper, a number of foundational concepts related to interaction and complex cognitive activities are syncretized into a coherent theoretical framework. This framework is general, in the sense that it is applicable to all technologies, platforms, tools, users, activities, and visual representations. Included in the framework is a catalog of 32 fundamental epistemic action patterns, with each action pattern being characterized and examined in terms of its utility in supporting different complex cognitive activities. This catalog of action patterns is comprehensive, covering a broad range of interactions that are performed by a diverse group of users for all kinds of tasks and activities. The presented framework is also generative, in that it can stimulate creativity and innovation in research and design for a number of domains and disciplines, including data and information visualization, visual analytics, digital libraries, health informatics, learning sciences and technologies, personal information management, decision support, information systems, and knowledge management.

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The impact of structural complexity on the understandability of UML statechart diagrams

Cited by 55 publications

References 39 publications

Evaluating requirements modeling methods based on user perceptions: A family of experiments

Evaluating requirements modeling methods based on user perceptions: A family of experiments

Assessing the maintainability of software product line feature models using structural metrics

Interaction Design for Complex Cognitive Activities with Visual Representations: A Pattern-Based Approach

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