05 Fakultät Informatik, Elektrotechnik und Informationstechnik

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6

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Publication Type: search.filters.UBSTyp.KonferenzbeitragSubject: search.filters.subject.004Institute: search.filters.UBSInstitut.Fakultätsübergreifend / Sonstige Einrichtung

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Now showing 1 - 10 of 21
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    Modelling the quality economics of defect-detection techniques
    (2006) Wagner, Stefan
    There are various ways to evaluate defect-detection techniques. However, for a comprehensive evaluation the only possibility is to reduce all influencing factors to costs. There are already some models and metrics for the cost of quality that can be used in that context. These models allow the structuring of the costs but do not show all influencing factors and their relationships. This paper proposes an analytical model for the economics of defect-detection techniques that can be used for analysis and optimisation of the usage of such techniques. In particular we analyse the sensitivity of the model and how the model can be applied in practice.
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    SalChartQA: question-driven saliency on information visualisations
    (2024) Wang, Yao; Wang, Weitian; Abdelhafez, Abdullah; Elfares, Mayar; Hu, Zhiming; Bâce, Mihai; Bulling, Andreas
    Understanding the link between visual attention and user’s needs when visually exploring information visualisations is under-explored due to a lack of large and diverse datasets to facilitate these analyses. To fill this gap, we introduce SalChartQA - a novel crowd-sourced dataset that uses the BubbleView interface as a proxy for human gaze and a question-answering (QA) paradigm to induce different information needs in users. SalChartQA contains 74,340 answers to 6,000 questions on 3,000 visualisations. Informed by our analyses demonstrating the tight correlation between the question and visual saliency, we propose the first computational method to predict question-driven saliency on information visualisations. Our method outperforms state-of-the-art saliency models, improving several metrics, such as the correlation coefficient and the Kullback-Leibler divergence. These results show the importance of information needs for shaping attention behaviour and paving the way for new applications, such as task-driven optimisation of visualisations or explainable AI in chart question-answering.
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    Software quality models : purposes, usage scenarios and requirements
    (2009) Deißenböck, Florian; Juergens, Elmar; Lochmann, Klaus; Wagner, Stefan
    Software quality models are a well-accepted means to support quality management of software systems. Over the last 30 years, a multitude of quality models have been proposed and applied with varying degrees of success. Despite successes and standardisation efforts, quality models are still being criticised, as their application in practice exhibits various problems. To some extent, this criticism is caused by an unclear definition of what quality models are and which purposes they serve. Beyond this, there is a lack of explicitly stated requirements for quality models with respect to their intended mode of application. To remedy this, this paper describes purposes and usage scenarios of quality models and, based on the literature and experiences from the authors, collects critique of existing models. From this, general requirements for quality models are derived. The requirements can be used to support the evaluation of existing quality models for a given context or to guide further quality model development.
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    The Quamoco product quality modelling and assessment approach
    (2012) Wagner, Stefan; Lochmann, Klaus; Heinemann, Lars; Kläs, Michael; Trendowicz, Adam; Plösch, Reinhold; Seidl, Andreas; Goeb, Andreas; Streit, Jonathan
    Published software quality models either provide abstract quality attributes or concrete quality assessments. There are no models that seamlessly integrate both aspects. In the project Quamoco, we built a comprehensive approach with the aim to close this gap. For this, we developed in several iterations a meta quality model specifying general concepts, a quality base model covering the most important quality factors and a quality assessment approach. The meta model introduces the new concept of a product factor, which bridges the gap between concrete measurements and abstract quality aspects. Product factors have measures and instruments to operationalise quality by measurements from manual inspection and tool analysis. The base model uses the ISO 25010 quality attributes, which we refine by 200 factors and 600 measures for Java and C# systems. We found in several empirical validations that the assessment results fit to the expectations of experts for the corresponding systems. The empirical analyses also showed that several of the correlations are statistically significant and that the maintainability part of the base model has the highest correlation, which fits to the fact that this part is the most comprehensive. Although we still see room for extending and improving the base model, it shows a high correspondence with expert opinions and hence is able to form the basis for repeatable and understandable quality assessments in practice.
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    Mouse2Vec: learning reusable semantic representations of mouse behaviour
    (2024) Zhang, Guanhua; Hu, Zhiming; Bâce, Mihai; Bulling, Andreas
    The mouse is a pervasive input device used for a wide range of interactive applications. However, computational modelling of mouse behaviour typically requires time-consuming design and extraction of handcrafted features, or approaches that are application-specific. We instead propose Mouse2Vec - a novel self-supervised method designed to learn semantic representations of mouse behaviour that are reusable across users and applications. Mouse2Vec uses a Transformer-based encoder-decoder architecture, which is specifically geared for mouse data: During pretraining, the encoder learns an embedding of input mouse trajectories while the decoder reconstructs the input and simultaneously detects mouse click events. We show that the representations learned by our method can identify interpretable mouse behaviour clusters and retrieve similar mouse trajectories. We also demonstrate on three sample downstream tasks that the representations can be practically used to augment mouse data for training supervised methods and serve as an effective feature extractor.
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    Naming the pain in requirements engineering: design of a global family of surveys and first results from Germany
    (2013) Méndez Fernández, Daniel; Wagner, Stefan
    Context: For many years, we have observed industry struggling in defining a high quality requirements engineering (RE) and researchers trying to understand industrial expectations and problems. Although we are investigating the discipline with a plethora of empirical studies, those studies either concentrate on validating specific methods or on single companies or countries. Therefore, they allow only for limited empirical generalisations. Objective: To lay an empirical and generalisable foundation about the state of the practice in RE, we aim at a series of open and reproducible surveys that allow us to steer future research in a problem-driven manner. Method: We designed a globally distributed family of surveys in joint collaborations with different researchers from different countries. The instrument is based on an initial theory inferred from available studies. As a long-term goal, the survey will be regularly replicated to manifest a clear understanding on the status quo and practical needs in RE. In this paper, we present the design of the family of surveys and first results of its start in Germany. Results: Our first results contain responses from 30 German companies. The results are not yet generalisable, but already indicate several trends and problems. For instance, a commonly stated problem respondents see in their company standards are artefacts being underrepresented, and important problems they experience in their projects are incomplete and inconsistent requirements. Conclusion: The results suggest that the survey design and instrument are well-suited to be replicated and, thereby, to create a generalisable empirical basis of RE in practice.
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    Clone detection in automotive model-based development
    (2008) Deißenböck, Florian; Hummel, Benjamin; Juergens, Elmar; Schätz, Bernhard; Wagner, Stefan; Girard, Jean-François; Teuchert, Stefan
    Model-based development is becoming an increasingly common development methodology. In important domains like embedded systems already major parts of the code are generated from models specified with domain-specific modelling languages. Hence, such models are nowadays an integral part of the software development and maintenance process and therefore have a major economic and strategic value for the software-developing organisations. Nevertheless almost no work has been done on a quality defect that is known to seriously hamper maintenance productivity in classic code-based development: Cloning. This paper presents an approach for the automatic detection of clones in large models as they are used in model-based development of control systems. The approach is based on graph theory and hence can be applied to most graphical data-flow languages. An industrial case study demonstrates the applicability of our approach for the detection of clones in Matlab/Simulink models that are widely used in model-based development of embedded systems in the automotive domain.
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    Saliency3D: a 3D saliency dataset collected on screen
    (2024) Wang, Yao; Dai, Qi; Bâce, Mihai; Klein, Karsten; Bulling, Andreas
    While visual saliency has recently been studied in 3D, the experimental setup for collecting 3D saliency data can be expensive and cumbersome. To address this challenge, we propose a novel experimental design that utilizes an eye tracker on a screen to collect 3D saliency data. Our experimental design reduces the cost and complexity of 3D saliency dataset collection. We first collect gaze data on a screen, then we map them to 3D saliency data through perspective transformation. Using this method, we collect a 3D saliency dataset (49,276 fixations) comprising 10 participants looking at sixteen objects. Moreover, we examine the viewing preferences for objects and discuss our findings in this study. Our results indicate potential preferred viewing directions and a correlation between salient features and the variation in viewing directions.
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    Reading data: on digital reception studies
    (2018) Willand, Marcus; Beck, Jens; Reiter, Nils
    In the paper we present a method for the analysis of entity associations that real readers make in their reviews on goodreads.com, a social reading platform - and first results and insights of our analysis.
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    Detecting protagonists in German plays around 1800 as a classification task
    (2018) Reiter, Nils; Krautter, Benjamin; Pagel, Janis; Willand, Marcus
    In this paper, we aim at identifying protagonists in plays automatically. To this end, we train a classifier using various features and investigate the importance of each feature. A challenging aspect here is that the number of spoken words for a character is a very strong baseline. We can show, however, that a) the stage presence of characters and b) topics used in their speech can help to detect protagonists even above the baseline.