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9th IFIP WG 13.2 International Working Conference on Human-Centered Software Engineering (HCSE)

作者： Kirchhoff, Jonas Weskamp, Christoph Engels, Gregor Paderborn Univ Software Innovat Lab Paderborn Germany

ISBN: (纸本)9783031147852;9783031147845

Corporate decision makers have individual requirements for decision support influenced by business goals, regulatory restrictions or access to resources such as data. Ideally, decision makers could quickly create tailored decision support systems (DSS) themselves which optimally address their individual requirements for decision support. Although service-oriented architectures have been proposed for DSS customization, they are primarily targeting trained software developers and cannot immediately be adapted by decision makers or domain experts with little to no software development knowledge. In this paper, we therefore motivate an assisted process-based service composition approach which can be used by non-developers to create tailored DSS. For assistance during service composition, we contribute a meta-model for the formalization of both decision support requirements and functionality of decision support services. Models created according to the meta-model can be used to detect mismatches between a decision maker's requirements for decision support and services selected in the service composition representing a DSS. Furthermore, the formalizations may even be used for automated service composition given a decision maker's decision support requirements. We demonstrate the expressiveness of our metamodel in the domain of regional energy distribution network planning.

关键词： Service-oriented DSS end-user programming Automated service composition Decision support system generator

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Considerations for using Block-Based Languages for Industrial Robot programming - a Case Study 3

Considerations for using Block-Based Languages for Industria...

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3rd IEEE/ACM International Workshop on Robotics Software Engineering (RoSE)

作者： Mayr-Dorn, Christoph Winterer, Mario Salomon, Christian Hohensinger, Doris Ramler, Rudolf Johannes Kepler Univ Linz Linz Austria Software Competence Ctr Hagenberg GmbH Hagenberg Austria

ISBN: (纸本)9781665444743

The paradigm shift triggered by Industry 4.0 leads to a fast rising number of industrial machinery and collaborative robots that increases the need for flexible customization of production processes and automation workflows. end-user programming of industrial robots has become an essential capability for all areas in industry. Consequently, different visual programming languages have found their way into the domain of industrial robot programming. In this paper, we investigate the applicability of block-based programming languages for large and complex robot programs in realistic environments. Here, a key aspect of robot programming is not only the interaction with the physical environment, but also the robot's interaction with other shopfloor participants at the software control level. To this end, we analysed the requirements for programming a robot based a real world production cell and implemented the necessary programming constructs using Blockly, an open-source block-based visual language. We assessed the results comparing the implementation of a change in Blockly and the Sequential Function Chart-based language. We find that while Blockly is able to express large and complex real-world robot programs, a major contributing factor is not just the language itself but the presentation of the robot's run-time environment as well as support by the development environment (i.e., editor). Our preliminary user experiment has identified a set of challenges in understanding and changing such programs that we now plan to follow-up with a larger user study.

关键词： Robot programming end-user programming manufacturing automation block-based programming languages

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Stylette: Styling the Web with Natural Language 22

Stylette: Styling the Web with Natural Language

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CHI Conference on Human Factors in Computing Systems (CHI)

作者： Kim, Tae Soo Choi, DaEun Choi, Yoonseo Kim, Juho Korea Adv Inst Sci & Technol Sch Comp Daejeon South Korea

ISBN: (纸本)9781450391573

end-users can potentially style and customize websites by editing them through in-browser developer tools. Unfortunately, end-users lack the knowledge needed to translate high-level styling goals into low-level code edits. We present Stylette, a browser extension that enables users to change the style of websites by expressing goals in natural language. By interpreting the user's goal with a large language model and extracting suggestions from our dataset of 1.7 million web components, Stylette generates a palette of CSS properties and values that the user can apply to reach their goal. A comparative study (N=40) showed that Stylette lowered the learning curve, helping participants perform styling changes 35% faster than those using developer tools. By presenting various alternatives for a single goal, the tool helped participants familiarize themselves with CSS through experimentation. Beyond CSS, our work can be expanded to help novices quickly grasp complex software or programming languages.

关键词： Web Design Natural Language Interface end-user programming Machine Learning

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Engaging end-user driven recommender systems: personalization through web augmentation

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MULTIMEDIA TOOLS AND APPLICATIONS 2021年第5期80卷 6785-6809页

作者： Wischenbart, Martin Firmenich, Sergio Rossi, Gustavo Bosetti, Gabriela Kapsammer, Elisabeth Johannes Kepler Univ Linz Linz Austria Univ Nacl La Plata Lab Invest & Formac Informat Avanzada LIFIA La Plata Argentina Consejo Nacl Invest Cient & Tecn La Plata Argentina Johannes Kepler Univ Linz Dept Cooperat Informat Syst CIS Linz Austria

In the past decades recommender systems have become a powerful tool to improve personalization on the Web. Yet, many popular websites lack such functionality, its implementation usually requires certain technical skills, and, above all, its introduction is beyond the scope and control of end-users. To alleviate these problems, this paper presents a novel tool to empower end-users without programming skills, without any involvement of website providers, to embed personalized recommendations of items into arbitrary websites on client-side. For this we have developed a generic meta-model to capture recommender system configuration parameters in general as well as in a web augmentation context. Thereupon, we have implemented a wizard in the form of an easy-to-use browser plug-in, allowing the generation of so-called user scripts, which are executed in the browser to engage collaborative filtering functionality from a provided external rest service. We discuss functionality and limitations of the approach, and in a study with end-users we assess the usability and show its suitability for combining recommender systems with web augmentation techniques, aiming to empower end-users to implement controllable recommender applications for a more personalized browsing experience.

关键词： Web augmentation Visual programming Client-side personalization end-user programming end-user development Controllability of recommender systems Browser-side trans-coding

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Empowering domain experts to author valid statistical analyses 35

Empowering domain experts to author valid statistical analys...

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35th Annual ACM Symposium on user Interface Software and Technology (UIST)

作者： Jun, Eunice Univ Washington Paul G Allen Sch Comp Sci & Engn Seattle WA 98195 USA

ISBN: (纸本)9781450393218

Reliable statistical analyses are critical for making scientific discoveries, guiding policy, and informing decisions. To author reliable statistical analyses, integrating knowledge about the domain, data, statistics, and programming is necessary. However, this is an unrealistic expectation for many analysts who may possess domain expertise but lack statistical or programming expertise, including many researchers, policy makers, and other data scientists. How can our statistical software help these analysts? To address this need, we first probed into the cognitive and operational processes involved in authoring statistical analyses and developed the theory of hypothesis formalization. Authoring statistical analyses is a dual-search process that requires grappling with assumptions about conceptual relationships and iterating on statistical model implementations. This led to our key insight: statistical software needs to help analysts translate what they know about their domain and data into statistical modeling programs. To do so, statistical software must provide programming interfaces and interaction models that allow statistical non-experts to express their analysis goals accurately and reflect on their domain knowledge and data. Thus far, we have developed two such systems that embody this insight: Tea and Tisane. Ongoing work on rTisane explores new semantics for more accurately eliciting analysis intent and conceptual knowledge. Additionally, we are planning a summative evaluation of rTisane to assess our hypothesis that this new way of authoring statistical analyses makes domain experts more aware of their implicit assumptions, able to author and understand nuanced statistical models that answer their research questions, and avoid previous analysis mistakes.

关键词： statistical analysis end-user programming domain-specifc languages mixed-initiative systems transparent statistics validity

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Flow-Based programming for Machine Learning

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FUTURE INTERNET 2022年第2期14卷 58-58页

作者： Mahapatra, Tanmaya Banoo, Syeeda Nilofer Tech Univ Munich Software & Syst Engn Res Grp Boltzmannstr 03 D-85748 Garching Germany Birla Inst Technol & Sci Dept Comp Sci & Informat Syst Pilani 333031 Rajasthan India

Machine Learning (ML) has gained prominence and has tremendous applications in fields like medicine, biology, geography and astrophysics, to name a few. Arguably, in such areas, it is used by domain experts, who are not necessarily skilled-programmers. Thus, it presents a steep learning curve for such domain experts in programming ML applications. To overcome this and foster widespread adoption of ML techniques, we propose to equip them with domain-specific graphical tools. Such tools, based on the principles of flow-based programming paradigm, would support the graphical composition of ML applications at a higher level of abstraction and auto-generation of target code. Accordingly, (i) we have modelled ML algorithms as composable components;(ii) described an approach to parse a flow created by connecting several such composable components and use an API-based code generation technique to generate the ML application. To demonstrate the feasibility of our conceptual approach, we have modelled the APIs of Apache Spark ML as composable components and validated it in three use-cases. The use-cases are designed to capture the ease of program specification at a higher abstraction level, easy parametrisation of ML APIs, auto-generation of the ML application and auto-validation of the generated model for better prediction accuracy.

关键词： end-user programming graphical flows graphical programming tools machine learning as a service (MLaaS) machine-learning-platform-as-a-service (ML PaaS) machine learning pipelines

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Caregiver development of activity-supporting services for smart homes

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JOURNAL OF AMBIENT INTELLIGENCE AND SMART ENVIRONMENTS 2021年第6期13卷 453-471页

作者： Belloum, Rafik Yaddaden, Amel Lussier, Maxime Bier, Nathalie Consel, Charles INRIA Talence France Univ Montreal Inst Univ Geriatrie Montreal Ctr Rech Montreal PQ Canada Bordeaux INP Dept Comp Sci Bordeaux France

Older adults often need some level of assistance in performing daily living activities. Even though these activities are common to the vast majority of individuals (e.g., eating, bathing, dressing), the way they are performed varies across individuals. Supporting older people in performing their everyday activities is a major avenue of research in smart homes. However, because of its early stage, this line of work has paid little attention on customizing assistive computing support with respect to the specific needs of each older adult towards improving its effectiveness and acceptability. We propose a tool-based approach to allowing caregivers to define services in the area of home daily living, leveraging their knowledge and expertise on the older adult they care for. This approach consists of two stages: 1) a wizard allows caregivers to define an assistive service, which supports aspects of a daily activity that are specific to an older adult;2) the wizard-generated service is uploaded in an existing smart home platform and interpreted by a dedicated component, carrying out the caregiver-defined service. Our approach has been implemented. Our wizard has been successfully used to define existing manually-programmed, activity-supporting services. The resulting services have been deployed and executed by an existing assisted living platform deployed in the home of community-dwelling individuals. They have been shown to be equivalent to their manually-programmed counterparts. We also conducted an ergonomics study involving five occupational therapists, who tested our wizard with clinical vignettes describing fictitious patients. Participants were able to successfully define services while revealing an ease of use of our wizard.

关键词： Smart home ambient assisted living assistive computing end-user programming

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end-user modeling of quality for web components

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JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS 2023年第3期35卷

作者： Lizcano, David Martinez-Ortiz, Andres-Leonardo Grignard, Arnaud Lopez, Genoveva Madrid Open Univ UDIMA Madrid Spain Comp Soc GoogleCloud Ecosyst Program Geneva Switzerland Univ Politecn Madrid Escuela Tecn Super Ingn Informat Seville Spain MIT Media Lab Cambridge MA 02139 USA

With years of frantic development, when release fast and release often was the mandatory rule for web technologies and services, the open source paradigm and online distribution repositories have imposed de facto standards for quality assessment in fast-paced innovation processes. Nowadays, however, in pursuit of productivity, security, and user satisfaction, the industry is beginning, through the introduction of new standards such as ECMAScript 6 or web components, to consider software engineering mandates for web technologies. This article reports a quality model aligned with international standard ISO/IEC 25010, covering web components technology, which ultimately aims to improve adoption by the software engineering industry, traditionally wary of agile Internet practices, the open source paradigm, and public repositories. Our research also presents an experimentation platform on which end users have validated the quality properties, highlighting the implicit connection with the perceived quality. The key result of our research convinces us that user ratings are suitable as a testing mechanism for product quality and quality-in-use metrics in order to define an absolute scale of comparison for web component quality.

关键词： end-user programming end-user software engineering human-computer interaction human-inspired metrics reliability software quality

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Refactoring in Computational Notebooks

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ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY 2023年第3期32卷 77-77页

作者： Liu, Eric S. Lukes, Dylan A. Griswold, William G. Univ Calif San Diego Comp Sci & Engn 9500 Gilman Dr La Jolla CA 92093 USA

Due to the exploratory nature of computational notebook development, a notebook can be extensively evolved even though it is small, potentially incurring substantial technical debt. Indeed, in interview studies notebook authors have attested to performing ongoing tidying and big cleanups. However, many notebook authors are not trained as software developers, and environments like JupyterLab possess few features to aid notebook maintenance. As software refactoring is traditionally a critical tool for reducing technical debt, we sought to better understand the unique and growing ecology of computational notebooks by investigating the refactoring of public Jupyter notebooks. We randomly selected 15,000 Jupyter notebooks hosted on GitHub and studied 200 with meaningful commit histories. We found that notebook authors do refactor, favoring a few basic classic refactorings as well as those involving the notebook cell construct. Those with a computing background refactored differently than others, but not more so. Exploration-focused notebooks had a unique refactoring profile compared to more exposition-focused notebooks. Authors more often refactored their code as they went along, rather than deferring maintenance to big cleanups. These findings point to refactoring being intrinsic to notebook development.

关键词： Computational notebooks end-user programming refactoring

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Towards programming in Natural Language: Learning New Functions from Spoken Utterances

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INTERNATIONAL JOURNAL OF SEMANTIC COMPUTING 2020年第2期14卷 249-272页

作者： Weigelt, Sebastian Steurer, Vanessa Hey, Tobias Tichy, Walter F. Karlsruhe Inst Technol Inst Program Struct & Data Org Karlsruhe Germany

Systems with conversational interfaces are rather popular nowadays. However, their full potential is not yet exploited. For the time being, users are restricted to calling predefined functions. Soon, users will expect to customize systems to their needs and create own functions using nothing but spoken instructions. Thus, future systems must understand how laypersons teach new functionality to intelligent systems. The understanding of natural language teaching sequences is a first step toward comprehensive end-user programming in natural language. We propose to analyze the semantics of spoken teaching sequences with a hierarchical classification approach. First, we classify whether an utterance constitutes an effort to teach a new function or not. Afterward, a second classifier locates the distinct semantic parts of teaching efforts: declaration of a new function, specification of intermediate steps, and superfluous information. For both tasks we implement a broad range of machine learning techniques: classical approaches, such as Naive Bayes, and neural network configurations of various types and architectures, such as bidirectional LSTMs. Additionally, we introduce two heuristic-based adaptations that are tailored to the task of understanding teaching sequences. As data basis we use 3168 descriptions gathered in a user study. For the first task convolutional neural networks obtain the best results (accuracy: 96.6%);bidirectional LSTMs excel in the second (accuracy: 98.8%). The adaptations improve the first-level classification considerably (plus 2.2% points).

关键词： programming in natural language natural language understanding end-user programming conversational interfaces spoken language understanding natural language processing computational linguistics naturalistic programming machine learning neural networks intelligent systems artificial intelligence

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