BackgroundBioinformatics data analysis faces significant challenges. As data analysis often takes the form of pipelines or workflows, workflow managers (WfMs) have become essential. Data flowprogramming constitutes t...
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BackgroundBioinformatics data analysis faces significant challenges. As data analysis often takes the form of pipelines or workflows, workflow managers (WfMs) have become essential. Data flowprogramming constitutes the preferred approach in WfMs, enabling parallel processes activated reactively based on input availability. While this paradigm typically follows a linear, acyclic progression, cyclic workflows are sometimes necessary in bioinformatics analyses. These cyclic workflows also present an opportunity to explore workflow interactivity, a feature not widely implemented in existing *** propose DeBasher, a tool that adopts the flow-based programming (FBP) paradigm, in which the workflow components are in control of their life cycle and can store state information, allowing the execution of complex workflows that include cycles. DeBasher also incorporates a powerful model of interactivity, where the user can alter the behavior of a running workflow. Additionally, DeBasher allows the user to define triggers so as to initiate the execution of a complete workflow or a part of it. The ability to execute processes with state and in control of their life cycle also has applications in dynamic scheduling tasks. Furthermore, DeBasher presents a series of extra features, including the combination of multiple workflows at runtime through a feature we have called runtime piping, switching to static scheduling to increase scalability, or implementing processes in multiple languages. DeBasher has been successfully used to process 131.7 TB of genomic data by means of a variant calling *** is an FBP Bash extension that can be useful in a wide range of situations and in particular when implementing complex workflows, workflows with interactivity or triggers, or when a high scalability is required.
Music and computer science (CS) have profound historical and structural connections, with programming music offering a promising avenue for engaging children in CS through creative expression. To foster this engagemen...
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ISBN:
(纸本)9798400705311
Music and computer science (CS) have profound historical and structural connections, with programming music offering a promising avenue for engaging children in CS through creative expression. To foster this engagement, our team developed M-flow, a flow-based music programming platform designed to introduce students to CS via music. Despite extensive existing research in music and CS education, experience reports and empirical studies on K-12 teachers' implementation and its impact on young kids' learning are limited. Therefore, we recruit elementary school teachers and students with no or limited prior programming experience, introducing them to M-flow and its curriculum through a professional development workshop, a semester's job embedded support, and classroom implementation. We describe the experiences of teachers as they attempt to integrate music and CS, the challenges they face, and the influence on students' attitudes toward learning computing concepts. Specifically, we reflect on our intervention by conducting a sequential mixed-method evaluation. During the qualitative phase, we collected multiple sources of data from three teachers through focus groups and debriefings after a semester of classroom implementation. Thematic analysis of workshop activities, interviews, and debrief videos revealed three themes with seven sub-themes on teachers' integration of flow-based music programming and two themes with five sub-themes on challenges faced by the teachers. In the quantitative phase, we gathered data on attitudes and self-efficacy from 75 students taught by these teachers. Results indicate that the flow-based music programming environment provided an engaging programming experience for students and significantly increased their self-efficacy towards learning programming.
Predictive modelling in drug discovery is challenging to automate as it often contains multiple analysis steps and might involve cross-validation and parameter tuning that create complex dependencies between tasks. Wi...
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Predictive modelling in drug discovery is challenging to automate as it often contains multiple analysis steps and might involve cross-validation and parameter tuning that create complex dependencies between tasks. With large-scale data or when using computationally demanding modelling methods, e-infrastructures such as high-performance or cloud computing are required, adding to the existing challenges of fault-tolerant automation. Workflow management systems can aid in many of these challenges, but the currently available systems are lacking in the functionality needed to enable agile and flexible predictive modelling. We here present an approach inspired by elements of the flow-based programming paradigm, implemented as an extension of the Luigi system which we name SciLuigi. We also discuss the experiences from using the approach when modelling a large set of biochemical interactions using a shared computer cluster.
In this article, we show a flow-based programming environment for interactive geometry software. flow-based programming is one of the programming paradigms. All of the processes and data are represented as nodes, and ...
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ISBN:
(数字)9783030522001
ISBN:
(纸本)9783030522001
In this article, we show a flow-based programming environment for interactive geometry software. flow-based programming is one of the programming paradigms. All of the processes and data are represented as nodes, and we connect processes and data with edges. We call the figure with nodes and edges graph because the figure looks like a planar graph. There is a lot of software implementing flow-based programming. However, there are few mathematical software based on a flow-based programming environment. So, we develop experimental interactive geometry software to generate kaleidoscope patterns based on flow-based programming. The software shows us some advantages of flow-based programming. First, it is easy to understand the procedure of construction. Second, flow-based programming is flexible. Third, flow-based programming has high extensibility. We seek possibilities of practical use of the geometrical construction software with flow-based programming.
Over the past few years, there has been an increasing demand for crowd sensing applications. While existing mobile app designers greatly facilitate the development of crowd sensing applications for non-ICT experts, th...
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ISBN:
(纸本)9781509026258
Over the past few years, there has been an increasing demand for crowd sensing applications. While existing mobile app designers greatly facilitate the development of crowd sensing applications for non-ICT experts, they do not yet provide technological support for other aspects required to manage crowd sensing applications, such as support for data gathering campaigns, advanced forms of data aggregation, and participant coordination. In this paper, we present DisCoPar, a novel platform for designing crowd sensing applications, which utilises a distributed flow-based programming approach to facilitate the development of mobile applications and their matching serverside logic. The data-driven nature of our approach enables users to contribute data and receive feedback in real-time, which greatly facilitates user collaboration. We demonstrate the features of our prototype platform by creating a noise measuring application with a corresponding collaborative data collection campaign.
Software plays an increasingly important role in our daily lives. The development of this software is complex and hard to understand by non-professionals. Fundamental knowledge about programming languages and software...
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ISBN:
(纸本)9781450389976
Software plays an increasingly important role in our daily lives. The development of this software is complex and hard to understand by non-professionals. Fundamental knowledge about programming languages and software structure is required to change it. By changing the logical complexity represented in software code in something more intuitively understandable, like graphical elements, even non-professionals can understand and learn to design software. Systems that are inspired by flow-based programming offer an interesting approach to this problem. This paper presents two pattern and five pattern candidates, which are a distillation from practices that are already in use. The presented pattern are Functions as building blocks and Connect building blocks. These pattern are used in established products like Node-Red[3] or n8n[2].
Software plays an increasingly important role in our daily lives. The development of this software is complex and hard to understand by non-professionals. Fundamental knowledge about programming languages and software...
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ISBN:
(纸本)9781450389976
Software plays an increasingly important role in our daily lives. The development of this software is complex and hard to understand by non-professionals. Fundamental knowledge about programming languages and software structure is required to change it. By changing the logical complexity represented in software code in something more intuitively understandable, like graphical elements, even non-professionals can understand and learn to design software. Systems that are inspired by flow-based programming offer an interesting approach to this problem. This paper presents two pattern and five pattern candidates, which are a distillation from practices that are already in use. The presented pattern are Functions as building blocks and Connect building blocks. These pattern are used in established products like Node-Red[3] or n8n[2].
Increased sensing data in the context of the Internet of Things (IoT) necessitates data analytics. It is challenging to write applications for Big Data systems due to complex, highly parallel software frameworks and s...
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Increased sensing data in the context of the Internet of Things (IoT) necessitates data analytics. It is challenging to write applications for Big Data systems due to complex, highly parallel software frameworks and systems. The inherent complexity in programming Big Data applications is also due to the presence of a wide range of target frameworks, with different data abstractions and APIs. The paper aims to reduce this complexity and its ensued learning curve by enabling domain experts, that are not necessarily skilled Big Data programmers, to develop data analytics applications via domain-specific graphical tools. The approach follows the flow-based programming paradigm used in IoT mashup tools. The paper contributes to these aspects by (i) providing a thorough analysis and classification of the widely used Spark framework and selecting suitable data abstractions and APIs for use in a graphical flow-based programming paradigm and (ii) devising a novel, generic approach for programming Spark from graphical flows that comprises early-stage validation and code generation of Spark applications. Use cases for Spark have been prototyped and evaluated to demonstrate code-abstraction, automatic data abstraction interconversion and automatic generation of target Spark programs, which are the keys to lower the complexity and its ensued learning curve involved in the development of Big Data applications.
Current architectural Design-Space Exploration (DSE) tools specify the exploration problem through annotations or pragmas. However, this approach is inherently language-dependent and limits the applicability to one sp...
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Current architectural Design-Space Exploration (DSE) tools specify the exploration problem through annotations or pragmas. However, this approach is inherently language-dependent and limits the applicability to one specific target language and synthesis toolchain. Additionally, the rapid development of new hardware Domain-Specific Languages, programming models, and different exploration heuristics calls for a language-agnostic and modular approach. To address this need, we present a DSE formalization to facilitate the integration of new components and customized flows and leverage it to implement Dflows, a flow-based-programming DSE tool that decouples problem definition, code generation, exploration, and evaluation strategies. Dflows’s compiler-based frontend provides language-agnostic generation of design points through Abstract Syntax Tree manipulation. We show how Dflows can integrate custom performance models from complex state-of-the-art accelerators for Verilog, VHDL, Chisel, and HLS designs. We compare the runtimes of our DSE process against a state-of-the-art Chisel-based DSE tool, achieving up to 3.74× speedup while identifying the same set of optimal solutions. Additionally, we integrate in Dflows a custom exploration heuristic leveraging genetic algorithms and a novel online learning fitness function approximation methodology. This approximation yields a negligible hypervolume difference with the exhaustive search Pareto-front while improving DSE runtime by up to 2.67×.
Teaching computer programming to children and adolescents has become popular in recent years. This popularity has resulted in increased research into techniques for teaching introductory programming using visual langu...
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Teaching computer programming to children and adolescents has become popular in recent years. This popularity has resulted in increased research into techniques for teaching introductory programming using visual languages, especially block-based languages. This study aims to explore new possibilities for teaching programming by adopting a hybrid environment between the descriptive and flow-oriented paradigm. The use of the Semiotic Engineering's Communicability Evaluation Method (CEM), a theoretical line of Human-Computer Interaction based on communication, was applied to assess its usefulness to a high school audience. The teaching activities took place in cycles, with successive refinements, forming an action-research strategy. In this way, we conducted a descriptive case study with a qualitative analysis of the data, in which we collected a participant observation scheme. Our results established that the use of CEM in education was appropriate, that the proposed environment was suitable for the study, and the topics were relevant to the target audience.
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