DSLs for Decision Services: A Tutorial Introduction to Language-Driven Engineering

Gossen, Frederik; Margaria, Tiziana; Murtovi, Alnis; Naujokat, Stefan; Steffen, Bernhard

doi:10.1007/978-3-030-03418-4_33

Cited by 15 publications

(8 citation statements)

References 12 publications

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“…In fact, the classification times eventually stabilise for D D * , illustrating the key feature of Random Forests, the reduction of the learner's variance. 13 As sketched in Tables 1 and 2, these observations carry over to other popular data sets in the UCI Machine Learning Repository [8].…”

Section: Experimental Performance Evaluationmentioning

confidence: 88%

“…For the Iris flower example, these are 150 records, a number that also explains the quite smooth result graphs. Our implementation relies on the standard Random Forest implementation in Weka [37] and on the ADD implementation of the ADD-Lib [13,14,33]. Please note that the considered data sets have been developed with evaluations of this kind in mind by independent parties, and that we are not using any additional data for our transformation.…”

Section: Experimental Performance Evaluationmentioning

confidence: 99%

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Algebraic aggregation of random forests: towards explainability and rapid evaluation

Gossen

Steffen

2021

Int J Softw Tools Technol Transfer

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Random Forests are one of the most popular classifiers in machine learning. The larger they are, the more precise the outcome of their predictions. However, this comes at a cost: it is increasingly difficult to understand why a Random Forest made a specific choice, and its running time for classification grows linearly with the size (number of trees). In this paper, we propose a method to aggregate large Random Forests into a single, semantically equivalent decision diagram which has the following two effects: (1) minimal, sufficient explanations for Random Forest-based classifications can be obtained by means of a simple three step reduction, and (2) the running time is radically improved. In fact, our experiments on various popular datasets show speed-ups of several orders of magnitude, while, at the same time, also significantly reducing the size of the required data structure.

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Section: Experimental Performance Evaluationmentioning

confidence: 88%

Section: Experimental Performance Evaluationmentioning

confidence: 99%

Algebraic aggregation of random forests: towards explainability and rapid evaluation

Gossen

Steffen

2021

Int J Softw Tools Technol Transfer

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“…The native and process DSLs have been previously applied also to robotic scenarios [19], and [18] shows how to craft REST services and cloud services in the DIME environment. In [15] we also adopted the ADD-Lib [12] for policy definition. The policies designed with ADD-lib translate to efficient code that is integrated in DIME through its Native DSL mechanism.…”

Section: Edgex Foundry As Iiot Middleware Platformmentioning

confidence: 99%

“…5. What changes are the specific access policies for the PreMS from Table 1, which we will again define using the low code model driven development tool ADD-Lib [12] and the surrounding PreMS application logic.…”

Section: Secure Access Policy For Premsmentioning

confidence: 99%

DSLs and Middleware Platforms in a Model-Driven Development Approach for Secure Predictive Maintenance Systems in Smart Factories

John

Ghosal²,

Margaria

et al. 2021

Lecture Notes in Computer Science

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In many industries, traditional automation systems (operating technology) such as PLCs are being replaced with modern, networked ICT-based systems as part of a drive towards the Industrial Internet of Things (IIoT). The intention behind this is to use more cost-effective, open platforms that also integrate better with an organisation’s information technology (IT) systems. In order to deal with heterogeneity in these systems, middleware platforms such as EdgeX Foundry, IoTivity, FI-WARE for Internet of Things (IoT) systems are under development that provide integration and try to overcome interoperability issues between devices of different standards. In this paper, we consider the EdgeX Foundry IIoT middleware platform as a transformation engine between field devices and enterprise applications. We also consider security as a critical element in this and discuss how to prevent or mitigate the possibility of several security risks. Here we address secure data access control by introducing a declarative policy layer implementable using Ciphertext-Policy Attribute-Based Encryption (CP-ABE). Finally, we tackle the interoperability challenge at the application layer by connecting EdgeX with DIME, a model-driven/low-code application development platform that provides methods and techniques for systematic integration based on layered Domain-Specific Languages (DSL). Here, EdgeX services are accessed through a Native DSL, and the application logic is designed in the DIME Language DSL, lifting middleware development/configuration to a DSL abstraction level. Through the use of DSLs, this approach covers the integration space domain by domain, technology by technology, and is thus highly generalizable and reusable. We validate our approach with an example IIoT use case in smart manufacturing.

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“…255] 3 . This example originates from an email classification service that assigns colors to emails based on some importance criterion [14]. It is shown here solely to illustrate the flexibility of ADDs.…”

Section: Decision Diagramsmentioning

confidence: 99%

ADD-Lib: Decision Diagrams in Practice

Gossen¹,

Murtovi²,

Zweihoff³

et al. 2019

Preprint

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In the paper, we present the ADD-Lib, our efficient and easy to use framework for Algebraic Decision Diagrams (ADDs). The focus of the ADD-Lib is not so much on its efficient implementation of individual operations, which are taken by other established ADD frameworks, but its ease and flexibility, which arise at two levels: the level of individual ADD-tools, which come with a dedicated user-friendly webbased graphical user interface, and at the meta level, where such tools are specified. Both levels are described in the paper: the meta level by explaining how we can construct an ADD-tool tailored for Random Forest refinement and evaluation, and the accordingly generated Web-based domain-specific tool, which we also provide as an artifact for cooperative experimentation. In particular, the artifact allows readers to combine a given Random Forest with their own ADDs regarded as expert knowledge and to experience the corresponding effect.

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DSLs for Decision Services: A Tutorial Introduction to Language-Driven Engineering

Cited by 15 publications

References 12 publications

Algebraic aggregation of random forests: towards explainability and rapid evaluation

Algebraic aggregation of random forests: towards explainability and rapid evaluation

DSLs and Middleware Platforms in a Model-Driven Development Approach for Secure Predictive Maintenance Systems in Smart Factories

ADD-Lib: Decision Diagrams in Practice

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