SEMKIS-DSL: A Domain-Specific Language to Support Requirements Engineering of Datasets and Neural Network Recognition

in Information (2023), 14(4),

Neural network (NN) components are being increasingly incorporated into software systems. Neural network properties are determined by their architecture, as well as the training and testing datasets used ... [more ▼]

Neural network (NN) components are being increasingly incorporated into software systems. Neural network properties are determined by their architecture, as well as the training and testing datasets used. The engineering of datasets and neural networks is a challenging task that requires methods and tools to satisfy customers’ expectations. The lack of tools that support requirements specification languages makes it difficult for engineers to describe dataset and neural network recognition skill requirements. Existing approaches often rely on traditional ad hoc approaches, without precise requirement specifications for data selection criteria, to build these datasets. Moreover, these approaches do not focus on the requirements of the neural network’s expected recognition skills. We aim to overcome this issue by defining a domain-specific language that precisely specifies dataset requirements and expected recognition skills after training for an NN-based system. In this paper, we present a textual domain-specific language (DSL) called SEMKIS-DSL (Software Engineering Methodology for the Knowledge management of Intelligent Systems) that is designed to support software engineers in specifying the requirements and recognition skills of neural networks. This DSL is proposed in the context of our general SEMKIS development process for neural network engineering. We illustrate the DSL’s concepts using a running example that focuses on the recognition of handwritten digits. We show some requirements and recognition skills specifications and demonstrate how our DSL improves neural network recognition skills. [less ▲]

Formal Verification of Ecosystem Restoration Requirements using UML and Alloy

Report (2023)

United Nations have declared the current decade (2021-2030) as the ”UN Decade on Ecosystem Restoration” to join R&D forces to fight against the ongoing environmental crisis. Given the ongoing degradation ... [more ▼]

United Nations have declared the current decade (2021-2030) as the ”UN Decade on Ecosystem Restoration” to join R&D forces to fight against the ongoing environmental crisis. Given the ongoing degradation of earth ecosystems and the related crucial services that they offer to the human society, ecosystem restoration has become a major society-critical issue. It is required to develop rigorously software applications managing ecosystem restoration. Reliable models of ecosystems and restoration goals are necessary. This paper proposes a rigorous approach for ecosystem requirements modeling using formal methods from a model-driven software engineering point of view. The authors describe the main concepts at stake with a metamodel in UML and introduce a formalization of this metamodel in Alloy. The formal model is executed with Alloy Analyzer, and safety and liveness properties are checked against it. This approach helps ensuring that ecosystem specifications are reliable and that the specified ecosystem meets the desired restoration goals, seen in our approach as liveness and safety properties. The concepts and activities of the approach are illustrated with CRESTO, a real-world running example of a restored Costa Rican ecosystem. [less ▲]

SEMKIS-DSL: a Domain-Specific Language for Specifying Neural Networks’ Key-Properties

Report (2021)

Neural networks are becoming increasingly part of today’s software systems. These neural networks are simplified models of the human brain that are mainly capable of learning from large datasets to ... [more ▼]

Neural networks are becoming increasingly part of today’s software systems. These neural networks are simplified models of the human brain that are mainly capable of learning from large datasets to compute some function based on recognized data. Engineering these datasets and these neural network-based software systems is a complicated and challenging task. Software engineers require methods and tools to engineer these datasets and neural networks for their customers and to satisfy their requirements. In general, they lack methods and tools to support the engineering of dataset and neural networks that satisfy the customer’s requirements. They follow traditional approaches consisting of time-consuming, imprecise and manual activities. Typically, these approaches are not supported by any tool that precisely analyse and specify the neural network’s recognition skills. In our previous work, we have introduced the notion of key-properties for describing the neural network’s recognition skills. In this paper, we define a domain-specific language to support our SEMKIS software engineering methodology for the dataset augmentation to improve network’s key-properties. We present the SEMKIS-DSL for the specification of the key-properties of a neural network. We illustrate the concepts of our DSL with a running example specifying a neural network for recognizing a digital meter counter state. This running example demonstrates a specification of the neural network’s key-properties using the SEMKIS-DSL and a successful improvement of the neural network’s recognition skills. [less ▲]

Specifying key-properties to improve the recognition skills of neural networks

in Proceedings of the 2020 European Symposium on Software Engineering (2020, November 06)

Software engineers are increasingly asked to build datasets for engineering neural network-based software systems. These datasets are used to train neural networks to recognise data. Traditionally, data ... [more ▼]

Software engineers are increasingly asked to build datasets for engineering neural network-based software systems. These datasets are used to train neural networks to recognise data. Traditionally, data scientists build datasets consisting of random collected or generated data. Their approaches are often costly, inefficient and time-consuming. Software engineers rely on these traditional approaches that do not support precise data selection criteria based on customer’s requirements. In this paper, we introduce an extended software engineering method for dataset augmentation to improve neural networks by satisfying the customer’s requirements. We introduce the notion of key-properties to describe the neural network’s recognition skills. Key-properties are used all along the engineering process for developing the neural network in cooperation with the customer. We propose a rigorous process for augmenting datasets based on the analysis and specification of the key-properties. We conducted an experimentation on a case study on the recognition of the state of a digital meter counter. We demonstrate an informal specification of the neural network’s key-properties and a successful improvement of a neural network’s recognition of the meter counter state. [less ▲]

Teaching DevOps in Academia and Industry: Reflections and Vision

in Bruel, Jean-Michel; Mazzara, Manuel; Meyer, Bertrand (Eds.) Software Engineering Aspects of Continuous Development and New Paradigms of Software Production and Deployment (2020, January 19)

The new century brought us a kind of renaissance in software development methods. The advent of the Agile manifesto has led to greater appreciation of methodologies aimed at producing valuable software ... [more ▼]

The new century brought us a kind of renaissance in software development methods. The advent of the Agile manifesto has led to greater appreciation of methodologies aimed at producing valuable software through continuous incremental cycles. More recently, a new set of practices enclosed under the term DevOps has appeared to attain manifesto's objectives in more efficient manner. The software development community has already noticed the benefits brought by DevOps. Thus, the necessity of education in the field becomes more and more important, both from the technical and organisational point of view. This paper describes parallel experiences of teaching both undergraduate and graduate students at the university, and junior professional developers in industry, compares the two approaches and sums up the lessons learnt. A vision driven by the DevOps practices aimed at implementing a shift in the Software Engineering Higher Education curricula to takeover its current limitations is also reported at the end of the paper. [less ▲]

Analysing the SWECOM and DDaT standards for designing a DevOps course content

Presentation (2019, November)

DevOps and its Philosophy : Education Matters!

Report (2019)

DevOps processes comply with principles and offer practices with main objective to support efficiently the evolution of IT systems. To be efficient a DevOps process relies on a set of integrated tools ... [more ▼]

DevOps processes comply with principles and offer practices with main objective to support efficiently the evolution of IT systems. To be efficient a DevOps process relies on a set of integrated tools. DevOps is among the first competencies together with Agile method required by the industry. As a new approach it is necessary to develop and offer to the academy and to the industry training programs to prepare our engineers in the best possible way. In this chapter we present the main aspects of the educational effort made in the recent years to educate to the concepts and values of the DevOps philosophy. This includes principles, practices, tools and architectures, primarily the microservices architectural style, which shares many aspects of DevOps approaches especially the modularity and flexibility which enables continuous change and delivery. Two experiences have been made, one at academic level as a master program course and the other, as an industrial training. Based on those two experiences, we provide a comparative analysis and some proposals in order to develop and improve DevOps education for the future. [less ▲]

Design of a (yet another?) DevOps course

in Bruel, Jean-Michel; Mazzara, Manuel; Meyer, Bertrand (Eds.) Software Engineering Aspects of Continuous Development and New Paradigms of Software Production and Deployment (2019, January 19)

DevOps have received marginal attention inside the higher education level curricula despite of its boom in the industrial sector. This paper presents the design of an academic master-level course aimed at ... [more ▼]

DevOps have received marginal attention inside the higher education level curricula despite of its boom in the industrial sector. This paper presents the design of an academic master-level course aimed at DevOps. The proposed design is based on earlier experiences in teaching DevOps-related topics. The specification of the course design is provided using the SWEBOK Guide and Bloom’s taxonomy to enhance the quality of the course design specification, and ease its assessment once delivered. [less ▲]

Messir: A Text-First DSL-Based Approach for UML Requirements Engineering (Tool Demo), in ACM SIGPLAN conference on Systems, Programming, Languages and Applications: Software for Humanity (SPLASH)

Poster (2018)

ABSTRA

Messir: A Text-First DSL-Based Approach for UML Requirements Engineering (Tool Demo)

in Proceedings of the 11th ACM SIGPLAN International Conference on Software Language Engineering SLE'18 (2018)