scholarly journals Automatic generation of atomic multiplicity-preserving search operators for search-based model engineering

2021 ◽  
Author(s):  
Alexandru Burdusel ◽  
Steffen Zschaler ◽  
Stefan John
Keyword(s):  
Heuristic Search ◽  
Automatic Generation ◽  
Model Transformations ◽  
Evolutionary Search ◽  
Optimal Solutions ◽  
Model Driven ◽  
Mutation Operators ◽  
Domain Expertise ◽  
Effectiveness And Efficiency ◽  
Better Than

AbstractRecently, there has been increased interest in combining model-driven engineering and search-based software engineering. Such approaches use meta-heuristic search guided by search operators (model mutators and sometimes breeders) implemented as model transformations. The design of these operators can substantially impact the effectiveness and efficiency of the meta-heuristic search. Currently, designing search operators is left to the person specifying the optimisation problem. However, developing consistent and efficient search-operator rules requires not only domain expertise but also in-depth knowledge about optimisation, which makes the use of model-based meta-heuristic search challenging and expensive. In this paper, we propose a generalised approach to automatically generate atomic multiplicity-preserving search operators for a given optimisation problem. This reduces the effort required to specify an optimisation problem and shields optimisation users from the complexity of implementing efficient meta-heuristic search mutation operators. We evaluate our approach with a set of case studies and show that the automatically generated rules are comparable to, and in some cases better than, manually created rules at guiding evolutionary search towards near-optimal solutions.

scholarly journals Resource and dependency based test case generation for RESTful Web services

2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Man Zhang ◽  
Bogdan Marculescu ◽  
Andrea Arcuri
Keyword(s):  
Web Services ◽  
Domain Knowledge ◽  
Automated System ◽  
Test Case ◽  
Test Cases ◽  
Evolutionary Search ◽  
Sampling Strategies ◽  
Mutation Operators ◽  
On Line ◽  
Restful Web Services

AbstractNowadays, RESTful web services are widely used for building enterprise applications. REST is not a protocol, but rather it defines a set of guidelines on how to design APIs to access and manipulate resources using HTTP over a network. In this paper, we propose an enhanced search-based method for automated system test generation for RESTful web services, by exploiting domain knowledge on the handling of HTTP resources. The proposed techniques use domain knowledge specific to RESTful web services and a set of effective templates to structure test actions (i.e., ordered sequences of HTTP calls) within an individual in the evolutionary search. The action templates are developed based on the semantics of HTTP methods and are used to manipulate the web services’ resources. In addition, we propose five novel sampling strategies with four sampling methods (i.e., resource-based sampling) for the test cases that can use one or more of these templates. The strategies are further supported with a set of new, specialized mutation operators (i.e., resource-based mutation) in the evolutionary search that take into account the use of these resources in the generated test cases. Moreover, we propose a novel dependency handling to detect possible dependencies among the resources in the tested applications. The resource-based sampling and mutations are then enhanced by exploiting the information of these detected dependencies. To evaluate our approach, we implemented it as an extension to the EvoMaster tool, and conducted an empirical study with two selected baselines on 7 open-source and 12 synthetic RESTful web services. Results show that our novel resource-based approach with dependency handling obtains a significant improvement in performance over the baselines, e.g., up to + 130.7% relative improvement (growing from + 27.9% to + 64.3%) on line coverage.

scholarly journals Learn-CIAM: A Model-Driven Approach for the Development of Collaborative Learning Tools

2021 ◽  
Vol 11 (6) ◽  
pp. 2554
Author(s):  
Yoel Arroyo ◽  
Ana I. Molina ◽  
Miguel A. Redondo ◽  
Jesús Gallardo
Keyword(s):  
Collaborative Learning ◽  
Methodological Approach ◽  
Automatic Generation ◽  
Learning Activities ◽  
Learning Tools ◽  
Model Driven ◽  
Collaborative Tools ◽  
Learning Tasks ◽  
Collaborative Learning Tools ◽  
Model Driven Approach

This paper introduces Learn-CIAM, a new model-based methodological approach for the design of flows and for the semi-automatic generation of tools in order to support collaborative learning tasks. The main objective of this work is to help professors by establishing a series of steps for the specification of their learning courses and the obtaining of collaborative tools to support certain learning activities (in particular, for in-group editing, searching and modeling). This paper presents a complete methodological framework, how it is supported conceptually and technologically, and an application example. So to guarantee the validity of the proposal, we also present some validation processes with potential designers and users from different profiles such as Education and Computer Science. The results seem to demonstrate a positive reception and acceptance, concluding that its application would facilitate the design of learning courses and the generation of collaborative learning tools for professionals of both profiles.

scholarly journals ALBA: a model-driven framework for the automatic generation of android location-based apps

2021 ◽  
Vol 28 (1) ◽  
Author(s):  
Mohammadali Gharaat ◽  
Mohammadreza Sharbaf ◽  
Bahman Zamani ◽  
Abdelwahab Hamou-Lhadj
Keyword(s):  
Automatic Generation ◽  
Model Driven

Automatic tourist attraction and representative icon determination for tourist map generation

2013 ◽  
Vol 13 (1) ◽  
pp. 18-28 ◽  
Author(s):  
Chao-Hung Lin ◽  
Jyun-Yuan Chen ◽  
Shun-Siang Hsu ◽  
Yun-Huan Chung
Keyword(s):  
User Study ◽  
Three Dimensional ◽  
Automatic Generation ◽  
Visual Features ◽  
Tourist Attraction ◽  
Tourist Attractions ◽  
Photo Sharing ◽  
Map Generation ◽  
Three Dimensional Models ◽  
Better Than

Tourist maps are designed to direct tourists to tourist attractions in unfamiliar areas. A well-designed tourist map can provide tourists with sufficient and intuitive information about places of interest. Thus, providing up-to-date information on places of interest and selecting their representative icons are fundamental and important in automatic generation of tourist maps. In this article, approaches for determining places of interest and for determining their representative icons are introduced. In contrast to general digital tourist maps that use text, simple shapes, or three-dimensional models, we use photos that offer abundant visual features of places of interest as icons in tourist maps. The photos are automatically extracted from a repository of photos downloaded from photo-sharing communities. Tourist attractions and their corresponding image icons are determined by means of photo voting and photo quality assessment. Qualitative analyses, including a user study and experiments in several areas with numerous tourist attractions, indicated that the proposed method can generate visually pleasant and elaborate tourist maps. In addition, the analyses indicated that the map produced by our method is better than maps generated by related methods and is comparable to hand-designed tourist maps.

scholarly journals Day-Ahead Forecasting of Hourly Photovoltaic Power Based on Robust Multilayer Perception

2018 ◽  
Vol 10 (12) ◽  
pp. 4863 ◽  
Author(s):  
Chao Huang ◽  
Longpeng Cao ◽  
Nanxin Peng ◽  
Sijia Li ◽  
Jing Zhang ◽  
...  
Keyword(s):  
Power Plants ◽  
Mean Squared Error ◽  
Absolute Error ◽  
Multilayer Perception ◽  
Squared Error ◽  
The Mean ◽  
Effectiveness And Efficiency ◽  
Mlp Network ◽  
Grid Operation ◽  
Better Than

Photovoltaic (PV) modules convert renewable and sustainable solar energy into electricity. However, the uncertainty of PV power production brings challenges for the grid operation. To facilitate the management and scheduling of PV power plants, forecasting is an essential technique. In this paper, a robust multilayer perception (MLP) neural network was developed for day-ahead forecasting of hourly PV power. A generic MLP is usually trained by minimizing the mean squared loss. The mean squared error is sensitive to a few particularly large errors that can lead to a poor estimator. To tackle the problem, the pseudo-Huber loss function, which combines the best properties of squared loss and absolute loss, was adopted in this paper. The effectiveness and efficiency of the proposed method was verified by benchmarking against a generic MLP network with real PV data. Numerical experiments illustrated that the proposed method performed better than the generic MLP network in terms of root mean squared error (RMSE) and mean absolute error (MAE).

scholarly journals Generating Collaborative Systems for Digital Libraries: a Model-Driven Approach

2010 ◽  
Vol 29 (4) ◽  
pp. 171 ◽  
Author(s):  
Alessio Malizia ◽  
Paolo Bottoni ◽  
S. Levialdi
Keyword(s):  
Digital Library ◽  
User Interfaces ◽  
Digital Libraries ◽  
Automatic Generation ◽  
Visual Language ◽  
Domain Experts ◽  
Model Driven ◽  
Neutral Models ◽  
Definition Of ◽  
High Level

The design and development of a digital library involves different stakeholders, such as: information architects, librarians, and domain experts, who need to agree on a common language to describe, discuss, and negotiate the services the library has to offer. To this end, high-level, language-neutral models have to be devised. Metamodeling techniques favor the definition of domainspecific visual languages through which stakeholders can share their views and directly manipulate representations of the domain entities. This paper describes CRADLE (Cooperative-Relational Approach to Digital Library Environments), a metamodel-based framework and visual language for the definition of notions and services related to the development of digital libraries. A collection of tools allows the automatic generation of several services, defined with the CRADLE visual language, and of the graphical user interfaces providing access to them for the final user. The effectiveness of the approach is illustrated by presenting digital libraries generated with CRADLE, while the CRADLE environment has been evaluated by using the cognitive dimensions framework.

ANALYSIS OF MUTATION OPERATORS ON QUANTUM-BEHAVED PARTICLE SWARM OPTIMIZATION ALGORITHM

2009 ◽  
Vol 05 (02) ◽  
pp. 487-496 ◽  
Author(s):  
WEI FANG ◽  
JUN SUN ◽  
WENBO XU
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm Optimization Algorithm ◽  
Novel Mutation ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Mutation Operator ◽  
Fundamental Theory ◽  
Swarm Optimization ◽  
Mutation Operators ◽  
Better Than

Mutation operator is one of the mechanisms of evolutionary algorithms (EAs) and it can provide diversity in the search and help to explore the undiscovered search place. Quantum-behaved particle swarm optimization (QPSO), which is inspired by fundamental theory of PSO algorithm and quantum mechanics, is a novel stochastic searching technique and it may encounter local minima problem when solving multi-modal problems just as that in PSO. A novel mutation mechanism is proposed in this paper to enhance the global search ability of QPSO and a set of different mutation operators is introduced and implemented on the QPSO. Experiments are conducted on several well-known benchmark functions. Experimental results show that QPSO with some of the mutation operators is proven to be statistically significant better than the original QPSO.

scholarly journals Comparison Between Internal and External DSLs via RubyTL and Gra2MoL

2012 ◽  
pp. 109-131 ◽  
Author(s):  
Jesús Sánchez Cuadrado ◽  
Javier Luis Cánovas Izquierdo ◽  
Jesús García Molina
Keyword(s):  
Empirical Studies ◽  
Lessons Learned ◽  
The Other ◽  
Model Transformations ◽  
Domain Specific Languages ◽  
Model Driven ◽  
Domain Specific ◽  
Advantages And Disadvantages

Domain Specific Languages (DSL) are becoming increasingly more important with the emergence of Model-Driven paradigms. Most literature on DSLs is focused on describing particular languages, and there is still a lack of works that compare different approaches or carry out empirical studies regarding the construction or usage of DSLs. Several design choices must be made when building a DSL, but one important question is whether the DSL will be external or internal, since this affects the other aspects of the language. This chapter aims to provide developers confronting the internal-external dichotomy with guidance, through a comparison of the RubyTL and Gra2MoL model transformations languages, which have been built as an internal DSL and an external DSL, respectively. Both languages will first be introduced, and certain implementation issues will be discussed. The two languages will then be compared, and the advantages and disadvantages of each approach will be shown. Finally, some of the lessons learned will be presented.

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