Intelligent Interleaving of Scenarios: A Novel Approach to System Level Test Generation

2007 ◽  
Author(s):  
Shady Copty ◽  
Itai Jaeger ◽  
Yoav Katz ◽  
Michael Vinov
Keyword(s):  
Test Generation ◽  
System Level ◽  
Novel Approach

scholarly journals Microstructural and Functional Gradients are Increasingly Dissociated in Transmodal Cortices

2018 ◽  
Author(s):  
Casey Paquola ◽  
Reinder Vos De Wael ◽  
Konrad Wagstyl ◽  
Richard A.I. Bethlehem ◽  
Seok-Jun Hong ◽  
...  
Keyword(s):  
System Level ◽  
Human Cognition ◽  
Neural Function ◽  
Structural Constraints ◽  
Primate Research ◽  
Novel Approach ◽  
Novel Method ◽  
And Function ◽  
The Relationship

SummaryWhile the role of cortical microstructure in organising neural function is well established, it remains unclear how structural constraints can give rise to more flexible elements of cognition. While non-human primate research has demonstrated a close structure-function correspondence, the relationship between microstructure and function remains poorly understood in humans, in part because of the reliance onpost mortemanalyses which cannot be directly related to functional data. To overcome this barrier, we developed a novel approach to model the similarity of microstructural profiles sampled in the direction of cortical columns. Our approach was initially formulated based on an ultra-high-resolution 3D histological reconstruction of an entire human brain and then translated to myelin-sensitive MRI data in a large cohort of healthy adults. This novel method identified a system-level gradient of microstructural differentiation traversing from primary sensory to limbic regions that followed shifts in laminar differentiation and cytoarchitectural complexity. Importantly, while microstructural and functional gradients described a similar hierarchy, they became increasingly dissociated in transmodal default mode and fronto-parietal networks. Meta analytic decoding of these topographic dissociations highlighted involvement in higher-level aspects of cognition such as cognitive control and social cognition. Our findings demonstrate a relative decoupling of macroscale functional from microstructural gradients in transmodal regions, which likely contributes to the flexible role these regions play in human cognition.

scholarly journals Adaptive Hypermutation for Search-Based System Test Generation: A Study on REST APIs with EvoMaster

2022 ◽  
Vol 31 (1) ◽  
pp. 1-52
Author(s):  
Man Zhang ◽  
Andrea Arcuri
Keyword(s):  
Test Generation ◽  
Novel Mutation ◽  
System Level ◽  
Mutation Operator ◽  
System Testing ◽  
Fitness Evaluation ◽  
Branch Coverage ◽  
Adaptive Weight ◽  
Rest Api ◽  
Different Characteristics

REST web services are widely popular in industry, and search techniques have been successfully used to automatically generate system-level test cases for those systems. In this article, we propose a novel mutation operator which is designed specifically for test generation at system-level, with a particular focus on REST APIs. In REST API testing, and often in system testing in general, an individual can have a long and complex chromosome. Furthermore, there are two specific issues: (1) fitness evaluation in system testing is highly costly compared with the number of objectives (e.g., testing targets) to optimize for; and (2) a large part of the genotype might have no impact on the phenotype of the individuals (e.g., input data that has no impact on the execution flow in the tested program). Due to these issues, it might be not suitable to apply a typical low mutation rate like 1/ n (where n is the number of genes in an individual), which would lead to mutating only one gene on average. Therefore, in this article, we propose an adaptive weight-based hypermutation, which is aware of the different characteristics of the mutated genes. We developed adaptive strategies that enable the selection and mutation of genes adaptively based on their fitness impact and mutation history throughout the search. To assess our novel proposed mutation operator, we implemented it in the EvoMaster tool, integrated in the MIO algorithm, and further conducted an empirical study with three artificial REST APIs and four real-world REST APIs. Results show that our novel mutation operator demonstrates noticeable improvements over the default MIO. It provides a significant improvement in performance for six out of the seven case studies, where the relative improvement is up to +12.09% for target coverage, +12.69% for line coverage, and +32.51% for branch coverage.

Architecting the Cooperative 3D Printing System

2020 ◽  
Author(s):  
Laxmi Poudel ◽  
Lucas Galvan Marques ◽  
Robert Austin Williams ◽  
Zachary Hyden ◽  
Pablo Guerra ◽  
...  
Keyword(s):  
3D Printing ◽  
Mobile Platform ◽  
System Level ◽  
New Developments ◽  
Fully Integrated ◽  
Charging Station ◽  
Novel Approach ◽  
G Code ◽  
3D Printers ◽  
Printing System

Abstract Cooperative 3D printing (C3DP) is a novel approach to additive manufacturing, where multiple mobile 3D printing robots work together cooperatively to print the desired part. At the core of C3DP lies the chunk-based printing strategy. This strategy splits the desired part into smaller chunks, and then the chunks are assigned and scheduled to be printed by individual printing robots. In our previous work, we presented various hardware and software components of C3DP, such as mobile 3D printers, chunk-based slicing, scheduling, and simulation. In this study, we present a fully integrated and functional C3DP platform with all necessary components, including chunker, slicer, scheduler, printing robots, build floor, and outline how they work in unison from a system-level perspective. To realize C3DP, new developments of both hardware and software are presented, including new chunking approaches, scalable scheduler for multiple robots, SCARA-based printing robots, a mobile platform for transporting printing robots, modular floor tiles, and a charging station for the mobile platform. Finally, we demonstrate the capability of the system using two case studies. In these demonstrations, a CAD model of a part is fed to the chunker, divided into smaller chunks, passed to the scheduler, and assigned and scheduled to be printed by the scheduler with a given number of robots. The slicer generates G-code for each of the chunks and combines G-code into one file for each robot. The simulator then uses the G-code generated by the slicer to generate animations for visualization purposes.

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