A three-dimensional view model of open source-aware software development for large-scale mobile software platforms

2010 ◽  
Author(s):  
Toshihiko Yamakami
Keyword(s):  
Software Development ◽  
Open Source ◽  
Large Scale ◽  
Three Dimensional ◽  
Mobile Software ◽  
Software Platforms

Logging Analysis and Prediction in Open Source Java Project

2021 ◽  
pp. 733-761
Author(s):  
Sangeeta Lal ◽  
Neetu Sardana ◽  
Ashish Sureka
Keyword(s):  
Machine Learning ◽  
Content Analysis ◽  
Software Development ◽  
Anomaly Detection ◽  
Open Source ◽  
Large Scale ◽  
Source Code ◽  
Scale Analysis ◽  
Large Scale Analysis ◽  
Research Questions

Log statements present in source code provide important information to the software developers because they are useful in various software development activities such as debugging, anomaly detection, and remote issue resolution. Most of the previous studies on logging analysis and prediction provide insights and results after analyzing only a few code constructs. In this chapter, the authors perform an in-depth, focused, and large-scale analysis of logging code constructs at two levels: the file level and catch-blocks level. They answer several research questions related to statistical and content analysis. Statistical and content analysis reveals the presence of differentiating properties among logged and nonlogged code constructs. Based on these findings, the authors propose a machine-learning-based model for catch-blocks logging prediction. The machine-learning-based model is found to be effective in catch-blocks logging prediction.

scholarly journals Computational generation of an annotated gigalibrary of synthesizable, composite peptidic macrocycles

2020 ◽  
Vol 117 (40) ◽  
pp. 24679-24690
Author(s):  
Ishika Saha ◽  
Eric K. Dang ◽  
Dennis Svatunek ◽  
Kendall N. Houk ◽  
Patrick G. Harran
Keyword(s):  
Virtual Screening ◽  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Three Dimensional ◽  
Pharmacological Properties ◽  
Robust Methods ◽  
Small Peptide ◽  
Multistep Reaction ◽  
Condensed Heterocycles

Peptidomimetic macrocycles have the potential to regulate challenging therapeutic targets. Structures of this type having precise shapes and drug-like character are particularly coveted, but are relatively difficult to synthesize. Our laboratory has developed robust methods that integrate small-peptide units into designed scaffolds. These methods create macrocycles and embed condensed heterocycles to diversify outcomes and improve pharmacological properties. The hypothetical scope of the methodology is vast and far outpaces the capacity of our experimental format. We now describe a computational rendering of our methodology that creates an in silico three-dimensional library of composite peptidic macrocycles. Our open-source platform, CPMG (Composite Peptide Macrocycle Generator), has algorithmically generated a library of 2,020,794,198 macrocycles that can result from the multistep reaction sequences we have developed. Structures are generated based on predicted site reactivity and filtered on the basis of physical and three-dimensional properties to identify maximally diverse compounds for prioritization. For conformational analyses, we also introduce ConfBuster++, an RDKit port of the open-source software ConfBuster, which allows facile integration with CPMG and ready parallelization for better scalability. Our approach deeply probes ligand space accessible via our synthetic methodology and provides a resource for large-scale virtual screening.

Logging Analysis and Prediction in Open Source Java Project

2018 ◽  
pp. 57-85
Author(s):  
Sangeeta Lal ◽  
Neetu Sardana ◽  
Ashish Sureka
Keyword(s):  
Machine Learning ◽  
Content Analysis ◽  
Software Development ◽  
Anomaly Detection ◽  
Open Source ◽  
Large Scale ◽  
Source Code ◽  
Scale Analysis ◽  
Large Scale Analysis ◽  
Research Questions

Log statements present in source code provide important information to the software developers because they are useful in various software development activities such as debugging, anomaly detection, and remote issue resolution. Most of the previous studies on logging analysis and prediction provide insights and results after analyzing only a few code constructs. In this chapter, the authors perform an in-depth, focused, and large-scale analysis of logging code constructs at two levels: the file level and catch-blocks level. They answer several research questions related to statistical and content analysis. Statistical and content analysis reveals the presence of differentiating properties among logged and nonlogged code constructs. Based on these findings, the authors propose a machine-learning-based model for catch-blocks logging prediction. The machine-learning-based model is found to be effective in catch-blocks logging prediction.

scholarly journals The influence of uncertain loading on topology-optimized designs

2021 ◽  
Author(s):  
Philipp Hofer ◽  
Erich Wehrle
Keyword(s):  
Topology Optimization ◽  
Open Source ◽  
Large Scale ◽  
Three Dimensional ◽  
Applied Force ◽  
Structural Performance ◽  
Optimized Design ◽  
Applied Forces ◽  
Reducing Costs ◽  
The Relationship

The design of structures using topology optimization can improve the structural performance and save material, in turn reducing costs. Using a framework of large-scale, three-dimensional topology optimization implemented by the authors in an open-source multiphysical software, we investigate the influence of uncertain loading on the optimized design. Direct differentiation is used to reveal the relationship between displacements and applied force, giving an efficient and effective tool to postprocess optimized topologies. The developed methodology for the assessment of the sensitivity with respect to applied forces is explored using two three-dimensional examples: the classic MBB cantilever and a cableway pylon. The advantages and limitations of this method are discussed.

C haste : incorporating a novel multi-scale spatial and temporal algorithm into a large-scale open source library

2009 ◽  
Vol 367 (1895) ◽  
pp. 1907-1930 ◽  
Author(s):  
Miguel O. Bernabeu ◽  
Rafel Bordas ◽  
Pras Pathmanathan ◽  
Joe Pitt-Francis ◽  
Jonathan Cooper ◽  
...  
Keyword(s):  
Open Source ◽  
Computational Efficiency ◽  
Large Scale ◽  
Three Dimensional ◽  
Testing Procedure ◽  
Two Dimensions ◽  
Multi Scale ◽  
Bidomain Equations ◽  
Cancer Modelling ◽  
Set Up

Recent work has described the software engineering and computational infrastructure that has been set up as part of the Cancer, Heart and Soft Tissue Environment (C haste ) project. C haste is an open source software package that currently has heart and cancer modelling functionality. This software has been written using a programming paradigm imported from the commercial sector and has resulted in a code that has been subject to a far more rigorous testing procedure than that is usual in this field. In this paper, we explain how new functionality may be incorporated into C haste . Whiteley has developed a numerical algorithm for solving the bidomain equations that uses the multi-scale (MS) nature of the physiology modelled to enhance computational efficiency. Using a simple geometry in two dimensions and a purpose-built code, this algorithm was reported to give an increase in computational efficiency of more than two orders of magnitude. In this paper, we begin by reviewing numerical methods currently in use for solving the bidomain equations, explaining how these methods may be developed to use the MS algorithm discussed above. We then demonstrate the use of this algorithm within the C haste framework for solving the monodomain and bidomain equations in a three-dimensional realistic heart geometry. Finally, we discuss how C haste may be developed to include new physiological functionality—such as modelling a beating heart and fluid flow in the heart—and how new algorithms aimed at increasing the efficiency of the code may be incorporated.

Virtual Demonstration Tests of Large-Scale and Complex Artifacts Using an Open Source Parallel CAE System, ADVENTURE

2006 ◽  
Vol 110 ◽  
pp. 133-142 ◽  
Author(s):  
Shinobu Yoshimura
Keyword(s):  
Open Source ◽  
Large Scale ◽  
Three Dimensional ◽  
Element Model ◽  
General Purpose ◽  
Full Scale ◽  
Grid Environments ◽  
Dimensional Finite Element ◽  
Three Dimensional Finite Element ◽  
Cae System

The ADVENTURE project started as one of the research projects in the "Computational Science & Engineering" field selected for the "Research for the Future" Program sponsored by the Japan Society for the Promotion of Science during 1997-2002. Since March 2002, the project has continued as an independent project. In the project we have been developing an advanced general-purpose computational mechanics system, named ADVENTURE, running in various kinds of parallel and ditributed environments. The system is designed to be able to analyze a three-dimensional finite element model of arbitrary shape with 10-100 million DOFs mesh, and additionally to enable parametric and non-parametric shape optimization. The first version of the system has been released from the project website as open source software since March, 2002. 2,049 registered users in academia and industries have downloaded 12,827 modules and been using them, while one company has developed and released its commercial version named ADVENTUREcluster. The ADVENTURE system has been successfully implemented in various types of parallel and distributed environments including PC clusters, massively parallel processers such as Hitachi SR8000/MPP and the Earth Simulator, and Grid environments such as ITBL (IT-based Laboratory). The system has been successfully applied to solve various real world problems such as response of a full scale nuclear pressure vessel model and thermoelastic deformation of full scale electric mounting board of a mobile PC.

scholarly journals Large-scale open-source three-dimensional growth curves for clinical facial assessment and objective description of facial dysmorphism

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Harold S. Matthews ◽  
Richard L. Palmer ◽  
Gareth S. Baynam ◽  
Oliver W. Quarrell ◽  
Ophir D. Klein ◽  
...  
Keyword(s):  
Open Source ◽  
Clinical Diagnosis ◽  
Large Scale ◽  
Three Dimensional ◽  
Growth Curves ◽  
Facial Dysmorphism ◽  
Facial Morphology ◽  
Craniofacial Dysmorphism ◽  
Facial Shape ◽  
The Rich

AbstractCraniofacial dysmorphism is associated with thousands of genetic and environmental disorders. Delineation of salient facial characteristics can guide clinicians towards a correct clinical diagnosis and understanding the pathogenesis of the disorder. Abnormal facial shape might require craniofacial surgical intervention, with the restoration of normal shape an important surgical outcome. Facial anthropometric growth curves or standards of single inter-landmark measurements have traditionally supported assessments of normal and abnormal facial shape, for both clinical and research applications. However, these fail to capture the full complexity of facial shape. With the increasing availability of 3D photographs, methods of assessment that take advantage of the rich information contained in such images are needed. In this article we derive and present open-source three-dimensional (3D) growth curves of the human face. These are sequences of age and sex-specific expected 3D facial shapes and statistical models of the variation around the expected shape, derived from 5443 3D images. We demonstrate the use of these growth curves for assessing patients and show that they identify normal and abnormal facial morphology independent from age-specific facial features. 3D growth curves can facilitate use of state-of-the-art 3D facial shape assessment by the broader clinical and biomedical research community. This advance in phenotype description will support clinical diagnosis and the understanding of disease pathogenesis including genotype–phenotype relations.

scholarly journals Contextual Similarity Among Identifier Names: An Empirical Study

2020 ◽  
Author(s):  
Remo De Oliveira Gresta ◽  
Elder Cirilo
Keyword(s):  
Empirical Study ◽  
Software Development ◽  
Open Source ◽  
Semantic Similarity ◽  
Large Scale ◽  
Current Knowledge ◽  
Source Code ◽  
Word Embedding ◽  
Acceptable Level ◽  
Domain Information

Identifiers are one of the most important sources of domain information in software development. Therefore, it is recognized that the proper use of names directly impacts the code's comprehensibility, maintainability, and quality. Our goal in this work is to expand the current knowledge about names by considering not only their quality but also their contextual similarity. To achieve that, we extracted names of four large scale open-source projects written in Java. Then, we computed the semantic similarity between classes and their attributes/variables using Fasttext, an word embedding algorithm. As a result, we could observe that source code, in general, preserve an acceptable level of contextual similarity, developers avoid to use names out of the default dictionary (e.g., domain), and files with more changes and maintained by distinct contributors tend to have better a contextual similarity.

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