scholarly journals A Bag of Wiki Stories, Attribute Oriented Programming with XDoclet, Rx ++ and GS collections.

2020 ◽  
Author(s):  
Anil Kumar Bheemaiah
Keyword(s):  
Data Structure ◽  
Data Structures ◽  
Code Generation ◽  
Reusable Components ◽  
User Stories ◽  
Method Integration ◽  
Code Generators ◽  
Function Integration ◽  
Agile Process ◽  
Bayesian Machine Learning

The Wiki Story an essential documentation as javadoc is added to GS collections as a mutable data structure, added to collections like the Bag, leading to self modifiable programs with attribute oriented programming inspired by work in LISP and AIML, and the Self language of BotLibre. In this paper we integrate Open FaaS to Java 8 and RxJava, for Green Coding and the generalization to reusable components in remote functions on the edge or the cloud.Keywords: GS collections, Eclipse collections, XDoclet, Code Generators, Open FaaS, Bayou Framework.What:The GS Collections has a new data structure candidate, the Wiki Story WS, WS inherits from the User Stories of the Agile process, with documentation embedded in it as comments, amenable directly to OOPS programming. A WS data structure is defined by the this property and reflects a uniform xml, JSON and html5 DOM structure. X Doclet is introduced as attribute oriented programming with a set of attributes , both for Beans, Streams, and Rx Operators and data structures. How:Attributes define Rx and Rx ++ programming with code generators from XDoclet 2 library.Custom objects allow for the integration of Rx Stream objects, both sensor streams, event streams, kinesis streams and dynamoDB streams and many more streams. OpenFaaS is also integrated by a query based function integration as remote method or cloud based method integration with attributes, called green coding similar to the method, queryCodeGenerator()(Bheemaiah, n.d.)Bayou but extended to FaaS, services as attributes.(“How to Use Bayou – Bayou: Program Synthesis Powered by Bayesian Machine Learning” n.d.)Why:We have added wiki’s to the user stories provided as agile, attributes are added allowing for a query based tool for FaaS and XDoclet based code generation analogous to the neural sketch learning of Bayou. Code generation as amplification is now so fashionable that gangster like coders can also contribute really well generated code, an evolution of compiler backend code.Applications:Uniform high quality code, optimized to score high on Sonar, Code Generators for amplification and Green Coding.

scholarly journals IMPLEMENTING A DOMAIN MODEL FOR DATA STRUCTURES

1992 ◽  
Vol 02 (03) ◽  
pp. 375-402 ◽  
Author(s):  
DON BATORY ◽  
VIVEK SINGHAL ◽  
MARTY SIRKIN
Keyword(s):  
Data Structure ◽  
Data Structures ◽  
Domain Model ◽  
Complex Data ◽  
Domain Modeling ◽  
Reusable Components ◽  
Structure Domain

We present a model of the data structure domain that is expressed in terms of the GenVoca domain modeling concepts [7]. We show how familiar data structures can be encapsulated as realms of plug-compatible, symmetric, and reusable components, and we show how complex data structures can be formed from their composition. The target application of our research is a precompiler for specifying and generating customized data structures.

scholarly journals A Comparative Study about Data Structures Used for Efficient Management of Voxelised Full-Waveform Airborne LiDAR Data during 3D Polygonal Model Creation

2021 ◽  
Vol 13 (4) ◽  
pp. 559
Author(s):  
Milto Miltiadou ◽  
Neill D. F. Campbell ◽  
Darren Cosker ◽  
Michael G. Grant
Keyword(s):  
Data Structure ◽  
Data Structures ◽  
Airborne Lidar ◽  
Memory Allocation ◽  
Lidar Data ◽  
Full Waveform ◽  
Waveform Lidar ◽  
Airborne Lidar Data ◽  
Full Waveform Lidar ◽  
Polygonal Model

In this paper, we investigate the performance of six data structures for managing voxelised full-waveform airborne LiDAR data during 3D polygonal model creation. While full-waveform LiDAR data has been available for over a decade, extraction of peak points is the most widely used approach of interpreting them. The increased information stored within the waveform data makes interpretation and handling difficult. It is, therefore, important to research which data structures are more appropriate for storing and interpreting the data. In this paper, we investigate the performance of six data structures while voxelising and interpreting full-waveform LiDAR data for 3D polygonal model creation. The data structures are tested in terms of time efficiency and memory consumption during run-time and are the following: (1) 1D-Array that guarantees coherent memory allocation, (2) Voxel Hashing, which uses a hash table for storing the intensity values (3) Octree (4) Integral Volumes that allows finding the sum of any cuboid area in constant time, (5) Octree Max/Min, which is an upgraded octree and (6) Integral Octree, which is proposed here and it is an attempt to combine the benefits of octrees and Integral Volumes. In this paper, it is shown that Integral Volumes is the more time efficient data structure but it requires the most memory allocation. Furthermore, 1D-Array and Integral Volumes require the allocation of coherent space in memory including the empty voxels, while Voxel Hashing and the octree related data structures do not require to allocate memory for empty voxels. These data structures, therefore, and as shown in the test conducted, allocate less memory. To sum up, there is a need to investigate how the LiDAR data are stored in memory. Each tested data structure has different benefits and downsides; therefore, each application should be examined individually.

scholarly journals Shape Neutral Analysis of Graph-based Data-structures

2018 ◽  
Vol 18 (3-4) ◽  
pp. 470-483 ◽  
Author(s):  
GREGORY J. DUCK ◽  
JOXAN JAFFAR ◽  
ROLAND H. C. YAP
Keyword(s):  
Data Structure ◽  
Data Structures ◽  
Program Analysis ◽  
Constraint Handling ◽  
C Programs ◽  
Wide Range ◽  
Target Program ◽  
Target Data ◽  
Structure Graph ◽  
Structure Properties

AbstractMalformed data-structures can lead to runtime errors such as arbitrary memory access or corruption. Despite this, reasoning over data-structure properties for low-level heap manipulating programs remains challenging. In this paper we present a constraint-based program analysis that checks data-structure integrity, w.r.t. given target data-structure properties, as the heap is manipulated by the program. Our approach is to automatically generate a solver for properties using the type definitions from the target program. The generated solver is implemented using a Constraint Handling Rules (CHR) extension of built-in heap, integer and equality solvers. A key property of our program analysis is that the target data-structure properties are shape neutral, i.e., the analysis does not check for properties relating to a given data-structure graph shape, such as doubly-linked-lists versus trees. Nevertheless, the analysis can detect errors in a wide range of data-structure manipulating programs, including those that use lists, trees, DAGs, graphs, etc. We present an implementation that uses the Satisfiability Modulo Constraint Handling Rules (SMCHR) system. Experimental results show that our approach works well for real-world C programs.

Integrating Image Computation in Undergraduate Level Data-Structure Education

1998 ◽  
Vol 12 (08) ◽  
pp. 1071-1080 ◽  
Author(s):  
Sudeep Sarkar ◽  
Dmitry Goldgof
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Data Structure ◽  
Data Structures ◽  
Science Curriculum ◽  
Early Stage ◽  
Real Life ◽  
South Florida ◽  
The University ◽  
Structure Education

There is a growing need for expertise both in image analysis and in software engineering. To date, these two areas have been taught separately in an undergraduate computer and information science curriculum. However, we have found that introduction to image analysis can be easily integrated in data-structure courses without detracting from the original goal of teaching data structures. Some of the image processing tasks offer a natural way to introduce basic data structures such as arrays, queues, stacks, trees and hash tables. Not only does this integrated strategy expose the students to image related manipulations at an early stage of the curriculum but it also imparts cohesiveness to the data-structure assignments and brings them closer to real life. In this paper we present a set of programming assignments that integrates undergraduate data-structure education with image processing tasks. These assignments can be incorporated in existing data-structure courses with low time and software overheads. We have used these assignment sets thrice: once in a 10-week duration data-structure course at the University of California, Santa Barbara and the other two times in 15-week duration courses at the University of South Florida, Tampa.

scholarly journals DenseZDD: A Compact and Fast Index for Families of Sets

Algorithms ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 128 ◽  
Author(s):  
Shuhei Denzumi ◽  
Jun Kawahara ◽  
Koji Tsuda ◽  
Hiroki Arimura ◽  
Shin-ichi Minato ◽  
...  
Keyword(s):  
Data Structure ◽  
Data Structures ◽  
Information Integration ◽  
Decision Diagrams ◽  
Web Information Retrieval ◽  
Binary Decision ◽  
Web Information ◽  
Set Operations ◽  
Succinct Data Structure ◽  
The Family

In this article, we propose a succinct data structure of zero-suppressed binary decision diagrams (ZDDs). A ZDD represents sets of combinations efficiently and we can perform various set operations on the ZDD without explicitly extracting combinations. Thanks to these features, ZDDs have been applied to web information retrieval, information integration, and data mining. However, to support rich manipulation of sets of combinations and update ZDDs in the future, ZDDs need too much space, which means that there is still room to be compressed. The paper introduces a new succinct data structure, called DenseZDD, for further compressing a ZDD when we do not need to conduct set operations on the ZDD but want to examine whether a given set is included in the family represented by the ZDD, and count the number of elements in the family. We also propose a hybrid method, which combines DenseZDDs with ordinary ZDDs. By numerical experiments, we show that the sizes of our data structures are three times smaller than those of ordinary ZDDs, and membership operations and random sampling on DenseZDDs are about ten times and three times faster than those on ordinary ZDDs for some datasets, respectively.

scholarly journals Spaced Seed Data Structures forDe NovoAssembly

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Inanç Birol ◽  
Justin Chu ◽  
Hamid Mohamadi ◽  
Shaun D. Jackman ◽  
Karthika Raghavan ◽  
...  
Keyword(s):  
Data Structure ◽  
Data Structures ◽  
De Novo ◽  
Bloom Filters ◽  
De Bruijn Graph ◽  
Sequence Specificity ◽  
Sequencing Errors ◽  
Spaced Seeds ◽  
Read Error Correction ◽  
Seed Data

De novoassembly of the genome of a species is essential in the absence of a reference genome sequence. Many scalable assembly algorithms use the de Bruijn graph (DBG) paradigm to reconstruct genomes, where a table of subsequences of a certain length is derived from the reads, and their overlaps are analyzed to assemble sequences. Despite longer subsequences unlocking longer genomic features for assembly, associated increase in compute resources limits the practicability of DBG over other assembly archetypes already designed for longer reads. Here, we revisit the DBG paradigm to adapt it to the changing sequencing technology landscape and introduce three data structure designs for spaced seeds in the form of paired subsequences. These data structures address memory and run time constraints imposed by longer reads. We observe that when a fixed distance separates seed pairs, it provides increased sequence specificity with increased gap length. Further, we note that Bloom filters would be suitable to implicitly store spaced seeds and be tolerant to sequencing errors. Building on this concept, we describe a data structure for tracking the frequencies of observed spaced seeds. These data structure designs will have applications in genome, transcriptome and metagenome assemblies, and read error correction.

Suffix Tree Constructing Algorithm for Datasets with Discrete Contents

2015 ◽  
Vol 733 ◽  
pp. 867-870
Author(s):  
Zhen Zhong Jin ◽  
Zheng Huang ◽  
Hua Zhang
Keyword(s):  
Data Structure ◽  
Sensor Network ◽  
Association Analysis ◽  
Data Structures ◽  
Suffix Tree ◽  
Analysis Data ◽  
Large Datasets ◽  
Intermediate Data ◽  
Input Strings

The suffix tree is a useful data structure constructed for indexing strings. However, when it comes to large datasets of discrete contents, most existing algorithms become very inefficient. Discrete datasets are need to be indexed in many fields like record analysis, data analyze in sensor network, association analysis etc. This paper presents an algorithm, STD, which stands for Suffix Tree for Discrete contents, that performs very efficiently with discrete input datasets. It imports several wonderful intermediate data structures for discrete strings; we also take care of the situation that the discrete input strings have similar characteristics. Moreover, STD keeps the advantages of existing implementations which are for successive input strings. Experiments were taken to evaluate the performance and shown that the method works well.

Efficient Data Structures for Range Selections Problem

2013 ◽  
Vol 756-759 ◽  
pp. 1387-1391
Author(s):  
Xiao Dong Wang ◽  
Jun Tian
Keyword(s):  
Data Structure ◽  
Linear Space ◽  
Data Structures ◽  
Computation Model ◽  
Word Size ◽  
Selection Problems ◽  
Efficient Data ◽  
Space Data ◽  
Efficient Data Structures ◽  
Range Selection

Building an efficient data structure for range selection problems is considered. While there are several theoretical solutions to the problem, only a few have been tried out, and there is little idea on how the others would perform. The computation model used in this paper is the RAM model with word-size . Our data structure is a practical linear space data structure that supports range selection queries in time with preprocessing time.

Markup Discontinued

2009 ◽  
Author(s):  
C. M. Sperberg-McQueen ◽  
Claus Huitfeldt
Keyword(s):  
Data Structure ◽  
Data Structures ◽  
The Other ◽  
Discontinuous Elements ◽  
Parent Child

That the textual phenomena of interest for markup are not always hierarchically arranged is well known and widely discussed. Less frequently discussed is the fact that they are also not always contiguous, so that the units of our analysis cannot always correspond to single elements in the document. Various notations for discontinuous elements exist, but the mapping from those notations to data structures has not been well analysed or understood. And as far as we know, there are no standard mechanisms for validating discontinuous elements. We propose a data structure (a modification of the Goddag structure) to better handle discontinuous elements: we relax the rule that every pair of elements where one contains the other be related by a path of parent/child links. Parent/child links are then not an automatic result of containment. We conclude with a brief sketch of the issues involved in extending current validation mechanisms to handle discontinuity.

Description Mirror Features and Data Structures in an Optical CAD System

2014 ◽  
Vol 513-517 ◽  
pp. 796-799
Author(s):  
Jun Hai Jiang ◽  
Xiao Hui Yang
Keyword(s):  
Data Structure ◽  
Data Structures ◽  
Optical System ◽  
Simple Structure ◽  
Optical Design ◽  
Object Oriented ◽  
Optical Lens ◽  
Cad System ◽  
System Components ◽  
Object Oriented Methods

CAD is presented in optical design, the use of object-oriented methods, optical lens structure described. Using object-oriented techniques to describe the object lens, and with VC++ language features to build such systems, construct a data structure of the optical system components. This method has a simple structure, portability, reusability of characteristics.

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