Breadth First Search Based COSINE Software Code Framework Automation Algorithm

2014 ◽  
Author(s):  
Hao Ren ◽  
Wentao Mo ◽  
Guang Zhao ◽  
Dangpei Ren ◽  
Shuo Liu
Keyword(s):  
Data Structure ◽  
Software Development ◽  
Nuclear Power ◽  
Source Code ◽  
Automatic Generation ◽  
Breadth First Search ◽  
Design And Optimization ◽  
Tree Data ◽  
Tree Data Structure ◽  
Automation Technology

Using software automation technology can significantly improve the quality and productivity of nuclear power software development. Based on the ‘tree’ data structure, this paper proposed Breadth First Search (BFS) based nuclear power software source code framework automatic generation algorithm called CFAA (Code Framework Automation Algorithm). CFAA uses ‘tree’ data structure to represent architecture of nuclear power software, then utilizes BFS to traverse all tree nodes to generate software source code framework. CFAA enables programmers to focus more on nuclear power software architecture design and optimization, and then generate the skeleton source code automatically. CFAA has been applied to COSINE (Core and System Integrated Engine for design and analysis) software development. Practice proved that CFAA can improve the efficiency of building nuclear power software framework, while reducing the defect rate of nuclear power software development.

Breadth First Search Based COSINE Software Code Framework Automation Algorithm

2015 ◽  
Author(s):  
Hao Ren ◽  
Wentao Mo ◽  
Guang Zhao ◽  
Dangpei Ren ◽  
Shuo Liu
Keyword(s):  
Data Structure ◽  
Software Development ◽  
Software Architecture ◽  
Automatic Generation ◽  
Software Framework ◽  
Breadth First Search ◽  
Design And Optimization ◽  
Tree Data ◽  
Tree Data Structure ◽  
Automation Technology

Using software automation technology can significantly improve the quality and productivity of software development. Based on the tree data structure, this paper proposed the Breadth First Search (BFS) based software framework automatic generation algorithm called CFAA (Code Framework Automation Algorithm). The algorithm uses tree data structure to represent scientific computing software architecture, then uses the BFS to traverse all nodes of the tree to generate code framework of software. CFAA enable programmers to focus more on computing software architecture design and optimization, and then automatically generate the skeleton code. CFAA has been applied to COSINE (Core and System Integrated Engine for design and analysis) software development process. Practice proved that CFAA can improve the efficiency of building software framework, while reducing the defect rate of software development.

Code Automation Technology Based COSINE Software Development

2013 ◽  
Author(s):  
Hao Ren ◽  
Wentao Mo ◽  
Shuo Liu ◽  
Dong Li ◽  
Yang Sun ◽  
...  
Keyword(s):  
Software Development ◽  
Nuclear Power ◽  
Source Code ◽  
Data Access ◽  
Automatic Generation ◽  
Code Generator ◽  
C Language ◽  
Fortran Code ◽  
Development Feature ◽  
Automation Technology

Source code automatic generation technology can improve software development’s quality and productivity significantly. However, the existing code generators cannot satisfy nuclear power software development demand. This paper analyzes development feature of scientific computing software and develops a FORTRAN Code Generator (FCG) using C# language. FCG can generate program variables definition FORTRAN source code automatically according to input metadata. FCG also can generate memory allocation source code for dynamic variables in program. Besides, FCG can generate data access interface for global variables in code. Right now, FCG has been applied to source code development of COSINE (Core and System Integrated Engine for design and analysis) software package. Development practice has proved that FCG can improve development efficiency of nuclear power software greatly.

A Scalable Algorithm for Constructing Frequent Pattern Tree

2014 ◽  
Vol 10 (1) ◽  
pp. 42-56 ◽  
Author(s):  
Zailani Abdullah ◽  
Tutut Herawan ◽  
A. Noraziah ◽  
Mustafa Mat Deris
Keyword(s):  
Data Structure ◽  
Frequent Pattern ◽  
Frequent Patterns ◽  
Scalable Algorithm ◽  
Tree Construction ◽  
Frequent Pattern Tree ◽  
Support Threshold ◽  
Benchmark Datasets ◽  
Tree Data ◽  
Tree Data Structure

Frequent Pattern Tree (FP-Tree) is a compact data structure of representing frequent itemsets. The construction of FP-Tree is very important prior to frequent patterns mining. However, there have been too limited efforts specifically focused on constructing FP-Tree data structure beyond from its original database. In typical FP-Tree construction, besides the prior knowledge on support threshold, it also requires two database scans; first to build and sort the frequent patterns and second to build its prefix paths. Thus, twice database scanning is a key and major limitation in completing the construction of FP-Tree. Therefore, this paper suggests scalable Trie Transformation Technique Algorithm (T3A) to convert our predefined tree data structure, Disorder Support Trie Itemset (DOSTrieIT) into FP-Tree. Experiment results through two UCI benchmark datasets show that the proposed T3A generates FP-Tree up to 3 magnitudes faster than that the benchmarked FP-Growth.

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