A Study on the Enhancement of the Efficiency of Lifelong Education Program Operation for University Students -Focusing on Demand Analysis of Gyeongbuk A University Students-

2021 ◽  
Vol 12 (1) ◽  
pp. 2629-2644
Author(s):  
Bogim Jeong ◽  
Seontae Park
Keyword(s):  
University Students ◽  
Education Program ◽  
Demand Analysis ◽  
Lifelong Education ◽  
On Demand

scholarly journals Optimal and Perfectly Parallel Algorithms for On-demand Data-Flow Analysis

2020 ◽  
pp. 112-140 ◽  
Author(s):  
Krishnendu Chatterjee ◽  
Amir Kafshdar Goharshady ◽  
Rasmus Ibsen-Jensen ◽  
Andreas Pavlogiannis
Keyword(s):  
Data Flow ◽  
Flow Analysis ◽  
Demand Analysis ◽  
Finite Domain ◽  
Data Flow Analysis ◽  
On Demand ◽  
Time Optimal ◽  
Speed Up ◽  
Flow Functions ◽  
Flow Graphs

AbstractInterprocedural data-flow analyses form an expressive and useful paradigm of numerous static analysis applications, such as live variables analysis, alias analysis and null pointers analysis. The most widely-used framework for interprocedural data-flow analysis is IFDS, which encompasses distributive data-flow functions over a finite domain. On-demand data-flow analyses restrict the focus of the analysis on specific program locations and data facts. This setting provides a natural split between (i) an offline (or preprocessing) phase, where the program is partially analyzed and analysis summaries are created, and (ii) an online (or query) phase, where analysis queries arrive on demand and the summaries are used to speed up answering queries.In this work, we consider on-demand IFDS analyses where the queries concern program locations of the same procedure (aka same-context queries). We exploit the fact that flow graphs of programs have low treewidth to develop faster algorithms that are space and time optimal for many common data-flow analyses, in both the preprocessing and the query phase. We also use treewidth to develop query solutions that are embarrassingly parallelizable, i.e. the total work for answering each query is split to a number of threads such that each thread performs only a constant amount of work. Finally, we implement a static analyzer based on our algorithms, and perform a series of on-demand analysis experiments on standard benchmarks. Our experimental results show a drastic speed-up of the queries after only a lightweight preprocessing phase, which significantly outperforms existing techniques.

Safety verification test study based on demand analysis

2020 ◽  
Author(s):  
Wei Yan ◽  
Leili Hu ◽  
Shuizhong Chen ◽  
Shiyong Guo ◽  
Baolin Du ◽  
...  
Keyword(s):  
Demand Analysis ◽  
Safety Verification ◽  
On Demand ◽  
Test Study ◽  
Verification Test
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