Constraint-based program debugging using data structure repair

Author(s):  
Muhammad Zubair Malik ◽  
Junaid Haroon Siddiqui ◽  
Sarfraz Khurshid
2020 ◽  
Vol 39 (4) ◽  
pp. 5027-5036
Author(s):  
You Lu ◽  
Qiming Fu ◽  
Xuefeng Xi ◽  
Zhenping Chen

Data outsourcing has gradually become a mainstream solution, but once data is outsourced, data owners will without the control of the data hardware, there is a possibility that the integrity of the data will be destroyed objectively. Many current studies have achieved low network overhead cloud data set verification by designing algorithmic structures (e.g., hashing, Merkel verification trees); however, cloud service providers may not recognize the incompleteness of cloud data to avoid liability or business factors fact. There is a need to build a secure, reliable, non-tamperable, and non-forgeable verification system for accountability. Blockchain is a chain-like data structure constructed by using data signatures, timestamps, hash functions, and proof-of-work mechanisms. Using blockchain technology to build an integrity verification system can achieve fault accountability. Blockchain is a chain-like data structure constructed by using data signatures, timestamps, hash functions, and proof-of-work mechanisms. Using blockchain technology to build an integrity verification system can achieve fault accountability. This paper uses the Hadoop framework to implement data collection and storage of the HBase system based on big data architecture. In summary, based on the research of blockchain cloud data collection and storage technology, based on the existing big data storage middleware, a large flow, high concurrency and high availability data collection and processing system has been realized.


2011 ◽  
Vol 8 (5) ◽  
pp. 670-684 ◽  
Author(s):  
A. Baliga ◽  
V. Ganapathy ◽  
L. Iftode

2010 ◽  
Vol 45 (5) ◽  
pp. 281-292 ◽  
Author(s):  
Gautam Upadhyaya ◽  
Samuel P. Midkiff ◽  
Vijay S. Pai

2019 ◽  
Vol 43 (4) ◽  
pp. 66-66
Author(s):  
Guolong Zheng ◽  
Quang Loc Le ◽  
ThanhVu Nguyen ◽  
Quoc-Sang Phan

2016 ◽  
Vol 3 ◽  
pp. 1-19
Author(s):  
Luciana Quaranta

The Intermediate Data Structure (IDS) provides a common structure for storing and sharing historical demographic data. The structure also facilitates the construction of different open-access software to extract information from these tables and construct new variables. The article Using the Intermediate Data Structure (IDS) to Construct Files for Analysis (Quaranta 2015) presented a series of concepts and programs that allow the user to construct a rectangular episodes file for longitudinal statistical analysis using data stored in the IDS. The current article discusses, in detail, each of these programs, describing their technicalities, structure and syntax, and also explaining how they can be used.


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