The Experts below are selected from a list of 3189 Experts worldwide ranked by ideXlab platform

Miyun Park - One of the best experts on this subject based on the ideXlab platform.

  • study on standardization and construction of inventory database for asset management in water supply system
    International journal of database theory and application, 2016
    Co-Authors: Myeongsik Kong, Hongcheol Shin, Miyun Park
    Abstract:

    To standardize and construct an inventory database for a water supply system, an Inheritance Tree is constituted from Level 1 to 5 for specification of a classification structure for the water supply system. Level 1 is specified based on systems while Level 2 to 5 are specified to classify water supply systems by considering a structure’s role, function and type for each system. Also, the property information for asset management of each structure is systematcially investigated and written on a form to enable standardization of an inventory database. The property information is divided into asset classification information, asset location spatial information, asset specification information and asset management-related information, and the definitions, types, units and descriptions of the examined data are systematcially organized

  • study on inventory database construction for asset management in water supply system
    Information Technology and Computer Science, 2016
    Co-Authors: Myeongsik Kong, Hongcheol Shin, Miyun Park
    Abstract:

    To construct an inventory database for a water supply system, an Inheritance Tree is constituted from Level 1 to 5 for specification of a classification structure for the water supply system. Level 1 is specified based on systems while Level 2 to 5 are specified to classify water supply systems by considering a structure's role, function and type for each system. Also, the property information for asset management of each structure is systematcially investigated and written on a form to enable standardization of an inventory database. The property information is divided into asset classification information, asset location spatial information, asset specification information and asset management-related information, and the definitions, types, units and descriptions of the examined data are systematcially organized.

Myeongsik Kong - One of the best experts on this subject based on the ideXlab platform.

  • study on standardization and construction of inventory database for asset management in water supply system
    International journal of database theory and application, 2016
    Co-Authors: Myeongsik Kong, Hongcheol Shin, Miyun Park
    Abstract:

    To standardize and construct an inventory database for a water supply system, an Inheritance Tree is constituted from Level 1 to 5 for specification of a classification structure for the water supply system. Level 1 is specified based on systems while Level 2 to 5 are specified to classify water supply systems by considering a structure’s role, function and type for each system. Also, the property information for asset management of each structure is systematcially investigated and written on a form to enable standardization of an inventory database. The property information is divided into asset classification information, asset location spatial information, asset specification information and asset management-related information, and the definitions, types, units and descriptions of the examined data are systematcially organized

  • study on inventory database construction for asset management in water supply system
    Information Technology and Computer Science, 2016
    Co-Authors: Myeongsik Kong, Hongcheol Shin, Miyun Park
    Abstract:

    To construct an inventory database for a water supply system, an Inheritance Tree is constituted from Level 1 to 5 for specification of a classification structure for the water supply system. Level 1 is specified based on systems while Level 2 to 5 are specified to classify water supply systems by considering a structure's role, function and type for each system. Also, the property information for asset management of each structure is systematcially investigated and written on a form to enable standardization of an inventory database. The property information is divided into asset classification information, asset location spatial information, asset specification information and asset management-related information, and the definitions, types, units and descriptions of the examined data are systematcially organized.

Hongcheol Shin - One of the best experts on this subject based on the ideXlab platform.

  • study on standardization and construction of inventory database for asset management in water supply system
    International journal of database theory and application, 2016
    Co-Authors: Myeongsik Kong, Hongcheol Shin, Miyun Park
    Abstract:

    To standardize and construct an inventory database for a water supply system, an Inheritance Tree is constituted from Level 1 to 5 for specification of a classification structure for the water supply system. Level 1 is specified based on systems while Level 2 to 5 are specified to classify water supply systems by considering a structure’s role, function and type for each system. Also, the property information for asset management of each structure is systematcially investigated and written on a form to enable standardization of an inventory database. The property information is divided into asset classification information, asset location spatial information, asset specification information and asset management-related information, and the definitions, types, units and descriptions of the examined data are systematcially organized

  • study on inventory database construction for asset management in water supply system
    Information Technology and Computer Science, 2016
    Co-Authors: Myeongsik Kong, Hongcheol Shin, Miyun Park
    Abstract:

    To construct an inventory database for a water supply system, an Inheritance Tree is constituted from Level 1 to 5 for specification of a classification structure for the water supply system. Level 1 is specified based on systems while Level 2 to 5 are specified to classify water supply systems by considering a structure's role, function and type for each system. Also, the property information for asset management of each structure is systematcially investigated and written on a form to enable standardization of an inventory database. The property information is divided into asset classification information, asset location spatial information, asset specification information and asset management-related information, and the definitions, types, units and descriptions of the examined data are systematcially organized.

Olcay Taner Yildiz - One of the best experts on this subject based on the ideXlab platform.

  • software defect prediction using bayesian networks
    Empirical Software Engineering, 2014
    Co-Authors: Ahmet Okutan, Olcay Taner Yildiz
    Abstract:

    There are lots of different software metrics discovered and used for defect prediction in the literature. Instead of dealing with so many metrics, it would be practical and easy if we could determine the set of metrics that are most important and focus on them more to predict defectiveness. We use Bayesian networks to determine the probabilistic influential relationships among software metrics and defect proneness. In addition to the metrics used in Promise data repository, we define two more metrics, i.e. NOD for the number of developers and LOCQ for the source code quality. We extract these metrics by inspecting the source code repositories of the selected Promise data repository data sets. At the end of our modeling, we learn the marginal defect proneness probability of the whole software system, the set of most effective metrics, and the influential relationships among metrics and defectiveness. Our experiments on nine open source Promise data repository data sets show that response for class (RFC), lines of code (LOC), and lack of coding quality (LOCQ) are the most effective metrics whereas coupling between objects (CBO), weighted method per class (WMC), and lack of cohesion of methods (LCOM) are less effective metrics on defect proneness. Furthermore, number of children (NOC) and depth of Inheritance Tree (DIT) have very limited effect and are untrustworthy. On the other hand, based on the experiments on Poi, Tomcat, and Xalan data sets, we observe that there is a positive correlation between the number of developers (NOD) and the level of defectiveness. However, further investigation involving a greater number of projects is needed to confirm our findings.

Prakash Aravind - One of the best experts on this subject based on the ideXlab platform.

  • Devil is Virtual: Reversing Virtual Inheritance in C++ Binaries
    2020
    Co-Authors: Erinfolami, Rukayat Ayomide, Prakash Aravind
    Abstract:

    Complexities that arise from implementation of object-oriented concepts in C++ such as virtual dispatch and dynamic type casting have attracted the attention of attackers and defenders alike. Binary-level defenses are dependent on full and precise recovery of class Inheritance Tree of a given program. While current solutions focus on recovering single and multiple Inheritances from the binary, they are oblivious to virtual Inheritance. Conventional wisdom among binary-level defenses is that virtual Inheritance is uncommon and/or support for single and multiple Inheritances provides implicit support for virtual Inheritance. In this paper, we show neither to be true. Specifically, (1) we present an efficient technique to detect virtual Inheritance in C++ binaries and show through a study that virtual Inheritance can be found in non-negligible number (more than 10\% on Linux and 12.5\% on Windows) of real-world C++ programs including Mysql and libstdc++. (2) we show that failure to handle virtual Inheritance introduces both false positives and false negatives in the hierarchy Tree. These false positves and negatives either introduce attack surface when the hierarchy recovered is used to enforce CFI policies, or make the hierarchy difficult to understand when it is needed for program understanding (e.g., during decompilation). (3) We present a solution to recover virtual Inheritance from COTS binaries. We recover a maximum of 95\% and 95.5\% (GCC -O0) and a minimum of 77.5\% and 73.8\% (Clang -O2) of virtual and intermediate bases respectively in the virtual Inheritance Tree.Comment: Accepted at CCS20. This is a technical report versio