scholarly journals Software Reusability of Object-Oriented Systems using Data Mining Techniques

2020 ◽  
Vol 8 (6) ◽  
pp. 2144-2152
Keyword(s):  
Data Mining ◽  
Software Reuse ◽  
Object Oriented ◽  
Market Value ◽  
Software Systems ◽  
Data Mining Techniques ◽  
Software Reusability ◽  
Using Data ◽  
Object Oriented Systems

Due to fast advancement in software industry, there was a demand to cut down time and efforts during process of software development. While designing product and services it is very essential to assure quality of product in order to strengthen market value of the product. To accomplish both quality as well as productivity objectives, it is suggested to go for software reuse. Reusability is an essential measure that can be used to improve overall software quality with lesser cost and efforts. This paper gives insights into various literature studies related to software reusability of Object-oriented software using data mining techniques. In this paper even comparative analysis of various techniques related to prediction and enhancement of reusability of Object-Oriented software systems has been done. This would help to get better understanding of need of reusability enhancement of Object-Oriented systems using data mining techniques

Evaluation of Software Reusability Based on Coupling and Cohesion

2018 ◽  
Vol 28 (10) ◽  
pp. 1455-1485
Author(s):  
G. Priyalakshmi ◽  
R. Latha
Keyword(s):  
Software Reuse ◽  
Object Oriented ◽  
Software Systems ◽  
Software Components ◽  
Software Developers ◽  
Cumulative Score ◽  
Software Reusability ◽  
Two Measures ◽  
Code Search Engines

Code reuse has become very popular among software developers in recent times since it saves time and resources. One of the significant difficulties to software reuse is the time pertaining to assess the fitness of the reusable code components. Over the recent years, code search engines have made momentous advancement in establishing the semantic suitability of software components for new usage scenarios. But the issue of evaluating software components based on their nonfunctional suitability has been overlooked to a large extent. The maintenance and reusability of software systems are highly influenced by the structural properties of system classes like complexity, size, coupling, cohesion, etc. The quality of object-oriented code or design artifacts is commonly measured by analyzing the structure of these artifacts in terms of the interdependencies of classes and components as well as their internal elements. In this paper, we perform an empirical analysis on Python packages for the two measures namely coupling and cohesion. The coupling score of a module is computed as module imports and the cohesion score of a module is evaluated as call dependency between classes and global functions of the module. Finally, the proposed work evaluates a package in terms of reusability score which is a cumulative score of the coupling scores and cohesion scores of all the modules within the package. The study has evaluated 15 different packages and five different releases of one single package for reusability. We have empirically tested that the Halstead’s effort metric is inversely proportional to the reusability score. The reusability score was validated using four code detuners. The proposed work was compared with the existing metrics namely cyclomatic complexity and maintainability Index showing satisfactory results.

scholarly journals Metric Approach to Anticipate Reusability of Object-Oriented (O-O) Software Systems

2021 ◽  
Vol 12 (6) ◽  
pp. 2456-2467
Author(s):  
Bharti Bisht, Dr Parul Gandhi
Keyword(s):  
Software Evolution ◽  
Object Oriented ◽  
Software Systems ◽  
Reusable Components ◽  
Software Products ◽  
Software Reusability ◽  
Object Oriented Approach ◽  
Object Oriented Systems

In order to meet the fast software evolution, there is a call for the work on software development based process by reducing time as well as efforts. The aim of the development process should not only be developing software products and services but also focus on improving the quality of the particular software. Software Reusability can be considered as one of the solutions to achieve both objectives i.e. productivity as well as quality. There has been an evolution of various methods and techniques related to construction of reusable components over many years. Object-oriented approach also assures increased software reusability. It is easier to reuse object-oriented software rather than conventional software. The notion of reusability related to Object-oriented software can be achieved through inheritance which in turn contributes to development of reusable components. In this paper different metrics related to software reusability of Object-oriented software systems has been summarized and evaluated using Python. Three python-based programs are considered as datasets for this study-the first dataset depicts single-level inheritance, the second dataset depicts hierarchical inheritance whereas the third dataset depicts multilevel inheritance. This study shows more impact of multilevel inheritance on the reusability of Object-oriented software systems and also helped to understand the important role of metrics in evaluation of object-oriented systems.

scholarly journals Improving Quality of Educational Processes Providing New Knowledge Using Data Mining Techniques

2014 ◽  
Vol 147 ◽  
pp. 390-397 ◽  
Author(s):  
Manolis Chalaris ◽  
Stefanos Gritzalis ◽  
Manolis Maragoudakis ◽  
Cleo Sgouropoulou ◽  
Anastasios Tsolakidis
Keyword(s):  
Data Mining ◽  
Data Mining Techniques ◽  
Educational Processes ◽  
New Knowledge ◽  
Using Data

Using Data Mining Techniques to Discover Patterns in an Airline's Flight Hours Assignments

2021 ◽  
pp. 107-126
Author(s):  
Francisco Javier Villar Martín ◽  
Jose Luis Castillo Sequera ◽  
Miguel Angel Navarro Huerga
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Information System ◽  
Predictive Modeling ◽  
Data Model ◽  
Free Software ◽  
Data Mining Techniques ◽  
Visualization Tools ◽  
Using Data

The quality of a company's information system is essential and also its physical data model. In this article, the authors apply data mining techniques in order to generate knowledge from the information system's data model, and also to discover and understand hidden patterns within data that regulate the planning of flight hours of pilots and copilots in an airline. With this objective, they use Weka free software which offers a set of algorithms and visualization tools geared to data analysis and predictive modeling of information systems. Firstly, they apply clustering to study the information system and analyze data model; secondly, they apply association rules to discover connection patterns in data; and finally, they generate a decision tree to classify and extract more specific patterns. The authors suggest conclusions according these information system's data to improve future decision making in an airline's flight hours assignments.

Role of Data Mining and Knowledge Discovery in Managing Telecommunication Systems

2010 ◽  
pp. 14-29
Author(s):  
Ibrahiem Mahmoud Mohamed El Emary
Keyword(s):  
Data Mining ◽  
Quality Of Service ◽  
Expert Systems ◽  
Telecommunications Industry ◽  
Data Mining Techniques ◽  
Telecommunication Systems ◽  
The Status ◽  
Using Data

This chapter is interested in discussing how to use data mining techniques to assist in achieving an acceptable level of quality of service of telecommunication systems. The quality of service is defined as the metrics which are predicated by using the data mining techniques, decision tree, association rules and neural networks. Routing algorithms can use this metric for optimal path selection which in turn will affect positively on the system performance. Also, in this chapter management axis using data mining techniques were handled, i.e., check the status of the telecommunication networks, role of data mining in obtaining optimal configuration, how to use data mining technique to assure high level of security for the telecommunication. The popularity of data mining in the telecommunications industry can be viewed as an extension of the use of expert systems in the telecommunications industry. These systems were developed to address the complexity associated with maintaining a huge network infrastructure and the need to maximize network reliability while minimizing labor costs (Liebowitz, J. 1988). The problem with these expert systems is that they are expensive to develop because it is both difficult and time consuming to elicit the requisite domain knowledge from experts.

Path Mining in Web Processes Using Profiles

2011 ◽  
pp. 896-901 ◽  
Author(s):  
Jorge Cardoso
Keyword(s):  
Data Mining ◽  
Quality Of Service ◽  
Business Process ◽  
Management System ◽  
Business Process Management ◽  
Process Management ◽  
Business Processes ◽  
Data Mining Techniques ◽  
Using Data

Business process management systems (BPMSs) (Smith & Fingar, 2003) provide a fundamental infrastructure to define and manage business processes, Web processes, and workflows. When Web processes and workflows are installed and executed, the management system generates data describing the activities being carried out and is stored in a log. This log of data can be used to discover and extract knowledge about the execution of processes. One piece of important and useful information that can be discovered is related to the prediction of the path that will be followed during the execution of a process. I call this type of discovery path mining. Path mining is vital to algorithms that estimate the quality of service of a process, because they require the prediction of paths. In this work, I present and describe how process path mining can be achieved by using data-mining techniques.

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