Of The Object-oriented Research Articles

Estimation Model for Enhanced Predictive Object Point Metric in OO Software Size Estimation Using Deep Learning

The Software industry’s rapid growth contributes to the need for new technologies. PRICE software system uses Predictive Object Point (POP) as a size measure to estimate Effort and cost. A refined POP metric value for object-oriented software written in Java can be calculated using the Automated POP Analysis tool. This research used 25 open-source Java projects. The refined POP metric improves the drawbacks of the PRICE system and gives a more accurate size measure of software. This paper uses refined POP metrics with curve-fitting neural networks and multi-layer perceptron neural network-based deep learning to estimate the software development effort. Results show that this approach gives an effort estimate closer to the actual Effort obtained through Constructive Cost Estimation Model (COCOMO) estimation models and thus validates refined POP as a better size measure of object-oriented software than POP. Therefore we consider the MLP approach to help construct the metric for the scale of the Object-Oriented (OO) model system.

Development of Computational Thinking Using Microcontrollers Integrated into OOP (Object-Oriented Programming)

Nowadays, the theme of computer thinking is a common topic for educational research. The scientific literature on the subject has gradually appeared, in which psychologists emphasize the need for the development of thinking of children. Research often relates only to the development of computational thinking at elementary and high schools. Nowadays, almost everything is digitalized, so it is important to also develop the computational thinking skills of students at higher levels. In our study, we present the results of the conducted data analysis in which we examined the development of students’ efficiency. On the basis of the results, we propose a possible solution for the development of computational thinking. Using data research processes, we examined the results of the object-oriented (OO) planning and programming subject of Budapest Business School, going back 5 years. The results show that the level of particular computational thinking could be measured using the exam results, and teacher advancement (experience) improved the level of particular computational thinking. Today, education has been greatly influenced by COVID-19, challenging not only teachers but also students. The production of particular computational thinking under COVID-19 or online is much more effective than the pursuit of full computational thinking through traditional teaching.

Measure extendibility/extensibility quality attribute using object oriented design metric

Software design is one of the very important phases of the software engineering. The costs of software can be minimized if improvements or corrections made during this stage. Several of the current computer aided software engineering (CASE) tools like enterprise architect (EA) v12 do not have the capability to improve the design. This work aims to develop an algorithm that helps the software engineers evaluating the design quality utilizing one of the object-oriented (OO) design models namely quality metrics for object-oriented design (QMOOD) which represents as hierarchical model that describes the relationship between quality attributes such as reusability, extendibility and properties of the design of OO design. This algorithm describesed how the assessment of the extendibility/ extensibility using the software metrics has been done and the impact of the involved metrics in the extendibility value. Results obtained demonstrate the effect of OO design metrics such as inheritance, polymorphism, abstraction and coupling in quality characteristics like extensibility. The results show that lower values of abstraction and coupling, obtain higher value of extendibility which means the class diagram is ready to accept additional improvements. The proposed algorithm has been tested on two different systems (test cases) that vary in their class diagrams, functionalities, and complexities.

An empirical analysis of source code metrics and smart contract resource consumption

AbstractA smart contract (SC) is a programme stored in the Ethereum blockchain by a contract‐creation transaction. SC developers deploy an instance of the SC and attempt to execute it in exchange for a fee, paid in Ethereum coins (Ether). If the computation needed for their execution turns out to be larger than the effort proposed by the developer (i.e., the gasLimit), their client instantiation will not be completed successfully.In this paper, we examine SCs from 11 Ethereum blockchain‐oriented software projects hosted on GitHub.com, and we evaluate the resources needed for their deployment (i.e., the gasUsed). For each of these contracts, we also extract a suite of object‐oriented metrics, to evaluate their structural characteristics.Our results show a statistically significant correlation between some of the object‐oriented (OO) metrics and the resources consumed on the Ethereum blockchain network when deploying SCs. This result has a direct impact on how Ethereum developers engage with a SC: evaluating its structural characteristics, they will be able to produce a better estimate of the resources needed to deploy it. Other results show specific source code metrics to be prioritised based on application domains when the projects are clustered based on common themes.

Inheritance Metrics for Object-Oriented Design

The inheritance metrics give us information about the inheritance tree of the system. Inheritance is a key feature of the Object-Oriented (OO) paradigm. This mechanism supports the class hierarchy design and captures the IS-A relationship between a super class and its subclass. Several OO inheritance metrics have been proposed and their reviews are available in the literature. Among the various measurements we focus on the metrics of class inheritance hierarchies. In this paper we consider the inheritance metrics of F.T. Sheldon et al (2002) and Henderson Seller's (1996) for comparison with proposed inheritance metric suites. In doing so, an attempt has been made to define empirical relationship between the proposed inheritance metric suites with considered existing inheritance metrics and the focus was on which how the inheritance metric suites were correlated with the existing ones. Data for several C++ classes has been collected from various sources.

Class movement and re-location: An empirical study of Java inheritance evolution

Inheritance is a fundamental feature of the Object-Oriented (OO) paradigm. It is used to promote extensibility and reuse in OO systems. Understanding how systems evolve, and specifically, trends in the movement and re-location of classes in OO hierarchies can help us understand and predict future maintenance effort. In this paper, we explore how and where new classes were added as well as where existing classes were deleted or moved across inheritance hierarchies from multiple versions of four Java systems. We observed first, that in one of the studied systems the same set of classes was continuously moved across the inheritance hierarchy. Second, in the same system, the most frequent changes were restricted to just one sub-part of the overall system. Third, that a maximum of three levels may be a threshold when using inheritance in a system; beyond this level very little activity was observed, supporting earlier theories that, beyond three levels, complexity becomes overwhelming. We also found evidence of ‘collapsing’ hierarchies to bring classes up to shallower levels. Finally, we found that larger classes and highly coupled classes were more frequently moved than smaller and less coupled classes. Statistical evidence supported the view that larger classes and highly coupled classes were less cohesive than smaller classes and lowly coupled classes and were thus more suitable candidates for being moved (within an hierarchy).

Cell modeling with reusable agent-based formalisms

Biologists are building increasingly complex models and simulations of cells and other biological entities, and are looking at alternatives to traditional representations. Making use of the object-oriented (OO) paradigm, the Unified Modeling Language (UML) and Real-time Object-Oriented Modeling (ROOM) visual formalisms, and the Rational Rose RealTime (RRT) visual modeling tool, we summarize a previously-described multi-step process for constructing top-down models of cells. We first construct a simple model of a cell using an architecture in which all objects are containers, agents, or passive objects. We then reuse these architectural principles and components to extend our simple cell model into a more complex cell, the goal being to demonstrate that encapsulation familiar to artificial intelligence researchers can be employed by systems biologists in their models. A red blood cell is embedded in a straight-forward manner within a larger system, which is in turn iteratively embedded within still larger systems, including a blood vessel, a circulatory system, a human being, and a simple ecology. Each complexity increment reuses the same architectural principles, including the use of agents, each of which continuously either moves passive small molecules between containers, or transforms these passive objects from one type into another. We show how it is possible to start with a direct diagrammatic representation of a biological structure such as a cell, using terminology familiar to biologists, and by following a process of gradually adding more and more detail, arrive at a system with structure and behavior of arbitrary complexity that can run and be observed on a computer.

UML as a cell and biochemistry modeling language

The systems biology community is building increasingly complex models and simulations of cells and other biological entities, and are beginning to look at alternatives to traditional representations such as those provided by ordinary differential equations (ODE). The lessons learned over the years by the software development community in designing and building increasingly complex telecommunication and other commercial real-time reactive systems, can be advantageously applied to the problems of modeling in the biology domain. Making use of the object-oriented (OO) paradigm, the unified modeling language (UML) and Real-Time Object-Oriented Modeling (ROOM) visual formalisms, and the Rational Rose RealTime (RRT) visual modeling tool, we describe a multi-step process we have used to construct top–down models of cells and cell aggregates. The simple example model described in this paper includes membranes with lipid bilayers, multiple compartments including a variable number of mitochondria, substrate molecules, enzymes with reaction rules, and metabolic pathways. We demonstrate the relevance of abstraction, reuse, objects, classes, component and inheritance hierarchies, multiplicity, visual modeling, and other current software development best practices. We show how it is possible to start with a direct diagrammatic representation of a biological structure such as a cell, using terminology familiar to biologists, and by following a process of gradually adding more and more detail, arrive at a system with structure and behavior of arbitrary complexity that can run and be observed on a computer. We discuss our CellAK (Cell Assembly Kit) approach in terms of features found in SBML, CellML, E-CELL, Gepasi, Jarnac, StochSim, Virtual Cell, and membrane computing systems.

Performance evaluation of the object-relational transformation methodology

The emergence of the object-oriented (OO) methodology has shown its capabilities in modelling the real world better than the earlier relational methodology. However, object-oriented databases (OODBs) are still considered immature in comparison with relational databases (RDBs) which have existed for many years. RDBs still continue to dominate the implementation of databases constituting more than 90% of all database implementations [28]. It was felt worthwhile to exploit the great modelling power of OO methodology, while still facilitating relational implementations. These reasons have led us to develop an object-relational transformation methodology [20–25] which allows us to use the OO methodology for data modelling and to transform it into a relational logical model for implementation in relational database management systems (RDBMSs). The main purpose of this paper is to present a performance evaluation of the transformation methodology. The evaluation covers I/O cost models of different types of queries. The type of evaluation is basically comparison-based, in which the performance of SQL operations upon a set of tables derived from the relational data model is compared with the tables derived from the OO data model using the transformation methodology. The results of the evaluation show that the performance of the RDB implementation transferred from an OO conceptual model using our object-relational transformation methodology is better than the relational implementation using a conventional relational modelling. Moreover, in many cases, the relational modelling is not applicable since it cannot capture the design semantics particularly relating to collection types. Our object-relational methodology solves this problem.

Teaching object-oriented design with heuristics

The transition from "programmer" to "class designer" is difficult. Pedagogic challenges involve imparting an indepth knowledge of the object-oriented (OO) paradigm; gaining a firm understanding of the software engineering principles at play and knowing when and where to apply them effectively.

An Object-Oriented approach to the design of Geographic Information Systems

The applicability of the Object-Oriented (OO) approach to Geographic Information Systems (GISs) is analyzed. In software engineering, the OO approach as a design model, has been proven to produce quality software. It appears that GISs might also benefit from the OO approach. However, a GIS also imposes special ( e.g., spatial) requirements, inclusion of which in the OO model has to be investigated. The proposed solution tries to meet these special requirements by incorporating two data structures: the R-tree and the Binary Line Generalization (BLG) tree. The latter is a novel data structure introduced in this document.