scholarly journals An empirical evaluation of metrics on aspect-oriented programs

2019 ◽  
Vol 3 (2) ◽  
pp. 74
Author(s):  
Mazen Ismaeel Ghareb ◽  
Garry Allen
Keyword(s):  
Software Maintenance ◽  
Software Metrics ◽  
Current Model ◽  
Empirical Studies ◽  
Empirical Evaluation ◽  
Object Oriented Programming ◽  
Quality Model ◽  
Application Systems ◽  
Programming Quality ◽  
Dynamic Metrics

   The quality evaluation of software metrics measurement is considered as the primary indicator of imperfection prediction and software maintenance in various empirical studies of software products. However, there is no agreement on which metrics are compelling quality pointers for new software development approaches such as aspect-oriented programming (AOP) techniques. AOP intends to enhance programming quality by providing fundamentally different parts of the systems, for example, pointcuts, advice, and intertype relationships. Hence, it is not evident if quality characteristics for AOP could be extracted from direct expansions of traditional object-oriented programming (OOP) measurements. Then again, investigations of AOP do regularly depend on established static and dynamic metrics measurement; notwithstanding the late research of AOP in empirical studies, few analyses been adopted using the International Organization for Standardization 9126 quality model as useful markers of flaw inclination in this context. This paper examination we have considered different programming quality models given by various authors every once in a while and distinguished that adaptability was deficient in the current model. We have testing 10 projects developed by AOP. We have used many applications to extract the metrics, but none of them could extract all AOP Metrics. It only can measure some of AOP Metrics, not all of them. This study investigates the suitable framework for extract AOP Metrics, for instance, static and dynamic metrics measurement for hybrid application systems (AOP and OOP) or only AOP application.

scholarly journals Copula-based software metrics aggregation

2021 ◽  
Author(s):  
Maria Ulan ◽  
Welf Löwe ◽  
Morgan Ericsson ◽  
Anna Wingkvist
Keyword(s):  
Open Source Software ◽  
Software Metrics ◽  
Information Quality ◽  
Empirical Studies ◽  
Probabilistic Approach ◽  
Software Systems ◽  
Quality Model ◽  
Quality Models ◽  
Joint Distributions ◽  
Abstract Notion

AbstractA quality model is a conceptual decomposition of an abstract notion of quality into relevant, possibly conflicting characteristics and further into measurable metrics. For quality assessment and decision making, metrics values are aggregated to characteristics and ultimately to quality scores. Aggregation has often been problematic as quality models do not provide the semantics of aggregation. This makes it hard to formally reason about metrics, characteristics, and quality. We argue that aggregation needs to be interpretable and mathematically well defined in order to assess, to compare, and to improve quality. To address this challenge, we propose a probabilistic approach to aggregation and define quality scores based on joint distributions of absolute metrics values. To evaluate the proposed approach and its implementation under realistic conditions, we conduct empirical studies on bug prediction of ca. 5000 software classes, maintainability of ca. 15000 open-source software systems, and on the information quality of ca. 100000 real-world technical documents. We found that our approach is feasible, accurate, and scalable in performance.

scholarly journals Quality Metrics measurement for Hybrid Systems (Aspect Oriented Programming – Object Oriented Programming)

2021 ◽  
Vol 3 (3) ◽  
pp. 82-99
Author(s):  
Mazen Ismaeel Ghareb ◽  
Gary Allen
Keyword(s):  
Software Metrics ◽  
Object Oriented ◽  
Quality Metrics ◽  
Object Oriented Programming ◽  
Software Analysis ◽  
Programming Software ◽  
Dynamic Software ◽  
Software Quality Metrics ◽  
Dynamic Metrics ◽  
New Framework

This paper explores a new framework for calculating hybrid system metrics using software quality metrics aspect-oriented and object-oriented programming. Software metrics for qualitative and quantitative measurement is a mix of static and dynamic software metrics. It is noticed from the literature survey that to date, most of the architecture considered only the evaluation focused on static metrics for aspect-oriented applications. In our work, we mainly discussed the collection of static parameters ,  long with AspectJ-specific dynamic software metrics.The structure may provide a new direction for research while predicting software attributes because earlier dynamic metrics were ignored when evaluating quality attributes such as maintainability, reliability, and understandability of Asepect Oriented software. Dynamic metrics based on the  fundamentals of software engineering are equally crucial for software analysis as are static metrics. A similar concept is borrowed with the introduction of dynamic software metrics to implement aspect-riented software development.Currently, we only propose a structure and model using static and dynamic parameters to test the aspect-oriented method, but we still need to validate the proposed approach.

scholarly journals Hybrid Maintainability Prediction using Soft Computing Techniques

2021 ◽  
pp. 350-356
Author(s):  
Manju Duhan ◽  
Pradeep Kumar Bhatia
Keyword(s):  
Soft Computing ◽  
Software Maintenance ◽  
Software Metrics ◽  
Fuzzy Model ◽  
Object Oriented ◽  
Dynamic Binding ◽  
Proposed Model ◽  
Soft Computing Techniques ◽  
Run Time ◽  
Dynamic Metrics

Effective software maintenance is a crucial factor to measure that can be achieved with the help of software metrics. In this paper, authors derived a new approach for measuring the maintainability of software based on hybrid metrics that takes advantages of both i.e. static metrics and dynamic metrics in an object-oriented environment whereas, dynamic metrics capture the run time features of object-oriented languages i.e. run time polymorphism, dynamic binding etc. which is not covered by static metrics. To achieve this, the authors proposed a model based on static and hybrid metrics to measure maintainability factor by using soft computing techniques and it is found that the proposed neuro-fuzzy model was trained well and predict adequate results with MAE 0.003 and RMSE 0.009 based on hybrid metrics. Additionally, the proposed model was validated on two test datasets and it is concluded that the proposed model performed well, based on hybrid metrics.

scholarly journals Design of testing framework for code smell detection (OOPS) using BFO algorithm

2018 ◽  
Vol 7 (2.27) ◽  
pp. 161
Author(s):  
Pratiksha Sharma ◽  
Er. Arshpreet Kaur
Keyword(s):  
Software Metrics ◽  
Software Evolution ◽  
False Positive Rate ◽  
Optimization Technique ◽  
Research Work ◽  
Object Oriented Programming ◽  
Detection Methods ◽  
Major Drawback ◽  
Code Refactoring ◽  
Code Smell

Detection of bad smells refers to any indication in the program code of a execution that perhaps designate a issue, maintain the software and software evolution. Code Smell detection is a main challenging for software developers and their informal classification direct to the designing of various smell detection methods and software tools. It appraises 4 code smell detection tool in software like as a in Fusion, JDeodorant, PMD and Jspirit. In this research proposes a method for detection the bad code smells in software is called as code smell. Bad smell detection in software, OOSMs are used to identify the Source Code whereby Plug-in were implemented for code detection in which position of program initial code the bad smell appeared so that software refactoring can then acquire position. Classified the code smell, as a type of codes: long method, PIH, LPL, LC, SS and GOD class etc. Detection of the code smell and as a result applying the correct detection phases when require is significant to enhance the Quality of the code or program. The various tool has been proposed for detection of the code smell each one featured by particular properties. The main objective of this research work described our proposed method on using various tools for code smell detection. We find the major differences between them and dissimilar consequences we attained. The major drawback of current research work is that it focuses on one particular language which makes them restricted to one kind of programs only. These tools fail to detect the smelly code if any kind of change in environment is encountered. The base paper compares the most popular code smell detection tools on basis of various factors like accuracy, False Positive Rate etc. which gives a clear picture of functionality these tools possess. In this paper, a unique technique is designed to identify CSs. For this purpose, various object-oriented programming (OOPs)-based-metrics with their maintainability index are used. Further, code refactoring and optimization technique are applied to obtain low maintainability Index. Finally, the proposed scheme is evaluated to achieve satisfactory results. The results of the BFOA test defined that the lazy class caused framework defects in DLS, DR, and SE. However, the LPL caused no framework defects what so ever. The consequences of the connection rules test searched that the LCCS (Lazy Class Code Smell) caused structured defects in DE and DLS, which corresponded to the consequences of the BFOA test. In this research work, a proposed method is designed to verify the code smell. For this purpose, different OOPs based Software Metrics with their MI (Maintainability Index) are utilized. Further Code refactoring and optimization method id applied to attained the less maintainability index and evaluated to achieved satisfactory results.    

Software Metrics and Design Quality in Object Oriented Paradigm

2011 ◽  
pp. 256-272
Author(s):  
Gopalakrishnan T.R. Nair ◽  
Selvarani R
Keyword(s):  
Risk Assessment ◽  
Software Metrics ◽  
Research Effort ◽  
Object Oriented ◽  
Object Oriented Programming ◽  
Quality Factors ◽  
Engineering Software ◽  
Building Models ◽  
Future Challenges ◽  
Significant Research

As the object oriented programming languages and development methodologies moved forward, a significant research effort was spent in defining specific approaches and building models for quality based on object oriented measurements. Software metrics research and practice have helped in building an empirical basis for software engineering. Software developers require objectives and valid measurement schemes for the evaluation and improvisation of product quality from the initial stages of development. Measuring the structural design properties of a software system such as coupling, inheritance, cohesion, and complexity is a promising approach which can lead to an early quality assessment. The class codes and class diagrams are the key artifacts in the development of object oriented (OO) software and it constitutes the backbone of OO development. It also provides a solid foundation for the design and development of software with a greater influence over the system that is implemented. This chapter presents a survey of existing relevant works on class code / class diagram metrics in an elaborate way. Here, a critical review of the existing work is carried out in order to identify the lessons learnt regarding the way these studies are performed and reported. This work facilitates the development of an empirical body of knowledge. The classical approaches based on statistics alone do not provide managers and developers with a decision support scheme for risk assessment and cost reduction. One of the future challenges is to use software metrics in a way that they creatively address and handle the key objectives of risk assessment and the estimation of external quality factors of the software.

Using Design of Experiments to Analyze Open Source Software Metrics for Change Impact Estimation

2019 ◽  
Vol 10 (1) ◽  
pp. 16-33
Author(s):  
Miloud Dahane ◽  
Mustapha Kamel Abdi ◽  
Mourad Bouneffa ◽  
Adeel Ahmad ◽  
Henri Basson
Keyword(s):  
Statistical Analysis ◽  
Design Of Experiments ◽  
Open Source Software ◽  
Software Maintenance ◽  
Software Metrics ◽  
Software Evolution ◽  
Measurement Tool ◽  
Software Artifacts ◽  
Change Impact ◽  
Evolution Control

Software evolution control mostly relies on the better structure of the inherent software artifacts and the evaluation of different qualitative factors like maintainability. The attributes of changeability are commonly used to measure the capability of the software to change with minimal side effects. This article describes the use of the design of experiments method to evaluate the influence of variations of software metrics on the change impact in developed software. The coupling metrics are considered to analyze their degree of contribution to cause a change impact. The data from participant software metrics are expressed in the form of mathematical models. These models are then validated on different versions of software to estimate the correlation of coupling metrics with the change impact. The proposed approach is evaluated with the help of a set of experiences which are conducted using statistical analysis tools. It may serve as a measurement tool to qualify the significant indicators that can be included in a Software Maintenance dashboard.

Empirical Evaluation of High-speed Cost-effective Ro-FSO System by Incorporating OCDMA-PDM Scheme under the Presence of Fog

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Sushank Chaudhary ◽  
Sunita Choudhary ◽  
Xuan Tang ◽  
Xian Wei
Keyword(s):  
Free Space ◽  
High Speed ◽  
Optical Network ◽  
Empirical Evaluation ◽  
Cost Effective ◽  
Free Space Optics ◽  
Space Optics ◽  
Optical Cable ◽  
Application Systems ◽  
Support Cost

AbstractRadio over free space optics (Ro-FSO) innovation saddles the vast limit of optical fiber and the portability from local to remote systems. To enhance the capacity of Ro-FSO systems without compromising the bandwidth, this work incorporates use of hybrid polarization division multiplexing (PDM) with optical code division multiplexing (OCDMA) schemes. Due to low deployment time and support cost, the vast majority of the current optical network application systems adopts free space optics (FSO) as the elective answer for suitably supplanting fiber optical cable. This study has incorporated PDM and OCDMA schemes to design a 50 Gbps Ro-FSO link. Ten channels, each with 5 Gbps of data, are transported via FSO link of 3500 m. In addition, the proposed PDM-OCDMA-Ro-FSO link is evaluated under various atmospheric commotions.

Using Ensembles for Class-Imbalance Problem to Predict Maintainability of Open Source Software

2020 ◽  
Vol 27 (05) ◽  
pp. 2040011
Author(s):  
Ruchika Malhotra ◽  
Kusum Lata
Keyword(s):  
Software Maintenance ◽  
Software Metrics ◽  
Performance Metrics ◽  
Class Imbalance ◽  
Maintenance Cost ◽  
Class Imbalance Problem ◽  
Imbalanced Datasets ◽  
Minority Class ◽  
Imbalance Problem ◽  
Ensemble Techniques

To facilitate software maintenance and save the maintenance cost, numerous machine learning (ML) techniques have been studied to predict the maintainability of software modules or classes. An abundant amount of effort has been put by the research community to develop software maintainability prediction (SMP) models by relating software metrics to the maintainability of modules or classes. When software classes demanding the high maintainability effort (HME) are less as compared to the low maintainability effort (LME) classes, the situation leads to imbalanced datasets for training the SMP models. The imbalanced class distribution in SMP datasets could be a dilemma for various ML techniques because, in the case of an imbalanced dataset, minority class instances are either misclassified by the ML techniques or get discarded as noise. The recent development in predictive modeling has ascertained that ensemble techniques can boost the performance of ML techniques by collating their predictions. Ensembles themselves do not solve the class-imbalance problem much. However, aggregation of ensemble techniques with the certain techniques to handle class-imbalance problem (e.g., data resampling) has led to several proposals in research. This paper evaluates the performance of ensembles for the class-imbalance in the domain of SMP. The ensembles for class-imbalance problem (ECIP) are the modification of ensembles which pre-process the imbalanced data using data resampling before the learning process. This study experimentally compares the performance of several ECIP using performance metrics Balance and g-Mean over eight Apache software datasets. The results of the study advocate that for imbalanced datasets, ECIP improves the performance of SMP models as compared to classic ensembles.

Quality Assessment of Standard and Customized COTS Products

2020 ◽  
Vol 11 (3) ◽  
pp. 1-13
Author(s):  
Sudhaman Parthasarathy ◽  
C. Sridharan ◽  
Thangavel Chandrakumar ◽  
S. Sridevi
Keyword(s):  
Software Quality ◽  
Enterprise Resource Planning ◽  
Software Metrics ◽  
Resource Planning ◽  
Quality Attributes ◽  
Future Research ◽  
Quality Model ◽  
Erp System ◽  
Cots Products ◽  
Commercial Off The Shelf

Software quality is a very important aspect in evolving strategy for IT vendors involved in commercial off-the-shelf (COTS) (also referred as packaged software) product development. Software metrics are widely accepted measures for monitoring and managing the quality in software projects. Enterprise resource planning (ERP) systems are COTS products and attempt to integrate data and processes in organizations and often require extensive customization. Using software quality metrics already established in literature, software quality attributes defined by the quality model ISO/IEC 9126 were evaluated for a standard and a customized ERP product. This will help the ERP team to identify the specific quality attributes that were affected owing to customization. This research study infers that there exists a considerable impact of ERP system customization over the quality of ERP product. The implications of the findings for both practice and research are discussed, and possible areas of future research are identified.

scholarly journals Empirical Studies for the Assessment of the Effectiveness of Design Patterns in Migration between Software Architectures of Embedded Applications

2012 ◽  
Vol 2012 ◽  
pp. 1-14
Author(s):  
Farah Lakhani ◽  
Michael J. Pont
Keyword(s):  
Design Patterns ◽  
Broad Class ◽  
Empirical Studies ◽  
Empirical Evaluation ◽  
Software Architectures ◽  
Migration Process ◽  
Specific Goal ◽  
Develop Software ◽  
Embedded Applications ◽  
Improve Reliability

Two main architectures used to develop software for modern embedded applications are “event triggered” (ET) and “time triggered” (TT). ET designs involve creating systems which handle multiple interrupts; by contrast, only one interrupt is ever enabled in a TT design, and this interrupt is usually linked to a timer “Tick.” Although TT architectures are widely used in safety-related designs, they are less familiar to developers of mainstream embedded systems. The work on this research began from the premise that—for a broad class of systems—the use of a TT architecture would improve reliability. The overall goal of the work presented here was to identify ways in which the effort involved in migrating between existing ET architectures and “equivalent” TT architectures could be reduced. The specific goal of the research was to explore whether the use of an appropriate set of design patterns could assist developers who wished to migrate between ET and TT designs. An empirical evaluation of the efficacy of a newly proposed pattern collection is described in this paper. The results of these trials demonstrate that the proposed collection of patterns has the potential to support developers by helping them to take appropriate decisions during the migration process.

Sign in / Sign up

Export Citation Format

Share Document