Search results for: Mohammad Azzeh

Items from 1 to 20 out of 27 results

article

A soft computing approach for software defect density prediction

Mohammad Azzeh, Yousef Alqasrawi, Yousef Elsheikh

Journal of Software: Evolution and Process > 36 > 4 > n/a - n/a

Defect density is an essential software testing and maintenance aspect that determines the quality of software products. It is used as a management factor to distribute limited human resources successfully. The availability of public defect datasets facilitates building defect density prediction models using established static code metrics. Since the data gathered for software modules are often subject...

article

Software Defect Prediction Using Non-Dominated Sorting Genetic Algorithm and k-Nearest Neighbour Classifier

Mohammad Azzeh, Ali Bou Nassif, Manar Abu Talib, Hajra Iqba

e-Informatica Software Engineering Journal > 2024 > Vol. 18, nr 1 > 240103

Background: Software Defect Prediction (SDP) is a vital step in software development. SDP aims to identify the most likely defect-prone modules before starting the testing phase, and it helps assign resources and reduces the cost of testing. Aim: Although many machine learning algorithms have been used to classify software modules based on static code metrics, the k-Nearest Neighbors (kNN) method...

article

Project productivity evaluation in early software effort estimation

Mohammad Azzeh, Ali Bou Nassif

Journal of Software: Evolution and Process > 30 > 12 > n/a - n/a

The productivity factor has long been a key driver to estimate effort from Use Case Points (UCP) size measure, especially when historical dataset is absent. But, no one questions: Does productivity still matter when historical data are also available? To facilitate answering this question, the present paper studies the role of productivity from 2 perspectives. First, does learning productivity from...

article

Analyzing the relationship between project productivity and environment factors in the use case points method

Mohammad Azzeh, Ali Bou Nassif

Journal of Software: Evolution and Process > 29 > 9 > n/a - n/a

Project productivity is a key factor for producing effort estimates from use case points (UCP), especially when the historical dataset is absent. The first versions of UCP effort estimation models used a fixed number or very limited numbers of productivity ratios for all new projects. These approaches have not been well examined over a large number of projects, so the validity of these studies was...

chapter

Robust Rank Aggregation method for Case-Base effort estimation

Ali Bou Nassif, Mohammad Azzeh, Shadi Banitaan

2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE) > 1 - 5

2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE)

It is well recognized that effort estimation is an essential part of successful software management. Among many estimation models, the Case-Base Effort Estimation (CBEE) has been intensively used among researchers and practitioners as a promising model for better and accurate effort prediction. The common challenges with this model are: (1) finding the nearest cases to the new case, (2) selecting...

chapter

User Movement Prediction: The Contribution of Machine Learning Techniques

Shadi Banitaan, Mohammad Azzeh, Ali Bou Nassif

2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA) > 571 - 575

2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA)

Ambient Assisted Living (AAL) aims to increase the time older people or disabled people can live in their home environment by assisting them in performing activities of daily living by the use of intelligent products. Localization and tracking of users in indoor environment are the main components of AAL. Wireless sensor networks is an effective technology to accomplish these services by using Received...

article

A hybrid model for estimating software project effort from Use Case Points

Mohammad Azzeh, Ali Bou Nassif

Applied Soft Computing > 2016 > 49 > C > 981-989

Early software effort estimation is a hallmark of successful software project management. Building a reliable effort estimation model usually requires historical data. Unfortunately, since the information available at early stages of software development is scarce, it is recommended to use software size metrics as key cost factor of effort estimation. Use Case Points (UCP) is a prominent size measure...

chapter

Preface

Mohammad Hijjawi, Mohammad Azzeh, Ahmad Al-Tamimi

2016 7th International Conference on Computer Science and Information Technology (CSIT) > 1 - 2

2016 7th International Conference on Computer Science and Information Technology (CSIT)

It is our privilege and pleasure to welcome you to the Seventh International Conference on Computer Science and Information Technology, CSIT 2016, in Amman, Jordan. The previous CSIT meetings were held all at Applied Science Private University. As an established international event and one of the main conferences for the computer science and information technology community, once again our conference...

article

Guest editorial: special issue on predictive analytics using machine learning

Ali Bou Nassif, Mohammad Azzeh, Shadi Banitaan, Daniel Neagu

Neural Computing and Applications > 2016 > 27 > 8 > 2153-2155

chapter

Software Project Similarity Measurement Based on Fuzzy C-Means

Mohammad Azzeh, Daniel Neagu, Peter Cowling

Lecture Notes in Computer Science > Making Globally Distributed Software Development a Success Story > Process Tools and Metrics > 123-134

A reliable and accurate similarity measurement between two software projects has always been a challenge for analogy-based software cost estimation. Since the effort for a new project is retrieved from similar historical projects, it is essentially to use the appropriate similarity measure that finds those close projects which in turn increases the estimation accuracy. In software engineering literature,...

chapter

Adjusted Case-Based Software Effort Estimation Using Bees Optimization Algorithm

Mohammad Azzeh

Lecture Notes in Computer Science > Knowlege-Based and Intelligent Information and Engineering Systems > Other / Misc. Intelligent Systems Topics > 315-324

Case-Based Reasoning (CBR) has achieved a considerable interest from researchers for solving non-trivial or ill-defined problems such as those encountered by project managers including support for software project management in predictions and lesson learned. Software effort estimation is the key factor for successful software project management. In particular, the use of CBR for effort estimation...

chapter

An Application of Classification and Class Decomposition to Use Case Point Estimation Method

Mohammad Azzeh, Ali Bou nassif, Shadi Banitaan

2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA) > 1268 - 1271

2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA)

Use Case Points (UCP) estimation method describes the process of computing the software project size and productivity from use case diagram elements. These metrics are then used to predict the project effort at early stage of software development. The main challenges with previous models are that they were constructed based on a very limited number of observations, and using limited productivity ratios...

chapter

Class Decomposition Using K-Means and Hierarchical Clustering

Shadi Banitaan, Ali Bou Nassif, Mohammad Azzeh

2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA) > 1263 - 1267

2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA)

This paper presents a clustering-based class decomposition approach to improve the performance of classifiers. Class decomposition works by dividing each class into clusters, and by relabeling instances contained by each cluster with a new class. Several case studies used class decomposition combined with linear classifiers. While there is an essential improvement in classification accuracy because...

article

Neural network models for software development effort estimation: a comparative study

Ali Bou Nassif, Mohammad Azzeh, Luiz Fernando Capretz, Danny Ho

Neural Computing and Applications > 2016 > 27 > 8 > 2369-2381

Software development effort estimation (SDEE) is one of the main tasks in software project management. It is crucial for a project manager to efficiently predict the effort or cost of a software project in a bidding process, since overestimation will lead to bidding loss and underestimation will cause the company to lose money. Several SDEE models exist; machine learning models, especially neural...

article

Pareto efficient multi-objective optimization for local tuning of analogy-based estimation

Mohammad Azzeh, Ali Bou Nassif, Shadi Banitaan, Fadi Almasalha

Neural Computing and Applications > 2016 > 27 > 8 > 2241-2265

Analogy-based effort estimation (ABE) is one of the prominent methods for software effort estimation. The fundamental concept of ABE is closer to the mentality of expert estimation but with an automated procedure in which the final estimate is generated by reusing similar historical projects. The main key issue when using ABE is how to adapt the effort of the retrieved nearest neighbors. The adaptation...

article

An empirical evaluation of ensemble adjustment methods for analogy-based effort estimation

Mohammad Azzeh, Ali Bou Nassif, Leandro L. Minku

The Journal of Systems & Software > 2015 > 103 > Complete > 36-52

Effort adjustment is an essential part of analogy-based effort estimation, used to tune and adapt nearest analogies in order to produce more accurate estimations. Currently, there are plenty of adjustment methods proposed in literature, but there is no consensus on which method produces more accurate estimates and under which settings. This paper investigates the potential of ensemble learning for...

article

Analogy-based effort estimation: a new method to discover set of analogies from dataset characteristics

Mohammad Azzeh, Ali Bou Nassif

IET Software > 2015 > 9 > 2 > 39 - 50

Analogy-based effort estimation (ABE) is one of the efficient methods for software effort estimation because of its outstanding performance and capability of handling noisy datasets. Conventional ABE models usually use the same number of analogies for all projects in the datasets in order to make good estimates. The authors’ claim is that using same number of analogies may produce overall best performance...

chapter

Fuzzy Model Tree for Early Effort Estimation

Mohammad Azzeh, Ali Bou Nassif

2013 12th International Conference on Machine Learning and Applications > 2 > 117 - 121

2013 12th International Conference on Machine Learning and Applications (ICMLA)

Use Case Points (UCP) is a well-known method to estimate the project size, based on Use Case diagram, at early phases of software development. Although the Use Case diagram is widely accepted as a de-facto model for analyzing object oriented software requirements over the world, UCP method did not take sufficient amount of attention because, as yet, there is no consensus on how to produce software...

chapter

A comparison between decision trees and decision tree forest models for software development effort estimation

Ali Bou Nassif, Mohammad Azzeh, Luiz Fernando Capretz, Danny Ho

2013 Third International Conference on Communications and Information Technology (ICCIT) > 220 - 224

2013 International Conference on Communications and Information Technology (ICCIT)

Accurate software effort estimation has been a challenge for many software practitioners and project managers. Underestimation leads to disruption in the project's estimated cost and delivery. On the other hand, overestimation causes outbidding and financial losses in business. Many software estimation models exist; however, none have been proven to be the best in all situations. In this paper, a...

chapter

Software cost estimation based on use case points for global software development

Mohammad Azzeh

2013 5th International Conference on Computer Science and Information Technology > 214 - 218

2013 5th International Conference on Computer Science and Information Technology (CSIT)

This paper investigates the applicability of Use Case Point estimation model to global software project development. Nowadays, there is growing trend among leading software companies to outsource their project geographically, in countries with lower labor rate. This new trend increases competitiveness in the software market, which in turn shortens the development lifecycle time. This leads to several...

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INFONA - science communication portal

Search results for: Mohammad Azzeh

A soft computing approach for software defect density prediction

Software Defect Prediction Using Non-Dominated Sorting Genetic Algorithm and k-Nearest Neighbour Classifier

Project productivity evaluation in early software effort estimation

Analyzing the relationship between project productivity and environment factors in the use case points method

Robust Rank Aggregation method for Case-Base effort estimation

User Movement Prediction: The Contribution of Machine Learning Techniques

A hybrid model for estimating software project effort from Use Case Points

Preface

Guest editorial: special issue on predictive analytics using machine learning

Software Project Similarity Measurement Based on Fuzzy C-Means

Adjusted Case-Based Software Effort Estimation Using Bees Optimization Algorithm

An Application of Classification and Class Decomposition to Use Case Point Estimation Method

Class Decomposition Using K-Means and Hierarchical Clustering

Neural network models for software development effort estimation: a comparative study

Pareto efficient multi-objective optimization for local tuning of analogy-based estimation

An empirical evaluation of ensemble adjustment methods for analogy-based effort estimation

Analogy-based effort estimation: a new method to discover set of analogies from dataset characteristics

Fuzzy Model Tree for Early Effort Estimation

A comparison between decision trees and decision tree forest models for software development effort estimation

Software cost estimation based on use case points for global software development

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