Guest Editors
Dr. Dac-Nhuong Le, Haiphong University, Vietnam.
Dr. Harish Garg, Thapar Institute of Engineering and Technology, Deemed University, Patiala, Punjab, India.
Dr. João Manuel R. S. Tavares, Universidade do Porto, Portugal.
Summary
As software systems are becoming more and more large and complex, there are various challenges posed by these systems. A software goes through various stages before it can be deployed such as requirements elicitation, software designing, software project planning, software coding, software testing and maintenance. In each of these stages, there are a number of tasks or activities involved. Due to large and complex nature of software, these software engineering tasks have become increasingly costly and more prone to errors. Thus, there is a demand to explore computational intelligent techniques to carry out different software engineering tasks. Computational intelligence is related to artificial intelligence where the heuristic algorithms are designed and used to give a good output in a reasonable amount of time. These algorithms have been used in different fields such as medical science, bioinformatics, computer networks (for routing and scheduling), and forecasting. In addition, researchers have applied intelligent techniques to various domains of software engineering as well such as software requirement prioritization, software cost estimation, reliability assessment, software defect prediction, maintainability prediction, quality prediction, size estimation, software vulnerability prediction, software test case prioritization and many more. Computational techniques such as evolutionary algorithms, machine learning approaches, meta-heuristic algorithms, and optimization schemes, are different types of intelligent techniques frequently used. Optimization algorithms can be used for obtaining a solution to a problem where the goals or targets to be achieved are known. Machine learning algorithms are used when we have sufficient data using which knowledge can be extracted and models can be trained. For example, models can be developed for predicting error prone classes of software. A meta-heuristic is a high-level, iterative process that guides and manipulates an underlying heuristic to efficiently explore the search space. The underlying heuristic can be a local search, or a low or high-level procedure. Meta-heuristics provide near optimal solutions with high accuracy and limited resources in a reasonable amount of time by exploiting the search space. For this book, researchers, academicians and professionals are going to be invited to contribute with chapters expressing their ideas and research in the application of intelligent techniques to the field of software engineering. Both theoretical contributions and practical applications in the area of intelligent techniques are welcome.
Potential topics include, but are not limited to, the following:
• Artificial intelligence techniques for improving software development
• Bio-Inspired optimization techniques for software engineering
• Computational intelligence and quantitative software engineering
• Computational techniques to solve class imbalance problem
• Computational intelligence approaches for software quality improvement
• Search algorithms for test case prioritization
• Test case generation using intelligent algorithms
• Intelligent requirement elicitation to optimize software quality
• Software cost estimation models using machine learning
• Artificial intelligence in predictive maintenance
• Developing intelligent systems for software design
• Use of intelligent techniques for analyzing software repositories
• Assessing intelligent text classification techniques
• Software quality prediction using intelligent techniques
• Intelligent feature selection techniques
• Intelligent computing techniques for software reliability prediction
• Soft computing techniques for software effort models
• Intelligent computing techniques for schedule estimation models.
• Artificial intelligence in prediction of software maintenance effort.
• Artificial intelligence in for software quality prediction.
• Artificial intelligence in software vulnerability prediction.
• Developing intelligent systems for software defect prediction models
• Artificial intelligence in software cost estimation
Keywords
Software engineering, software development, software quality, computational intelligence, artificial intelligence, bio-Inspired optimization, evolution algorithms, meta-heuristic algorithms, machine learning
Published Papers
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Open Access
ARTICLE
Code Smell Detection Using Whale Optimization Algorithm
Moatasem M. Draz, Marwa S. Farhan, Sarah N. Abdulkader, M. G. Gafar
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1919-1935, 2021, DOI:10.32604/cmc.2021.015586
（This article belongs to this Special Issue:
Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract Software systems have been employed in many fields as a means to reduce human efforts; consequently, stakeholders are interested in more updates of their capabilities. Code smells arise as one of the obstacles in the software industry. They are characteristics of software source code that indicate a deeper problem in design. These smells appear not only in the design but also in software implementation. Code smells introduce bugs, affect software maintainability, and lead to higher maintenance costs. Uncovering code smells can be formulated as an optimization problem of finding the best detection rules. Although researchers have recommended different techniques to…
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Open Access
ARTICLE
Optimal Selection of Hybrid Renewable Energy System Using Multi-Criteria Decision-Making Algorithms
Hegazy Rezk, Irik Z. Mukhametzyanov, Mujahed Al-Dhaifallah, Hamdy A. Ziedan
CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2001-2027, 2021, DOI:10.32604/cmc.2021.015895
（This article belongs to this Special Issue:
Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract Several models of multi-criteria decision-making (MCDM) have identified the optimal alternative electrical energy sources to supply certain load in an isolated region in Al-Minya City, Egypt. The load demand consists of water pumping system with a water desalination unit. Various options containing three different power sources: only DG, PV-B system, and hybrid PV-DG-B, two different sizes of reverse osmosis (RO) units; RO-250 and RO-500, two strategies of energy management; load following (LF) and cycle charging (CC), and two sizes of DG; 5 and 10 kW were taken into account. Eight attributes, including operating cost, renewable fraction, initial cost, the cost…
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Open Access
ARTICLE
Predicting Drying Performance of Osmotically Treated Heat Sensitive Products Using Artificial Intelligence
S. M. Atiqure Rahman, Hegazy Rezk, Mohammad Ali Abdelkareem, M. Enamul Hoque, Tariq Mahbub, Sheikh Khaleduzzaman Shah, Ahmed M. Nassef
CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3143-3160, 2021, DOI:10.32604/cmc.2021.015048
（This article belongs to this Special Issue:
Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract The main goal of this research is to develop and apply a robust Artificial Neural Networks (ANNs) model for predicting the characteristics of the osmotically drying treated potato and apple samples as a model heat-sensitive product in vacuum contact dryer. Concentrated salt and sugar solutions were used as the osmotic solutions at 27C. Series of experiments were performed at various temperatures of 35C, 40C, and 55C for conduction heat input under vacuum ( −760 mm Hg) condition. Some experiments were also performed in a pure vacuum without heat addition. Dimensionless moisture content (DMC), effective moisture diffusivity, and mass flux were…
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Open Access
ARTICLE
Analyzing Some Elements of Technological Singularity Using Regression Methods
Ishaani Priyadarshini, Pinaki Ranjan Mohanty, Chase Cotton
CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3229-3247, 2021, DOI:10.32604/cmc.2021.015250
（This article belongs to this Special Issue:
Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract Technological advancement has contributed immensely to human life and society. Technologies like industrial robots, artificial intelligence, and machine learning are advancing at a rapid pace. While the evolution of Artificial Intelligence has contributed significantly to the development of personal assistants, automated drones, smart home devices, etc., it has also raised questions about the much-anticipated point in the future where machines may develop intelligence that may be equal to or greater than humans, a term that is popularly known as Technological Singularity. Although technological singularity promises great benefits, past research works on Artificial Intelligence (AI) systems going rogue highlight the downside…
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Open Access
ARTICLE
New Improved Ranked Set Sampling Designs with an Application to Real Data
Amer Ibrahim Al-Omari, Ibrahim M. Almanjahie
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1503-1522, 2021, DOI:10.32604/cmc.2021.015047
（This article belongs to this Special Issue:
Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract This article proposes two new Ranked Set Sampling (RSS) designs for estimating the population parameters: Simple Z Ranked Set Sampling (SZRSS) and Generalized Z Ranked Set Sampling (GZRSS). These designs provide unbiased estimators for the mean of symmetric distributions. It is shown that for non-uniform symmetric distributions, the estimators of the mean under the suggested designs are more efficient than those obtained by RSS, Simple Random Sampling (SRS), extreme RSS and truncation based RSS designs. Also, the proposed RSS schemes outperform other RSS schemes and provide more efficient estimates than their competitors under imperfect rankings. The suggested mean estimators under…
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Open Access
ARTICLE
Energy Management Control Strategy for Renewable Energy System Based on Spotted Hyena Optimizer
Hegazy Rezk, Ahmed Fathy, Mokhtar Aly, Mohamed N. Ibrahim
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2271-2281, 2021, DOI:10.32604/cmc.2021.014590
（This article belongs to this Special Issue:
Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract Hydrocarbons, carbon monoxide and other pollutants from the transportation sector harm human health in many ways. Fuel cell (FC) has been evolving rapidly over the past two decades due to its efficient mechanism to transform the chemical energy in hydrogen-rich compounds into electrical energy. The main drawback of the standalone FC is its slow dynamic response and its inability to supply rapid variations in the load demand. Therefore, adding energy storage systems is necessary. However, to manage and distribute the power-sharing among the hybrid proton exchange membrane (PEM) fuel cell (FC), battery storage (BS), and supercapacitor (SC), an energy management…
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Open Access
ARTICLE
Test Case Generation from UML-Diagrams Using Genetic Algorithm
Rajesh Kumar Sahoo, Morched Derbali, Houssem Jerbi, Doan Van Thang, P. Pavan Kumar, Sipra Sahoo
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2321-2336, 2021, DOI:10.32604/cmc.2021.013014
（This article belongs to this Special Issue:
Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract Software testing has been attracting a lot of attention for effective software development. In model driven approach, Unified Modelling Language (UML) is a conceptual modelling approach for obligations and other features of the system in a model-driven methodology. Specialized tools interpret these models into other software artifacts such as code, test data and documentation. The generation of test cases permits the appropriate test data to be determined that have the aptitude to ascertain the requirements. This paper focuses on optimizing the test data obtained from UML activity and state chart diagrams by using Basic Genetic Algorithm (BGA). For generating the…
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Open Access
ARTICLE
Optimal Reordering Trace Files for Improving Software Testing Suitcase
Yingfu Cai, Sultan Noman Qasem, Harish Garg, Hamïd Parvïn, Kim-Hung Pho, Zulkefli Mansor
CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1225-1239, 2021, DOI:10.32604/cmc.2021.014699
（This article belongs to this Special Issue:
Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract An invariant can be described as an essential relationship between program variables. The invariants are very useful in software checking and verification. The tools that are used to detect invariants are invariant detectors. There are two types of invariant detectors: dynamic invariant detectors and static invariant detectors. Daikon software is an available computer program that implements a special case of a dynamic invariant detection algorithm. Daikon proposes a dynamic invariant detection algorithm based on several runs of the tested program; then, it gathers the values of its variables, and finally, it detects relationships between the variables based on a simple…
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Open Access
ARTICLE
Acceptance Sampling Plans with Truncated Life Tests for the Length-Biased Weighted Lomax Distribution
Amer Ibrahim Al-Omari, Ibrahim M. Almanjahie, Olena Kravchuk
CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 285-301, 2021, DOI:10.32604/cmc.2021.014537
（This article belongs to this Special Issue:
Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract In this paper, we considered the Length-biased weighted Lomax distribution and constructed new acceptance sampling plans (ASPs) where the life test is assumed to be truncated at a pre-assigned time. For the new suggested ASPs, the tables of the minimum samples sizes needed to assert a specific mean life of the test units are obtained. In addition, the values of the corresponding operating characteristic function and the associated producer’s risks are calculated. Analyses of two real data sets are presented to investigate the applicability of the proposed acceptance sampling plans; one data set contains the first failure of 20 small…
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Open Access
ARTICLE
A Holistic, Proactive and Novel Approach for Pre, During and Post Migration Validation from Subversion to Git
Vinay Singh, Mohammed Alshehri, Alok Aggarwal, Osama Alfarraj, Purushottam Sharma, K. R. Pardasani
CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2359-2371, 2021, DOI:10.32604/cmc.2021.013272
（This article belongs to this Special Issue:
Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract Software development is getting a transition from centralized version control systems (CVCSs) like Subversion to decentralized version control systems (DVCDs) like Git due to lesser efficiency of former in terms of branching, fusion, time, space, merging, offline commits & builds and repository, etc. Git is having a share of 77% of total VCS, followed by Subversion with a share of 13.5%. The majority of software industries are getting a migration from Subversion to Git. Only a few migration tools are available in the software industry. Still, these too lack in many features like lack of identifying the empty directories as…
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Open Access
ARTICLE
Design and Implementation of Wheel Chair Control System Using Particle Swarm Algorithm
G. Mousa, Amr Almaddah, Ayman A. Aly
CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2005-2023, 2021, DOI:10.32604/cmc.2020.012580
（This article belongs to this Special Issue:
Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract About 10–20% of every country’s population is disable. There are at least 650 million people with a kind of disability worldwide. Assistance and support are perquisites for many handicap people for participating in society. Electric powered wheelchairs provide efficient mobility to motor impaired persons. In this paper a smart controller of a wheel chair mobile robot using Particle Swarm Optimization Proportional controller (
PSO-P) was proposed where (
PSO) algorithm was utilized to tune the proportional controller’s gains for each axis. Aiming to improve wheelchair tracking trajectory, a kinematic model of a robot with linear and angular velocities parameters was developed. The…
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Open Access
ARTICLE
Optimizing Bidders Selection of Multi-Round Procurement Problem in Software Project Management Using Parallel Max-Min Ant System Algorithm
Dac-Nhuong Le, Gia Nhu Nguyen, Harish Garg, Quyet-Thang Huynh, Trinh Ngoc Bao, Nguyen Ngoc Tuan
CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 993-1010, 2021, DOI:10.32604/cmc.2020.012464
（This article belongs to this Special Issue:
Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract This paper presents a Game-theoretic optimization via Parallel MinMax Ant System (PMMAS) algorithm is used in practice to determine the Nash
equilibrium value to resolve the confusion in choosing appropriate bidders of
multi-round procurement problem in software project management. To this end,
we introduce an approach that proposes: (i) A Game-theoretic model of multiround procurement problem (ii) A Nash equilibrium strategy corresponds to multi-round strategy bid (iii) An application of PSO for the determination of global
Nash equilibrium. The balance point in Nash Equilibrium can help to maintain
a sustainable structure not only in terms of project management but also…
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