ESSENT: an arithmetic optimization algorithm with enhanced scatter search strategy for automated test case generation

Article Computer Science, Software Engineering

Some Seeds Are Strong: Seeding Strategies for Search-based Test Case Selection

Aitor Arrieta et al.

Summary: This article proposes seeding strategies for the test case selection problem, which help to improve the performance of multi-objective search algorithms and find better solutions.

ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY (2023)

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Article Computer Science, Hardware & Architecture

Fog computing approaches in IoT-enabled smart cities

Maryam Songhorabadi et al.

Summary: The development of smart cities heavily relies on advanced computing paradigms, such as fog computing, to address the requirements of location-aware, latency-sensitive, and security-crucial applications. However, the frequently used cloud-based approaches in smart cities restrict the security, time-sensitive services, flexibility, and reliability. This paper proposes a study to explore the state-of-the-art fog-based approaches in smart cities and presents a classification of these approaches into service-based, resource-based, and application-based classes.

JOURNAL OF NETWORK AND COMPUTER APPLICATIONS (2023)

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Article Computer Science, Information Systems

A Framework for Smart Home System with Voice Control Using NLP Methods

Yuliy Iliev et al.

Summary: The rapid development of information technology and ubiquitous computing has transformed electronic devices from isolated islands of data and control to interconnected parts of intelligent systems. These network-based systems have advanced features, including IoT sensors and actuators, multiple connectivity options, and multimodal user interfaces, enabling remote monitoring and management. To develop a smart home system human machine interface with speech recognition, a new IoT-fog-cloud framework using natural language processing (NLP) methods is proposed. The framework adds utterance to command transformation to existing cloud-based speech-to-text and text-to-speech services, providing flexibility for different automation systems and languages.

ELECTRONICS (2023)

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Article Computer Science, Software Engineering

Instance Space Analysis of Search-Based Software Testing

Neelofar Neelofar et al.

Summary: Search-based software testing (SBST) is a mature area with techniques developed to tackle the challenging task of software testing. SBST techniques have been successfully applied in the industry to generate test cases for large and complex software systems. However, their effectiveness depends on the problem being addressed. This paper revisits the evaluation of SBST techniques using Instance Space Analysis (ISA) to visualize and assess their strengths and weaknesses across a broad range of problem instances from common benchmark datasets. The paper also examines the diversity and quality of benchmark datasets used in experimental evaluations.

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING (2023)

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Article Computer Science, Artificial Intelligence

Arithmetic optimization algorithm based on elementary function disturbance for solving economic load dispatch problem in power system

Wen-Kuo Hao et al.

Summary: This study proposes an improved Arithmetic Optimization Algorithm (AOA) based on elementary function disturbance to solve the economic load dispatch (ELD) problem. Experimental results demonstrate that the proposed algorithm performs the best in solving ELD problems.

APPLIED INTELLIGENCE (2022)

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Article Computer Science, Hardware & Architecture

Hybrid binary arithmetic optimization algorithm with simulated annealing for feature selection in high-dimensional biomedical data

Elham Pashaei et al.

Summary: This article introduces a new hybrid filter/wrapper gene selection method, mRMR-BAOAC-SA, to address the issue of redundant, noisy, and irrelevant genes in gene expression data. The proposed method was evaluated on multiple microarray datasets and demonstrated better classification accuracy and minimum selected genes compared to other methods.

JOURNAL OF SUPERCOMPUTING (2022)

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Article Computer Science, Artificial Intelligence

Multi-objective scheduling of IoT-enabled smart homes for energy management based on Arithmetic Optimization Algorithm: A Node-RED and NodeMCU module-based technique

Danial Bahmanyar et al.

Summary: This paper introduces a home energy management system based on IoT technology, which manages energy consumption by optimizing appliance scheduling and achieves demand side management. A multi-objective arithmetic optimization algorithm is used to find the optimal scheduling pattern, and the integration with renewable energy sources improves user comfort.

KNOWLEDGE-BASED SYSTEMS (2022)

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Article Computer Science, Software Engineering

Enhancing Dynamic Symbolic Execution by Automatically Learning Search Heuristics

Sooyoung Cha et al.

Summary: This paper introduces a technique for automatically generating search heuristics for dynamic symbolic execution with the goal of overcoming the challenge of exploring program execution paths effectively. By automatically learning search heuristics, the technique outperforms existing manually-crafted heuristics in terms of branch coverage and bug-finding.

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING (2022)

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Article Computer Science, Information Systems

Manifold-Inspired Search-Based Algorithm for Automated Test Case Generation

Fangqing Liu et al.

Summary: Automated test case generation based on path coverage is a complex problem due to the relationship between path and test cases. This article presents a manifold-inspired search algorithm that decomposes the search space and reduces redundant function evaluations. The algorithm finds equivalent mapping subspaces and generates test cases with high path coverage rates.

IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTING (2022)

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Article Automation & Control Systems

Automated test case generation for path coverage by using grey prediction evolution algorithm with improved scatter search strategy

Gaocheng Cai et al.

Summary: This paper introduces an automated test case generation for path coverage method based on grey prediction evolution algorithm, which achieves high path coverage in shorter running time by utilizing an improved scatter search strategy. Experimental results demonstrate its superiority over some state-of-the-art algorithms.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2021)

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Article Engineering, Multidisciplinary

The Arithmetic Optimization Algorithm

Laith Abualigah et al.

Summary: The Arithmetic Optimization Algorithm (AOA) is a new meta-heuristic method that makes use of the distribution behavior of arithmetic operators, demonstrating promising results in solving challenging optimization problems across various search spaces.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2021)

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Article Computer Science, Artificial Intelligence

Binary searching iterative algorithm for generating test cases to cover paths

Gaocheng Cai et al.

Summary: The paper proposes a search-based algorithm for generating test cases to satisfy path coverage criterion, which achieves high path coverage and requires significantly fewer test cases compared to other algorithms in experiments.

APPLIED SOFT COMPUTING (2021)

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Article Computer Science, Interdisciplinary Applications

Automated test case generation based on differential evolution with node branch archive

Xiaohu Dai et al.

Summary: ATCG is an active research topic in software testing engineering that can reduce testing costs, but redundant test cases exist in path coverage testing. By implementing a node branch archive strategy, search-based algorithms can cover more paths effectively.

COMPUTERS & INDUSTRIAL ENGINEERING (2021)

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Article Computer Science, Artificial Intelligence

Search-Based Algorithm With Scatter Search Strategy for Automated Test Case Generation of NLP Toolkit

Fangqing Liu et al.

Summary: A scatter search strategy is proposed in the study to automatically generate test cases covering all possible paths of NLP programs, which can effectively save test cases and running time consumptions.

IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE (2021)

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Article Computer Science, Artificial Intelligence