Khaled Slhoub

Social Media vs. News Platforms: A Cross-analysis for Fake News Detection Using Web Scraping and NLP

Standardizing the Requirements Specification of Multi-Agent Systems

Social Media vs. News Platforms: A Cross-analysis for Fake News Detection Using Web Scraping and NLP

Proceedings of the 15th International Conference on PErvasive Technologies Related to Assistive Environments

A Software Quality Resource Tool that Improves Quality Management of Scaled-down Development Environments

Standardizing the Requirements Specification of Multi-Agent Systems

Detecting Amazon Bot Reviewers Using Unsupervised and Supervised Learning

2022 IEEE World AI IoT Congress (AIIoT), Jun 6, 2022

Detecting Amazon Bot Reviewers Using Unsupervised and Supervised Learning

2022 IEEE World AI IoT Congress (AIIoT)

Automated Framework to Extract Software Requirements from Source Code

Software maintenance and innovation are constant challenges across industries, especially as prog... more Software maintenance and innovation are constant challenges across industries, especially as programming languages evolve with technology. Similarly, poor lexicon quality degrades program comprehension, increasing the effort required by developers to improve existing software products. To address these challenges, we propose a novel automated framework that extracts software requirements directly from source code using a baseline AI language model applied to a Java code base. Leveraging natural language processing techniques, the framework validates programs and generates easily readable requirements by analyzing file contents. The framework enhances agility and flexibility by providing comprehensive documentation for existing software systems. It caters to both experienced and less-experienced developers, offering an intuitive graphical user interface and enabling efficient identification and resolution of errors. The resulting output facilitates natural interaction through language processing. By automating the extraction process, the framework allows developers to better understand software systems, make informed decisions, and adapt to evolving needs.

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An Agent-Based Approach Toward Smart Software Testing

Lecture notes in networks and systems, Dec 31, 2022

Recommended practices for the specification of multi-agent systems requirements

The lack of process standardization in the development of multi-agent systems (MAS) causes a grea... more The lack of process standardization in the development of multi-agent systems (MAS) causes a great deal of difficulty for developers in addressing major development phases, such as requirements analysis. Instead, such MAS infrastructure is generally attended to in an ad-hoc fashion and important aspects of requirements analysis are often neglected altogether. The IEEE Std 830 model plays a key role in standardizing requirement specifications (SRS) for complex development of conventional software. Knowing that MAS are a natural and logical evolution of the conventional software development paradigms, we believe that the MAS requirement phase can thoroughly benefit from applying such a specific standard model in such a way that results in a high-quality and more accepted SRS artifact. Our purpose in this paper is to utilize and extend the IEEE Std 830-2009 model to specify requirements of multi-agent systems.

Towards Process Standardization for Requirements Analysis of Agent-Based Systems

Advances in Science, Technology and Engineering Systems Journal, May 1, 2018

The development of agent-based systems is negatively impacted by the lack of process standardizat... more The development of agent-based systems is negatively impacted by the lack of process standardization across the major development phases, such as the requirements analysis phase. This issue creates a key barrier for agent technology stockholders regarding comprehending and analyzing complexity associated with these systems specifications. Instead, such fundamental low-level infrastructure is loosely attended to in an ad-hoc fashion, and important aspects of requirements analysis are often neglected altogether. The IEEE Std 830 model is a recommended practice aimed at describing how to write better quality requirement specifications of conventional software. Knowing that agent-based computing is a natural and logical evolution of the conventional approaches to software development, we believe that the requirements phase in agent-based systems can benefit from applying the IEEE Std 830 model which results in high-quality and more accepted artifacts. This article provides a criteriabased evaluation that is derived from the software engineering body of knowledge guide to assessing the adoption degree of agent-oriented methodologies to software requirements standards. Then, it proposes a model-driven approach to restructuring and extending the IEEE Std 830-2009 standard model to specify requirements of agent-based systems. To evaluate the applicability and usefulness of the updated model, we design a research study that allows practicing the model with simple real-world problem scenarios and conducting a summative survey to solicit feedback on the model usages.

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A Metrics Tracking Program for Promoting High-Quality Software Development

2019 SoutheastCon, 2019

There has been substantial focus on software metrics over the last few decades. However, many act... more There has been substantial focus on software metrics over the last few decades. However, many activities within software engineering are often qualitative and are not consonant with automated approaches. Consequently, there are few tools to measure software development quality or to assess teamwork contribution. This paper uses ideas from the Goal-Questions-Metrics (GQM) paradigm to propose a set of metrics to track product and process quality throughout the software development process. The proposed metrics program consists of a set of quality metrics and associated standards that will encourage software development teams to produce high-quality products. We also propose a framework for a tool that implements the metrics tracking program and demonstrate its utility by developing an Eclipse plugin based on the proposed quality metrics.

Evaluation and Comparison of Agent-Oriented Methodologies: A Software Engineering Viewpoint

2019 IEEE International Systems Conference (SysCon), 2019

Numerous agent-oriented methodologies that offer a rich pool of resources to support developers o... more Numerous agent-oriented methodologies that offer a rich pool of resources to support developers of agent-based systems have been proposed. However, the use of existing methodologies in industrial settings is still limited due to the large volume of methodologies, diversity of covered scopes, ambiguity in concepts, and lack of maturity. This makes it difficult for agent technology practitioners to choose the appropriate methodology that best fits their given development context. To eliminate such agent-based development bottleneck, it is important to introduce suitable methods for evaluating, comparing, and classifying agent-oriented methodologies in order to leverage their usage among practitioners. Having systems to evaluate methodologies can effectively help developers better understand existing methodologies, realize their benefits, outline their pros and cons, and assist practitioners with selecting the best-fit methodology for a specific agent-based project. In response, this paper proposes a novel criteria-based evaluation that is influenced by software engineering practices to assess and compare agentoriented methodologies. The proposed evaluation is derived from the software engineering body of knowledge (SWEBOK) and provides a simplified method to assess the coverage degree of an agent-oriented methodology with respect to major software knowledge areas such as the requirements and testing phases. We demonstrate the applicability of the proposed evaluation by applying it to three agent-oriented methodologies (PASSI, MaSE, and Prometheus) in the software engineering requirements and testing phases.

Recommended practices for the specification of multi-agent systems requirements

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON), 2017

The lack of process standardization in the development of multi-agent systems (MAS) causes a grea... more The lack of process standardization in the development of multi-agent systems (MAS) causes a great deal of difficulty for developers in addressing major development phases, such as requirements analysis. Instead, such MAS infrastructure is generally attended to in an ad-hoc fashion and important aspects of requirements analysis are often neglected altogether. The IEEE Std 830 model plays a key role in standardizing requirement specifications (SRS) for complex development of conventional software. Knowing that MAS are a natural and logical evolution of the conventional software development paradigms, we believe that the MAS requirement phase can thoroughly benefit from applying such a specific standard model in such a way that results in a high-quality and more accepted SRS artifact. Our purpose in this paper is to utilize and extend the IEEE Std 830-2009 model to specify requirements of multi-agent systems.

Towards Process Standardization for Requirements Analysis of Agent-Based Systems

Advances in Science, Technology and Engineering Systems Journal, 2018

The development of agent-based systems is negatively impacted by the lack of process standardizat... more The development of agent-based systems is negatively impacted by the lack of process standardization across the major development phases, such as the requirements analysis phase. This issue creates a key barrier for agent technology stockholders regarding comprehending and analyzing complexity associated with these systems specifications. Instead, such fundamental low-level infrastructure is loosely attended to in an ad-hoc fashion, and important aspects of requirements analysis are often neglected altogether. The IEEE Std 830 model is a recommended practice aimed at describing how to write better quality requirement specifications of conventional software. Knowing that agent-based computing is a natural and logical evolution of the conventional approaches to software development, we believe that the requirements phase in agent-based systems can benefit from applying the IEEE Std 830 model which results in high-quality and more accepted artifacts. This article provides a criteriabased evaluation that is derived from the software engineering body of knowledge guide to assessing the adoption degree of agent-oriented methodologies to software requirements standards. Then, it proposes a model-driven approach to restructuring and extending the IEEE Std 830-2009 standard model to specify requirements of agent-based systems. To evaluate the applicability and usefulness of the updated model, we design a research study that allows practicing the model with simple real-world problem scenarios and conducting a summative survey to solicit feedback on the model usages.

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Evaluating the Influence of Twitter Bots via Agent-Based Social Simulation

IEEE Access

Social Media is used by many as a source of information for current world events, followed by pub... more Social Media is used by many as a source of information for current world events, followed by publicly sharing their sentiment about these events. However, when the shared information is not trustworthy and receives a large number of interactions, it alters the public's perception of authentic and false information, particularly when the origin of these stories comes from malicious sources. Over the past decade, there has been an influx of users on the Twitter social network, many of them automated bot accounts with the objective of participating in misinformation campaigns that heavily influence user susceptibility to fake information. This can affect public opinion on real-life matters, as previously seen in the 2020 presidential elections and the current COVID-19 epidemic, both plagued with misinformation. In this paper, we propose an agent-based social simulation environment that utilizes the social network Twitter, with the objective of evaluating how the beliefs of agents representing regular Twitter users can be influenced by malicious users scattered throughout Twitter with the sole purpose of spreading misinformation. We applied two scenarios to compare how these regular agents behave in the Twitter network, with and without malicious agents, to study how much influence malicious agents have on the general susceptibility of the regular users. To achieve this, we implemented a belief value system to measure how impressionable an agent is when encountering misinformation and how its behavior gets affected. The results indicated similar outcomes in the two scenarios as the affected belief value changed for these regular agents, exhibiting belief in the misinformation. Although the change in belief value occurred slowly, it had a profound effect when the malicious agents were present, as many more regular agents started believing in misinformation. INDEX TERMS Agent-based modeling, agent-based social simulation, multi-agent systems, social media, twitter, twitter bot.

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Evaluating the Influence of Twitter Bots via Agent-Based Social Simulation

by Aldo Averza and Khaled Slhoub

Evaluating_the_Influence_of_Twitter_Bots_via_Agent_Based_Social_Simulation, 2022

Social Media is used by many as a source of information for current world events, followed by pub... more Social Media is used by many as a source of information for current world events, followed by publicly sharing their sentiment about these events. However, when the shared information is not trustworthy and receives a large number of interactions, it alters the public's perception of authentic and false information, particularly when the origin of these stories comes from malicious sources. Over the past decade, there has been an influx of users on the Twitter social network, many of them automated bot accounts with the objective of participating in misinformation campaigns that heavily influence user susceptibility to fake information. This can affect public opinion on real-life matters, as previously seen in the 2020 presidential elections and the current COVID-19 epidemic, both plagued with misinformation. In this paper, we propose an agent-based social simulation environment that utilizes the social network Twitter, with the objective of evaluating how the beliefs of agents representing regular Twitter users can be influenced by malicious users scattered throughout Twitter with the sole purpose of spreading misinformation. We applied two scenarios to compare how these regular agents behave in the Twitter network, with and without malicious agents, to study how much influence malicious agents have on the general susceptibility of the regular users. To achieve this, we implemented a belief value system to measure how impressionable an agent is when encountering misinformation and how its behavior gets affected. The results indicated similar outcomes in the two scenarios as the affected belief value changed for these regular agents, exhibiting belief in the misinformation. Although the change in belief value occurred slowly, it had a profound effect when the malicious agents were present, as many more regular agents started believing in misinformation. INDEX TERMS Agent-based modeling, agent-based social simulation, multi-agent systems, social media, twitter, twitter bot.

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Automated Framework to Extract Software Requirements from Source Code

by Khaled Slhoub, Parth Ganeriwala, and Raquel Díaz

The 7th International Conference on Natural Language Processing and Information Retrieval(NLPIR 2023), 2023

Software maintenance and innovation are constant challenges across industries, especially as prog... more Software maintenance and innovation are constant challenges across industries, especially as programming languages evolve with technology. Similarly, poor lexicon quality degrades program comprehension, increasing the effort required by developers to improve existing software products. To address these challenges, we propose a novel automated framework that extracts software requirements directly from source code using a baseline AI language model applied to a Java code base. Leveraging natural language processing techniques, the framework validates programs and generates easily readable requirements by analyzing file contents. The framework enhances agility and flexibility by providing comprehensive documentation for existing software systems. It caters to both experienced and less-experienced developers, offering an intuitive graphical user interface and enabling efficient identification and resolution of errors. The resulting output facilitates natural interaction through language processing. By automating the extraction process, the framework allows developers to better understand software systems, make informed decisions, and adapt to evolving needs.

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