An artificial intelligence framework on software bug triaging, technological evolution, and future challenges: A review

Nagwani, Naresh Kumar; Suri, Jasjit S.

doi:10.1016/j.jjimei.2022.100153

Cited by 17 publications

(10 citation statements)

References 102 publications

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“…Methods such as factor analysis, correlation analysis, factor analysis, mathematical analysis, and mathematical programming were used in the research. The technology of using these methods is widely covered in sources [11][12][13][14][15].…”

Section: Methodsmentioning

confidence: 99%

Algorithms for improving the process of modeling complex systems based on big data: On the example of regional agricultural production

Juraev,

Mallaev,

Aralov

et al. 2023

E3S Web Conf.

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The article analyzes the sources of the development of specific mechanisms, assessing the future problems of regional agro-industry development. Agro-industry as a production facility forms a complex system. In this case, as the main elements, it is suggested that the criterion of non-loss of characteristics as a result of processing information about these elements is primary. It is justified that the information system of the Big Data type, the models that describe the laws, the mechanism that enables the improvement of the models, and the algorithms that activate the mechanism are of particular importance as these sources. Researchers estimate that the mechanism that allows for the improvement of system research models is artificial intelligence, and the main problem here is the obstacles in the development of algorithms that determine the trajectory of its activity. These obstacles are explained by the complexity of the system, the lack of sufficient information to assess the importance levels of its elements, low accuracy, and the fact that the level of importance is presented differently in different sources. Taking into account that agro-industry is a complex enough system, the need to research the laws of this network requires a big data type information system, and algorithms for using artificial intelligence-based mechanisms are proposed.

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Section: Methodsmentioning

confidence: 99%

Algorithms for improving the process of modeling complex systems based on big data: On the example of regional agricultural production

Juraev,

Mallaev,

Aralov

et al. 2023

E3S Web Conf.

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“…Bugs that decrease the resilience of AI models might cause unanticipated failures, especially in vital fields like autonomous cars and medical diagnostics. For instance, an error in a self-driving car's decision-making algorithm might cause it to fail to respond successfully to unexpected environmental changes, leading to an accident (Nagwani & Suri, 2023). AI models are frequently built with explicit boundaries to restrict their behaviour and prevent abuse.…”

Section: The Answer Of Ai Profession Relevancymentioning

confidence: 99%

Quo vadis Indonesian public relations profession: dilemma on the rise of AI

Silviani

2024

Indonesian Journal of Communications Studies

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The debate over AI has focused on its contrast with human employment. Simple perspectives are inadequate in public communication fields like Public Relations (PR). The conversation must shift from discussing AI's impact on human jobs to how AI will shape public communication as AI becomes more important in PR. To examine AI's effects on Public Relations, this study uses a literature review focusing on authority and public voice. Due to the risks of AI misuse, data discrimination, and data poisoning, public relations must carefully consider the implications of AI integration. Artificial Intelligence (AI) in Public Relations is studied using a literature review as its main method. Experts are consulted to identify AI's most significant challenges and opportunities in public relations. Public relations (PR) are affected by Artificial Intelligence (AI), which presents both opportunities and challenges. AI can boost public communication, but it also risks data misuse and discrimination. Ethical issues arise when AI represents the public's voice. This study provides useful insights into how Indonesia's Public Relations profession should approach Artificial Intelligence. PR professionals can overcome technical and ethical challenges and revolutionise public communication with AI integration. Therefore, ethical PR practice and the use of AI are becoming increasingly important.

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“…In addition to the traditional method of manually assigning bugs to appropriate developers, the literature provides an exhaustive array of approaches for semi- or fully automating the bug assignment process. These techniques are based on machine learning, social network analysis, tossing based on the graph, fuzzy logic, games in software development, operational research, and information retrieval, etc ., to perform automatic text summarization, duplicate detection, bug triaging, component prediction, severity/priority prediction, etc ., ( Sajedi-Badashian & Stroulia, 2020 ; Nagwani & Suri, 2023 ). These approaches try to minimize the effort, bug tossing length, and time required for bug resolution.…”

Section: Introductionmentioning

confidence: 99%

Enhancing bug allocation in software development: a multi-criteria approach using fuzzy logic and evolutionary algorithms

Gupta,

Gupta

2024

PeerJ Computer Science

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A bug tracking system (BTS) is a comprehensive data source for data-driven decision-making. Its various bug attributes can identify a BTS with ease. It results in unlabeled, fuzzy, and noisy bug reporting because some of these parameters, including severity and priority, are subjective and are instead chosen by the user’s or developer’s intuition rather than by adhering to a formal framework. This article proposes a hybrid, multi-criteria fuzzy-based, and multi-objective evolutionary algorithm to automate the bug management approach. The proposed approach, in a novel way, addresses the trade-offs of supporting multi-criteria decision-making to (a) gather decisive and explicit knowledge about bug reports, the developer’s current workload and bug priority, (b) build metrics for computing the developer’s capability score using expertise, performance, and availability (c) build metrics for relative bug importance score. Results of the experiment on five open-source projects (Mozilla, Eclipse, Net Beans, Jira, and Free desktop) demonstrate that with the proposed approach, roughly 20% of improvement can be achieved over existing approaches with the harmonic mean of precision, recall, f-measure, and accuracy of 92.05%, 89.04%, 90.05%, and 91.25%, respectively. The maximization of the throughput of the bug can be achieved effectively with the lowest cost when the number of developers or the number of bugs changes. The proposed solution addresses the following three goals: (i) improve triage accuracy for bug reports, (ii) differentiate between active and inactive developers, and (iii) identify the availability of developers according to their current workload.

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An artificial intelligence framework on software bug triaging, technological evolution, and future challenges: A review

Cited by 17 publications

References 102 publications

Algorithms for improving the process of modeling complex systems based on big data: On the example of regional agricultural production

Algorithms for improving the process of modeling complex systems based on big data: On the example of regional agricultural production

Quo vadis Indonesian public relations profession: dilemma on the rise of AI

Enhancing bug allocation in software development: a multi-criteria approach using fuzzy logic and evolutionary algorithms

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