Automatically prioritizing and assigning tasks from code repositories in puzzle driven development

Bugayenko, Yegor; Bakare, Ayomide; Cheverda, Arina; Farina, Mirko; Kruglov, Artem; Plaksin, Yaroslav; Succi, Giancarlo; Pedrycz, Witold

doi:10.1145/3524842.3528512

Proceedings of the 19th International Conference on Mining Software Repositories 2022

DOI: 10.1145/3524842.3528512

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Automatically prioritizing and assigning tasks from code repositories in puzzle driven development

Yegor Bugayenko¹,

Ayomide Bakare

Arina Cheverda

et al.

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Cited by 7 publications

(1 citation statement)

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“…This paper focuses on this problem and thus attempts to find a way to automatically assign to developers tasks that are then automatically extracted from a code. This idea was pioneered by Bugayenko [6] and is called "Puzzle Driven Development," or PDD.…”

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confidence: 99%

Automatically Prioritizing Tasks in Software Development

Bugayenko¹,

Farina

Kruglov

et al. 2023

IEEE Access

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Context: Within the domain of managing software development teams, effective task prioritization is a critical responsibility that should not be underestimated, particularly for larger organizations with significant backlogs. Current approaches primarily rely on predicting task priority without considering information about other tasks, potentially resulting in inaccurate priority predictions.Objective: This paper presents the benefits of considering the entire backlog when prioritizing tasks.Method: We employ an iterative approach using particle swarm optimization to optimize a linear model with various preprocessing methods to determine the optimal model for task prioritization within a backlog. Results:The findings of our study demonstrate the usefulness of constructing a task prioritization model based on complete information from the backlog. Conclusion:The method proposed in our study can serve as a valuable resource for future researchers and can also facilitate the development of new tools to aid IT management teams.

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confidence: 99%

Automatically Prioritizing Tasks in Software Development

Bugayenko¹,

Farina

Kruglov

et al. 2023

IEEE Access

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AI and society: a virtue ethics approach

et al. 2022

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Infosphere, Datafication, and Decision-Making Processes in the AI Era

Lavazza

Farina

2023

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A recent interpretation of artificial intelligence (AI) (Floridi 2013 , 2022 ) suggests that the implementation of AI demands the investigation of the binding conditions that make it possible to build and integrate artifacts into our lived world. Such artifacts can successfully interact with the world because our environment has been designed to be compatible with intelligent machines (such as robots). As the use of AI becomes ubiquitous in society, possibly leading to the formation of increasingly intelligent bio-technological unions, there will likely be a coexistence of a plethora of micro-environments wrapped and tailored around humans and basic robots. The key element of this pervasive process will be the capacity to integrate biological realms in an infosphere suitable for the implementation of AI technologies. This process will require extensive datafication. This is because data is the basis of the logical-mathematical codes and models that drive and guide AI. This process will have huge consequences on workplaces, on workers, as well as on the decision-making processes required for the functioning of future societies. In this paper we will offer a comprehensive reflection on the moral and social implications of datafication as well as a set of considerations about its desirability, which will be informed by the following insights: (1) full protection of privacy may become structurally impossible, thus leading to undesirable forms of political and social control; (2) worker’s freedom may be reduced; (3) human creativity, imagination, and even divergence from AI logic might be channeled and possibly discouraged; (4) there will likely be a push towards efficiency and instrumental reason, which will become preeminent in production lines as well as in society.

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Automatically prioritizing and assigning tasks from code repositories in puzzle driven development

Cited by 7 publications

References 1 publication

Automatically Prioritizing Tasks in Software Development

Automatically Prioritizing Tasks in Software Development

AI and society: a virtue ethics approach

Infosphere, Datafication, and Decision-Making Processes in the AI Era

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