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JOURNALS // Program Systems: Theory and Applications // Archive

Program Systems: Theory and Applications, 2022 Volume 13, Issue 3, Pages 307–324 (Mi ps405)

Artificial Intelligence, Intelligent Systems, Neural Networks

Assessment of time reduction when using a modified task-tracking methodology in IT project management

R. A. Sharaeva, V. V. Kugurakova

Kazan Federal University, Kazan, Russia

Abstract: Task-trackers that allow automating management tasks are traditionally used for IT project development management. Popular tools were analyzed, and new requirements were formulated for task and project management systems in general for any highly specialized areas of IT development. The author’s methodology for task-tracking systems, not found in any of the considered solutions, was developed. Practical implementation of the proposed approach showed that it is possible to solve management problems much more efficiently: optimization reaches more than 50% in some cases. In addition, the developed tool ProjectAR allows leveling several risks.
Comparison with the popular task tracker Asana, which is the closest to ProjectAR by its functionality, was conducted to prove the hypothesis of time reduction for management tasks. In addition to the time metric, the risk of incorrect integration of generated development artifacts was selected as a criterion for tool comparison. The tools were compared based on the number of templates needed to implement IT solutions and the number of typical projects.
At the end, a vision for tool development is given.

Key words and phrases: software engineering, IT development, task tracker, automation.

UDC: 004.451.(44/54)

MSC: Primary 94A29; Secondary 62P30

Received: 23.08.2022
Accepted: 21.09.2022

DOI: 10.25209/2079-3316-2022-13-3-307-324



© Steklov Math. Inst. of RAS, 2024