WORKLOAD BALANCING IN THE TEST CASE SCHEDULING: A METHEMATICAL APPROACH

Efficient scheduling of test cases is a critical task in environments where execution resources, such as testers or test environments, are limited and subject to individual availability constraints. In this paper, we propose a flexible and extensible mathematical model for optimizing test scheduling...

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Bibliographic Details
Published inComputer Systems and Information Technologies no. 2; pp. 81 - 86
Main Authors PIKH, Iryna, BILYK, Oleksii
Format Journal Article
LanguageEnglish
Published 26.06.2025
Online AccessGet full text
ISSN2710-0766
2710-0774
2710-0774
DOI10.31891/csit-2025-2-9

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Summary:Efficient scheduling of test cases is a critical task in environments where execution resources, such as testers or test environments, are limited and subject to individual availability constraints. In this paper, we propose a flexible and extensible mathematical model for optimizing test scheduling based on discrete time blocks. Each test case has a fixed duration and must be assigned to exactly one compatible tester. Testers, in turn, may be unavailable at specific time blocks due to pre-scheduled meetings or fixed breaks, such as lunch. The scheduling objective is to minimize the makespan, defined as the latest finish time among all scheduled tests. The model is formulated as a mixed-integer linear programming (MILP) problem that integrates testers' compatibility and availability constraints with task assignments into a unified framework. In contrast to models that assume testers are always available or disregard personal schedules, our method incorporates individual availability constraints for more realistic planning. The model is assessed on a synthetic scenario involving multiple testers with defined break times and varying task compatibility, and the resulting schedule is visualized with Gantt charts. The proposed formulation serves as a foundation for more advanced scheduling systems in quality assurance and resource-constrained testing workflows.
ISSN:2710-0766
2710-0774
2710-0774
DOI:10.31891/csit-2025-2-9