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(1) Background: A blockchain-based framework for distributed agile Open-Source Software for Archaeological Photogrammetry (OSSAP) testing life cycle is an innovative approach that uses blockchain technology to optimize the Open-Source Software for Archaeological Photogrammetry process. Previously, various methods have been employed to address communication and collaboration challenges in Open-Source Software for Archaeological Photogrammetry, but they were inadequate in aspects such as trust, traceability, and security. Additionally, a significant cause of project failure was the non-completion of unit testing by developers, leading to delayed testing. (2) Methods: This article discusses the integration of blockchain technology in Open-Source Software for Archaeological Photogrammetry and resolves critical concerns related to transparency, trust, coordination, testing and communication. A novel approach is proposed based on a blockchain framework named Open-Source Software for Archaeological Photogrammetry Testing-Plus. (3) Results: The Open-Source Software for Archaeological Photogrammetry Testing-Plus framework utilizes blockchain technology to provide a secure and transparent platform for acceptance testing and payment verification. Moreover, by leveraging smart contracts on a private Ethereum blockchain, Open-Source Software for Archaeological Photogrammetry Testing-Plus ensures that both the testing team and the development team are working towards a common goal and are compensated fairly for their contributions. (4) Conclusions: The experimental results conclusively show that this innovative approach substantially improves transparency, trust, coordination, testing and communication and provides security for both the testing team and the development team engaged in the distributed agile Open-Source Software for Archaeological Photogrammetry (Open-Source Software for Archaeological Photogrammetry) testing life cycle.
Details
; Farooq Muhammad Shoaib 1
; Qureshi, Junaid Nasir 2
; Manzoor Muhammad Faraz 1
; Shaheen Momina 3
1 School of System and Technology, Department of Artificial Intelligence, University of Management and Technology, Lahore 54000, Pakistan; [email protected] (O.A.); [email protected] (M.S.F.); [email protected] (M.F.M.)
2 Department of Computer Science, Bahria University, BULC, Lahore 54600, Pakistan; [email protected]
3 School of Arts, Humanities and Social Sciences, University of Roehampton, London SW15 5PU, UK