Machine Learning Application in LAPIS Agile Software Development Process

Mehmet Tugrul Tekbulut, Nurdan Canbaz, Tugba Öztürk Kaya
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Abstract

It is necessary to carry out improvement works at every stage of the software processes to adapt to changes in the world of software. For this reason, primarily, the processes should be specific, automatable and measurable; the opinions of the teams on improvement should be supported both for these processes and their own works.In this study, the contribution of the teams to the improvement works in the retrospective meeting, which is part of the improvement-oriented agile product development process, LAPIS (Logo Agile Process Improvement System) developed by LOGO, by being inspired by the lean manufacturing concept, has been supported by machine learning. The aim has been to expand the opportunities for the works of teams to improve and to be based on data. The effects of the study results on the software process measurement results have been examined, and the effects of the improvements on the company noticed by the teams have been evaluated.
机器学习在LAPIS敏捷软件开发过程中的应用
在软件过程的每个阶段进行改进工作以适应软件世界的变化是必要的。出于这个原因,主要是流程应该是具体的、可自动化的和可测量的;对于这些过程和他们自己的工作,应该支持团队关于改进的意见。在本研究中,团队在回顾会议中对改进工作的贡献是面向改进的敏捷产品开发过程的一部分,Logo在精益制造概念的启发下开发的LAPIS (Logo敏捷过程改进系统)得到了机器学习的支持。其目的是扩大团队工作改进和以数据为基础的机会。研究结果对软件过程度量结果的影响已经被检查过,并且团队注意到的对公司的改进的影响已经被评估过。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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