The first decade of DevOps-orientation in software-intensive organizational environments is often characterized with an emerging set of skills that support DevOps practice adoption, targeting a cross-functional collaborative culture; with an aim of achieving a shift in mindset, skillset, and toolset. We investigate DevOps adoption constructs to facilitate development of a formative measurement model to support leadership throughout the DevOps transitional journey. The model and its constructs are designed and validated with a multi-method approach. Initially an exploratory study of a survey is conducted with 250 respondents 76% of whom possess leadership roles, 93% work in Europe and Middle East, and two-thirds are practicing as DevOps practitioners. Pertinent model indicators are produced and grouped under constructs based on survey results and validated using PLS-SEM. The formative structural model is presented and validated in three separate focus group sessions, comprising of respectively seven (7), five (5), and seven (7) participants all of whom had held leadership positions; from countries including USA, UK, The Netherlands, UAE, Greece, Georgia, Switzerland. Seventeen (17) focus group participants provided additional responses through a focus group in-session survey, which allowed feedback on specific model constructs. Results indicate that a set of practices, a set of skills, a set of metrics, DevOps adoption planning and the existence of the DevOps adoption leader roles, should be part of organizational aspirations in the definition of leadership in a DevOps transition path.
{"title":"Synthesis of a Leadership Model for DevOps Adoption","authors":"Krikor Maroukian, S. Gulliver","doi":"10.1145/3501774.3501783","DOIUrl":"https://doi.org/10.1145/3501774.3501783","url":null,"abstract":"The first decade of DevOps-orientation in software-intensive organizational environments is often characterized with an emerging set of skills that support DevOps practice adoption, targeting a cross-functional collaborative culture; with an aim of achieving a shift in mindset, skillset, and toolset. We investigate DevOps adoption constructs to facilitate development of a formative measurement model to support leadership throughout the DevOps transitional journey. The model and its constructs are designed and validated with a multi-method approach. Initially an exploratory study of a survey is conducted with 250 respondents 76% of whom possess leadership roles, 93% work in Europe and Middle East, and two-thirds are practicing as DevOps practitioners. Pertinent model indicators are produced and grouped under constructs based on survey results and validated using PLS-SEM. The formative structural model is presented and validated in three separate focus group sessions, comprising of respectively seven (7), five (5), and seven (7) participants all of whom had held leadership positions; from countries including USA, UK, The Netherlands, UAE, Greece, Georgia, Switzerland. Seventeen (17) focus group participants provided additional responses through a focus group in-session survey, which allowed feedback on specific model constructs. Results indicate that a set of practices, a set of skills, a set of metrics, DevOps adoption planning and the existence of the DevOps adoption leader roles, should be part of organizational aspirations in the definition of leadership in a DevOps transition path.","PeriodicalId":255059,"journal":{"name":"Proceedings of the 2021 European Symposium on Software Engineering","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133338211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yasi Zhang, Sicheng Zhou, Xi Zheng, Yuyu Wang, Minrui Liang
Point spreads betting based on the approximation of score difference is prevalent within the NBA community. In this work, the primary objective is to construct a multidimensional linear model that incorporates both game and player information to forecast the score difference of NBA basketball games. We first considered the SHT Model that contains merely game information, including team intrinsic Strength, Home court advantage, and Tiredness due to successive games. The model is adequately convincing since the estimates are legitimate in terms of their signs and magnitudes. We further examined the influence of the absence of players on forecasting the score difference and applied the respective salary as a weighting factor to add variability into the model. The prediction results indicate that the SHT Model has the highest accuracy in predicting score difference, which will be adopted as our final model. Tests on different seasons demonstrate the final model's stability and practice ability.
{"title":"Modeling and Predicting the Outcomes of NBA Basketball Games","authors":"Yasi Zhang, Sicheng Zhou, Xi Zheng, Yuyu Wang, Minrui Liang","doi":"10.1145/3501774.3501788","DOIUrl":"https://doi.org/10.1145/3501774.3501788","url":null,"abstract":"Point spreads betting based on the approximation of score difference is prevalent within the NBA community. In this work, the primary objective is to construct a multidimensional linear model that incorporates both game and player information to forecast the score difference of NBA basketball games. We first considered the SHT Model that contains merely game information, including team intrinsic Strength, Home court advantage, and Tiredness due to successive games. The model is adequately convincing since the estimates are legitimate in terms of their signs and magnitudes. We further examined the influence of the absence of players on forecasting the score difference and applied the respective salary as a weighting factor to add variability into the model. The prediction results indicate that the SHT Model has the highest accuracy in predicting score difference, which will be adopted as our final model. Tests on different seasons demonstrate the final model's stability and practice ability.","PeriodicalId":255059,"journal":{"name":"Proceedings of the 2021 European Symposium on Software Engineering","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126476088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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