| 1. |
- Dakkak, Anas, et al.
(author)
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Continuous deployment in software-intensive system-of-systems
- 2023
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In: Information and Software Technology. - : Elsevier BV. - 0950-5849 .- 1873-6025. ; 159
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Journal article (peer-reviewed)abstract
- Context: While continuous deployment is popular among web-based software development organizations, adopting continuous deployment in software-intensive system-of-systems is more challenging. On top of the challenges arising from deploying software to a single software-intensive embedded system, software-intensive system-of-systems (SiSoS) add a layer of complexity as new software undergoes an extensive field validation applied to individual components of the SiSoS, as well as the overall SiSoS, to ensure that both legacy and new functionalities are working as desired. Objectives: This paper aims to study how SiSoS transitions to continuous deployment by exploring how continuous deployment impacts field testing and validation activities, how continuous deployment can be practiced in SiSoS, and to identify the success factors that companies need to consider when transitioning to continuous deployment. Method: We conducted a case study at Ericsson AB focusing on the embedded software of the Third Generation Radio Access Network (3G RAN). The 3G RAN consists of two large-scale software-intensive embedded systems, representing a simple SiSoS composed of two systems. 3G RAN software was the first to transition to continuous deployment and is used as a reference case for other products within Ericsson AB. Results: Software deployment, in addition to field testing and validation, have transitioned from being a discrete activity performed at the end of software development to a continuous process performed in parallel to software development. Further, our study reveals an orchestrating approach for software deployment, which allows pre/post validation of legacy behavior and new features in a shorter release and deployment cadence. Furthermore, we identified the essential success factors that organizations should consider when transitioning to continuous deployment. Conclusion: Transition to continuous deployment, in addition to field testing and validation, shall be considered and planned carefully. In this paper, we provide a set of success factors and orchestration technique that helps organization when transitioning to continuous deployment in the software-intensive embedded system-of-systems context.
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| 2. |
- Dakkak, Anas, et al.
(author)
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Controlled Continuous Deployment: A Case Study From The Telecommunications Domain
- 2022
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In: ACM International Conference Proceeding Series. - New York, NY, USA : ACM. ; , s. 24-33, s. 24-33
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Conference paper (peer-reviewed)abstract
- Continuous deployment has become a widely used practice in web-based software applications. Deploying a new software version to production is a seamless automated process executed thousands of times per day. Continuous deployment reduces the time between a code commit and that commit is active in production. While continuous deployment promises many advantages to software development organizations, the adoption of continuous deployment in the software-intensive embedded systems industry is limited. Several empirical studies have highlighted the challenges associated with software-intensive embedded systems. However, very few studies, if any at all, have attempted to provide a practical approach to realize continuous deployment to these systems. This paper proposes a Controlled Continuous Deployment (CCD) approach, which considers the constraints software-intensive embedded systems have, such as high reliability and availability requirements, limited possibility for rollback after deployment, and the high volume of in-service systems in the market. We derived the approach by conducting a case study at Ericsson AB, focusing on three Radio Access Networks (RAN) technologies embedded software used in 3G, 4G, and 5G mobile networks.
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| 3. |
- Dakkak, Anas, et al.
(author)
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Customer Support In The Era of Continuous Deployment: A Software-Intensive Embedded Systems Case Study
- 2022
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In: Proceedings - 2022 IEEE 46th Annual Computers, Software, and Applications Conference, COMPSAC 2022. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 914-923
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Conference paper (peer-reviewed)abstract
- Supporting customers after they acquire the prod-uct is essential for companies producing and selling software-intensive embedded systems products. Generally, customer sup-port is the first interaction point between the product users and the product vendor. Customer support is often engaged with answering customers' questions, troubleshooting, fault identification, and fixing product faults. While continuous deployment advocates for closer cooperation between the ones operating the software and the ones developing it, the means of such collaboration in general and the role of customer support, in particular, has not been addressed in the context of software-intensive embedded systems. Therefore, to better understand the impact that continuous deployment has on customer support and the role customer support should play in this context, we conducted a case study at a multinational company developing and selling telecommunications networks infrastructure. We focused on the 4th and 5th Generation (4G and 5G) Radio Access Networks (RAN) products, which can be considered a high volume product as they cover more than 80% of the world's population. Our study reveals that customer support needs to transition from a transaction-based and passive function triggered by customer support requests, to take an active role characterized by being proactive and preemptive to cope with the shorter operational time of a software version introduced by continuous deployment. In addition, customer support plays an essential role in making the feedback actionable by aggregating and consolidating feedback data to the R&D organization.
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| 4. |
- Dakkak, Anas, et al.
(author)
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DevServOps: DevOps For Product-Oriented Product Service Systems
- 2023
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In: Proceedings - 2023 49th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 328-331
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Conference paper (peer-reviewed)abstract
- Companies producing software-intensive products do not only offer products to customers but Product Service Systems (PSS), a combination of the products and services that address customers' needs. Further, product-related services are key in ensuring customer satisfaction as the service organization represents the company's interface toward its customers, who operate and use the products. Therefore, while DevOps has been widely adopted in companies developing web-based applications aiming to streamline the Development and Operations activities, the projecting of DevOps as applied in web-based applications to PSS is difficult without considering the role of services. Therefore, based on a two years participant observation case study conducted at a multinational telecommunications systems provider, we propose a new and novel approach called Development-Services-Operations (DevServOps) which incorporates services as a key player facilitating an end-to-end software flow toward customers in one direction and feedback toward developers in the other direction.
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| 5. |
- Dakkak, Anas, et al.
(author)
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Perceived benefits of continuous deployment in software-intensive embedded systems
- 2021
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In: Proceedings - 2021 IEEE 45th Annual Computers, Software, and Applications Conference, COMPSAC 2021. ; , s. 934-941
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Conference paper (peer-reviewed)abstract
- Continuous Deployment (CD) advocates for quick and frequent deployments of software to production. The goal is to bring new functionality as early as possible to users while learning from their usage. CD has emerged from web-based applications where it has been gaining traction over the past years. While CD is appealing for many software development organizations, empirical evidence on perceived benefits in software-intensive embedded systems is scarce. The objective of this paper is to identify perceived benefits after transitioning to continuous deployment from a long-cycle release and deployment process. To do that, a case study at a multinational telecommunication company was conducted focusing on large and complex embedded software; the Third Generation (3G) Radio Access Network (RAN) software.
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| 6. |
- Dakkak, Anas, et al.
(author)
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Success Factors when Transitioning to Continuous Deployment in Software-Intensive Embedded Systems
- 2021
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In: Proceedings - 2021 47th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2021. ; , s. 129-137
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Conference paper (peer-reviewed)abstract
- Continuous Deployment is the practice to deploy software more frequently to customers and learn from their usage. The aim is to introduce new functionality and features in an additive way to customers as soon as possible. While Continuous Deployment is becoming popular among web and cloud-based software development organizations, the adoption of continuous deployment within the software-intensive embedded systems industry is still limited.In this paper, we conducted a case study at a multinational telecommunications company focusing on the Third Generation Radio Access Network (3G RAN) embedded software. The organization has transitioned to Continuous Deployment where the software's deployment cycle has been reduced to 4 weeks from 24 weeks. The objective of this paper is to identify what does success means when transitioning to continuous deployment and the success factors that companies need to attend to when transitioning to continuous deployment in a large-scale embedded software.
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| 7. |
- Dakkak, Anas, et al.
(author)
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The Role Of Post-Release Software Traceability in Release Engineering: A Software-Intensive Embedded Systems Case Study From The Telecommunications Domain
- 2022
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In: Proceedings - 48th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2022. ; , s. 169-176
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Conference paper (peer-reviewed)abstract
- Modern release engineering practices such as continuous integration and delivery have allowed software development companies to transition from a long release cycle to a shorter one. The shorter release cycle has led to more software releases available to customers. At the same time, companies developing high-volume software-intensive embedded systems often deliver patch releases and maintenance releases on top of major and minor releases to customers who pick and choose what releases apply to them and decide when to upgrade the system, if to upgrade at all. While release engineering has been studied before in web-based, desktop-based, and embedded software, the focus has been on pre-release activities. Few studies have investigated what happens after the release, particularly the role of tracing software from release to deployment in high-volume software-intensive embedded systems. To address this gap, we conducted a qualitative case study at a multi-national telecommunications systems provider focusing on Radio Access Network (RAN) software. RAN software is a complex and large-scale embedded software used in mobile networks Base Stations (BS), providing software functionality for RAN mobile technologies ranging from 2G to 5G. Our study shed light on post-release software traceability and how it is used in the release engineering process.
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| 8. |
- Dakkak, Anas, et al.
(author)
-
The Role Of Post-Release Software Traceability in Release Engineering: A Software-Intensive Embedded Systems Case Study From The Telecommunications Domain
- 2022
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In: 2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781665461528 - 9781665461535
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Conference paper (peer-reviewed)abstract
- Modern release engineering practices such as continuous integration and delivery have allowed software development companies to transition from a long release cycle to a shorter one. The shorter release cycle has led to more software releases available to customers. At the same time, companies developing high-volume software-intensive embedded systems often deliver patch releases and maintenance releases on top of major and minor releases to customers who pick and choose what releases apply to them and decide when to upgrade the system, if to upgrade at all. While release engineering has been studied before in web-based, desktop-based, and embedded software, the focus has been on pre-release activities. Few studies have investigated what happens after the release, particularly the role of tracing software from release to deployment in high-volume software-intensive embedded systems. To address this gap, we conducted a qualitative case study at a multi-national telecommunications systems provider focusing on Radio Access Network (RAN) software. RAN software is a complex and large-scale embedded software used in mobile networks Base Stations (BS), providing software functionality for RAN mobile technologies ranging from 2G to 5G. Our study shed light on post-release software traceability and how it is used in the release engineering process.
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| 9. |
- Dakkak, Anas, et al.
(author)
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Towards AIOps enabled services in continuously evolving software-intensive embedded systems
- 2024
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In: Journal of Software: Evolution and Process. - : John Wiley & Sons. - 2047-7481 .- 2047-7473. ; 36:5
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Journal article (peer-reviewed)abstract
- Continuous deployment has been practiced for many years by companies developing web- and cloud-based applications. To succeed with continuous deployment, these companies have a strong collaboration culture between the operations and development teams. In addition, these companies use AI, analytics, and big data to assist with time-consuming postdeployment activities such as continuous monitoring and fault identification. Thus, the term AIOps has evolved to highlight the importance and difficulty of maintaining highly available applications in a complex and dynamic environment. In contrast, software-intensive embedded systems often provide customer product-related services, such as maintenance, optimization, and support. These services are critical for these companies as they provide significant revenue and increase customer satisfaction. Therefore, the objective of our study is to gain an in-depth understanding of the impact of continuous deployment on product-related services provided by software-intensive embedded systems companies. In addition, we aim to understand how AIOps can support continuous deployment in the context of software-intensive embedded systems. To address this objective, we conducted a case study at a large and multinational telecommunications systems provider focusing on the radio access network (RAN) systems for 4G and 5G networks. The company provides RAN products and three complementing services: rollout, optimization, and customer support. The results from the case study show that the boundaries between product-related services become blurry with continuous deployment. In addition, product-related services, which were conducted in sequence by independent projects, converge with continuous deployment and become part of the same project. Further, AIOps platforms play an important role in reducing costs and increasing postdeployment activities' efficiency and speed. These results show that continuous deployment has a profound impact on the software-intensive system's provider service organization. The service organization becomes the connection between the R&D organization and the customer. In order to cope with the increased speed of releases, deployment and postdeployment activities need to be largely automated. AIOps platforms are seen as a critical enabler in managing the increasing complexity without increasing human involvement.
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| 10. |
- Dakkak, Anas, et al.
(author)
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Towards Continuous Data Collection from In-service Products : Exploring the Relation Between Data Dimensions and Collection Challenges
- 2021
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In: 2021 28th Asia-Pacific Software Engineering Conference (APSEC). - : IEEE. - 9781665437844 - 9781665437851
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Conference paper (peer-reviewed)abstract
- Data collected from in-service products play an important role in enabling software-intensive embedded systems suppliers to embrace data-driven practices. Data can be used in many different ways such as to continuously learn and improve the product, enhance post-deployment services, reduce operational cost or create a better user experience. While there is no shortage of possible use cases leveraging data from in-service products, software-intensive embedded systems companies struggle to continuously collect data from their in-service products. Often, data collection is done in an ad-hoc way and targeting specific use cases or needs. Besides, few studies have investigated data collection challenges in relation to the data dimensions, which are the minimum set of quantifiable data aspects that can define software-intensive embedded product data from a collection point of view. To help address data collection challenges, and to provide companies with guidance on how to improve this process, we conducted a case study at a large multinational telecommunications supplier focusing on data characteristics and collection challenges from the Radio Access Networks (RAN) products. We further investigated the relations of these challenges to the data dimensions to increase our understanding of how data dominions contribute to the challenges.
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| 11. |
- Dakkak, Anas, et al.
(author)
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Towards Continuous Data Collection from In-service Products: Exploring the Relation between Data Dimensions and Collection Challenges
- 2021
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In: Proceedings - Asia-Pacific Software Engineering Conference, APSEC. - 1530-1362. ; 2021-December, s. 243-252
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Conference paper (peer-reviewed)abstract
- Data collected from in-service products play an important role in enabling software-intensive embedded systems suppliers to embrace data-driven practices. Data can be used in many different ways such as to continuously learn and improve the product, enhance post-deployment services, reduce operational cost or create a better user experience. While there is no shortage of possible use cases leveraging data from in-service products, software-intensive embedded systems companies struggle to continuously collect data from their in-service products. Often, data collection is done in an ad-hoc way and targeting specific use cases or needs. Besides, few studies have investigated data collection challenges in relation to the data dimensions, which are the minimum set of quantifiable data aspects that can define software-intensive embedded product data from a collection point of view. To help address data collection challenges, and to provide companies with guidance on how to improve this process, we conducted a case study at a large multinational telecommunications supplier focusing on data characteristics and collection challenges from the Radio Access Networks (RAN) products. We further investigated the relations of these challenges to the data dimensions to increase our understanding of how data dominions contribute to the challenges.
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| 12. |
- Issa Mattos, David, 1990, et al.
(author)
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Automated optimization of software parameters in a long term evolution radio base station
- 2019
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In: SysCon 2019 - 13th Annual IEEE International Systems Conference, Proceedings. - : Institute of Electrical and Electronics Engineers (IEEE).
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Conference paper (peer-reviewed)abstract
- Radio network optimization is concerned with the configuration of radio base station parameters in order to achieve the desired level of service quality in addition to many other differentiating technical factors. Mobile network operators have different physical locations, levels of traffic profiles, number of connected devices, and the desired quality of service. All of these conditions make the problem of optimizing the parameters of a radio base station specific to the operator's business goals. The high number of calibration parameters and the complex interaction between them make the system behave as a black-box model for any practical purpose. The computation of relevant operator metrics is often stochastic, and it can take several minutes to compute the effect of changing a single, making it impractical to optimize systems with approaches that require a large number of iterations. Operators want to optimize their already deployed system in online scenarios while minimizing the exposure of the system to a negative set of parameters during the optimization procedure. {This paper presents a novel approach to the optimization of a Long Term Evolution (LTE) radio base station in a large search space with an expensive stochastic objective and a limited regret bounds scenario. We show the feasibility of this approach by implementing it in an industrial testing bed radio base station connected to real User Equipment (UE) in collaboration with Ericsson. Two optimization processes in this experimental setup are executed to show the feasibility of the approach in real-world scenarios.
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| 13. |
- Issa Mattos, David, 1990, et al.
(author)
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Experimentation for Business-to-Business Mission-Critical Systems: A Case Study
- 2020
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In: Proceedings - 2020 IEEE/ACM International Conference on Software and System Processes, ICSSP 2020. - New York, NY, USA : ACM. - 9781450375122 ; 26 June 2020, s. 95-104
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Conference paper (peer-reviewed)abstract
- Continuous experimentation (CE) refers to a group of practices used by software companies to rapidly assess the usage, value and performance of deployed software using data collected from customers and the deployed system. Despite its increasing popularity in the development of web-facing applications, CE has not been discussed in the development process of business-to-business (B2B) mission-critical systems. We investigated in a case study the use of CE practices within several products, teams and areas inside Ericsson. By observing the CE practices of different teams, we were able to identify the key activities in four main areas and inductively derive an experimentation process, the HURRIER process, that addresses the deployment of experiments with customers in the B2B and with mission-critical systems. We illustrate this process with a case study in the development of a large mission-critical functionality in the Long Term Evolution (4G) product. In this case study, the HURRIER process is not only used to validate the value delivered by the solution but to increase the quality and the confidence from both the customers and the R&D organization in the deployed solution. Additionally, we discuss the challenges, opportunities and lessons learned from applying CE and the HURRIER process in B2B mission-critical systems.
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| 14. |
- Issa Mattos, David, 1990, et al.
(author)
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Experimentation for business-to-business mission-critical systems: A case study
- 2022
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In: Accelerating Digital Transformation: 10 Years of Software Center. - 9783031108730 ; , s. 351-371
-
Book chapter (other academic/artistic)abstract
- Continuous experimentation (CE) refers to a group of practices used by software companies to rapidly assess the usage, value and performance of deployed software using data collected from customers and the deployed system. Despite its increasing popularity in the development of web-facing applications, CE has not been discussed in the development process of business-to-business (B2B) mission-critical systems. We investigated in a case study the use of CE practices within several products, teams and areas inside Ericsson. By observing the CE practices of different teams, we were able to identify the key activities in four main areas and inductively derive an experimentation process, the HURRIER process, that addresses the deployment of experiments with customers in the B2B and with mission-critical systems. We illustrate this process with a case study in the development of a large mission-critical functionality in the Long Term Evolution (4G) product. In this case study, the HURRIER process is not only used to validate the value delivered by the solution but to increase the quality and the confidence from both the customers and the R&D organization in the deployed solution. Additionally, we discuss the challenges, opportunities and lessons learned from applying CE and the HURRIER process in B2B mission-critical systems.
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| 15. |
- Issa Mattos, David, 1990, et al.
(author)
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The HURRIER process for experimentation in business-to-business mission-critical systems
- 2023
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In: Journal of Software: Evolution and Process. - : Wiley. - 2047-7481 .- 2047-7473. ; 35:5
-
Journal article (peer-reviewed)abstract
- Continuous experimentation (CE) refers to a set of practices used by software companies to rapidly assess the usage, value, and performance of deployed software using data collected from customers and systems in the field using an experimental methodology. However, despite its increasing popularity in developing web-facing applications, CE has not been studied in the development process of business-to-business (B2B) mission-critical systems. By observing the CE practices of different teams, with a case study methodology inside Ericsson, we were able to identify the different practices and techniques used in B2B mission-critical systems and a description and classification of the four possible types of experiments. We present and analyze each of the four types of experiments with examples in the context of the mission-critical long-term evolution (4G) product. These examples show the general experimentation process followed by the teams and the use of the different CE practices and techniques. Based on these examples and the empirical data, we derived the HURRIER process to deliver high-quality solutions that the customers value. Finally, we discuss the challenges, opportunities, and lessons learned from applying CE and the HURRIER process in B2B mission-critical systems.
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| 16. |
- Munappy, Aiswarya Raj, 1990, et al.
(author)
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From Ad-Hoc Data Analytics to DataOps
- 2020
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In: Proceedings - 2020 IEEE/ACM International Conference on Software and System Processes, ICSSP 2020. - New York, NY, USA : ACM. ; , s. 165-174
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Conference paper (peer-reviewed)abstract
- The collection of high-quality data provides a key competitive advantage to companies in their decision-making process. It helps to understand customer behavior and enables the usage and deployment of new technologies based on machine learning. However, the process from collecting the data, to clean and process it to be used by data scientists and applications is often manual, non-optimized and error-prone. This increases the time that the data takes to deliver value for the business. To reduce this time companies are looking into automation and validation of the data processes. Data processes are the operational side of data analytic workflow.DataOps, a recently coined term by data scientists, data analysts and data engineers refer to a general process aimed to shorten the end-to-end data analytic life-cycle time by introducing automation in the data collection, validation, and verification process. Despite its increasing popularity among practitioners, research on this topic has been limited and does not provide a clear definition for the term or how a data analytic process evolves from ad-hoc data collection to fully automated data analytics as envisioned by DataOps.This research provides three main contributions. First, utilizing multi-vocal literature we provide a definition and a scope for the general process referred to as DataOps. Second, based on a case study with a large mobile telecommunication organization, we analyze how multiple data analytic teams evolve their infrastructure and processes towards DataOps. Also, we provide a stairway showing the different stages of the evolution process. With this evolution model, companies can identify the stage which they belong to and also, can try to move to the next stage by overcoming the challenges they encounter in the current stage.
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| 17. |
- Zhang, Hongyi, 1996, et al.
(author)
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Towards Federated Learning: A Case Study in the Telecommunication Domain
- 2021
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In: Lecture Notes in Business Information Processing. - Cham : Springer International Publishing. - 1865-1356 .- 1865-1348. ; 434 LNBIP, s. 238-253, s. 238-253
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Conference paper (peer-reviewed)abstract
- Federated Learning, as a distributed learning technique, has emerged with the improvement of the performance of IoT and edge devices. The emergence of this learning method alters the situation in which data must be centrally uploaded to the cloud for processing and maximizes the utilization of edge devices’ computing and storage capabilities. The learning approach eliminates the need to upload large amounts of local data and reduces data transfer latency with local data processing. Since the Federated Learning technique does not require centralized data for model training, it is better suited to edge learning scenarios in which nodes have limited data. However, despite the fact that Federated Learning has significant benefits, we discovered that companies struggle with integrating Federated Learning components into their systems. In this paper, we present case study research that describes reasons why companies anticipate Federated Learning as an applicable technique. Secondly, we summarize the services that a complete Federated Learning system needs to support in industrial scenarios and then identify the key challenges for industries to adopt and transition to Federated Learning. Finally, based on our empirical findings, we suggest five criteria for companies implementing reliable Federated Learning systems.
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