Pub Date : 2019-08-26DOI: 10.1007/s00450-019-00417-6
Lukas Reinfurt, Michael Falkenthal, Frank Leymann
Pattern languages as tools for solving problems based on interconnected, abstract, and proven solutions can offer valuable help to practitioners. But there is always the question of where to begin when a pattern language should be applied. Their authors often provide entry points, but these are usually only useful if one starts completely from scratch or from a very specific situation. When confronted with problems at hand, practitioners are often left to find a suitable entry point themselves by reading through the whole pattern language to find applicable patterns. To help with this problem, we present a general approach and its formalization that provides entry points for any kind of situation. Our general three step approach guides practitioners through Situation Assessment, Treatment Selection, and Treatment Application in order to find and apply a suitable pattern language for their specific problems. We formalize all the parts involved and show that the facts collected during Situation Assessment can be used to find a suitable entry point for a specific situation. We also present an algorithm for finding these entry points.
{"title":"Where to begin: on pattern language entry points","authors":"Lukas Reinfurt, Michael Falkenthal, Frank Leymann","doi":"10.1007/s00450-019-00417-6","DOIUrl":"https://doi.org/10.1007/s00450-019-00417-6","url":null,"abstract":"Pattern languages as tools for solving problems based on interconnected, abstract, and proven solutions can offer valuable help to practitioners. But there is always the question of where to begin when a pattern language should be applied. Their authors often provide entry points, but these are usually only useful if one starts completely from scratch or from a very specific situation. When confronted with problems at hand, practitioners are often left to find a suitable entry point themselves by reading through the whole pattern language to find applicable patterns. To help with this problem, we present a general approach and its formalization that provides entry points for any kind of situation. Our general three step approach guides practitioners through <i>Situation Assessment</i>, <i>Treatment Selection</i>, and <i>Treatment Application</i> in order to find and apply a suitable pattern language for their specific problems. We formalize all the parts involved and show that the facts collected during <i>Situation Assessment</i> can be used to find a suitable entry point for a specific situation. We also present an algorithm for finding these entry points.","PeriodicalId":41265,"journal":{"name":"SICS Software-Intensive Cyber-Physical Systems","volume":"310 3","pages":"1 - 13"},"PeriodicalIF":2.4,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138495265","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}
Pub Date : 2019-08-26DOI: 10.1007/s00450-019-00414-9
Robin Lichtenthäler, Mike Prechtl, Christoph Schwille, Tobias Schwartz, Pascal Cezanne, Guido Wirtz
With the emergence of cloud-native applications, the question arises how existing, often monolithic, applications can be migrated to this new paradigm. The main migration challenges are the decomposition of an application into fine-grained components and the introduction of cloud computing paradigms. With complex existing applications the migration is difficult. A structured and tool-supported approach would facilitate the migration process, which is why this paper proposes a model-driven engineering based approach. As a basis, this paper derives and presents requirements for such an approach from the literature on the one hand and a migration case study on the other. The requirements are specifically targeted at the necessary models, but also consider the overall approach. The necessities for the realization of a model-driven cloud-native migration approach are shown and remaining challenges are discussed.
{"title":"Requirements for a model-driven cloud-native migration of monolithic web-based applications","authors":"Robin Lichtenthäler, Mike Prechtl, Christoph Schwille, Tobias Schwartz, Pascal Cezanne, Guido Wirtz","doi":"10.1007/s00450-019-00414-9","DOIUrl":"https://doi.org/10.1007/s00450-019-00414-9","url":null,"abstract":"With the emergence of cloud-native applications, the question arises how existing, often monolithic, applications can be migrated to this new paradigm. The main migration challenges are the decomposition of an application into fine-grained components and the introduction of cloud computing paradigms. With complex existing applications the migration is difficult. A structured and tool-supported approach would facilitate the migration process, which is why this paper proposes a model-driven engineering based approach. As a basis, this paper derives and presents requirements for such an approach from the literature on the one hand and a migration case study on the other. The requirements are specifically targeted at the necessary models, but also consider the overall approach. The necessities for the realization of a model-driven cloud-native migration approach are shown and remaining challenges are discussed.","PeriodicalId":41265,"journal":{"name":"SICS Software-Intensive Cyber-Physical Systems","volume":"310 9","pages":"1 - 12"},"PeriodicalIF":2.4,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138495261","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}
Pub Date : 2019-08-26DOI: 10.1007/s00450-019-00418-5
Saliha Irem Besik, Johann-Christoph Freytag
Clinical workflows consist of sets of tasks involving patients and healthcare professionals. In such an environment, maintaining the privacy of patient data is a significant challenge. Healthcare providers have to consider both legislative compliances with tightening privacy regulations and growing privacy concerns of individuals. Unlike data security, which aims at preventing unauthorized access, privacy focuses on providing individuals the ability to control when, how, and to what extent their data is used with a particular purpose. In this paper, we present our first steps on transforming existing non-privacy-aware clinical workflows into privacy-aware ones through algorithms based on privacy policies and privacy preferences.
{"title":"A formal approach to build privacy-awareness into clinical workflows","authors":"Saliha Irem Besik, Johann-Christoph Freytag","doi":"10.1007/s00450-019-00418-5","DOIUrl":"https://doi.org/10.1007/s00450-019-00418-5","url":null,"abstract":"Clinical workflows consist of sets of tasks involving patients and healthcare professionals. In such an environment, maintaining the privacy of patient data is a significant challenge. Healthcare providers have to consider both legislative compliances with tightening privacy regulations and growing privacy concerns of individuals. Unlike data security, which aims at preventing unauthorized access, privacy focuses on providing individuals the ability to control when, how, and to what extent their data is used with a particular purpose. In this paper, we present our first steps on transforming existing non-privacy-aware clinical workflows into privacy-aware ones through algorithms based on privacy policies and privacy preferences.","PeriodicalId":41265,"journal":{"name":"SICS Software-Intensive Cyber-Physical Systems","volume":"310 4","pages":"1 - 12"},"PeriodicalIF":2.4,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138495264","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}
Pub Date : 2019-08-26DOI: 10.1007/s00450-019-00410-z
Daniel Del Gaudio, Pascal Hirmer
Today, Internet of Things applications are available throughout many different domains (manufacturing, health, cities, homes), enabling a high degree of automation to ease people’s lives. For example, automated heating systems in a smart home can lead to reduced costs and an increased comfort for the residents. In the IoT, situations can be detected through interpretation of data produced by heterogeneous sensors, which typically lead to an invocation of actuators. In such applications, sensor data is usually streamed to a central instance for processing. However, especially in time-critical applications, this is not feasible, since high latency is an issue. To cope with this problem, in this paper, we introduce an approach for decentralized data processing in the IoT. This leads to decreased latency as well as a reduction of costs.
{"title":"A lightweight messaging engine for decentralized data processing in the Internet of Things","authors":"Daniel Del Gaudio, Pascal Hirmer","doi":"10.1007/s00450-019-00410-z","DOIUrl":"https://doi.org/10.1007/s00450-019-00410-z","url":null,"abstract":"Today, Internet of Things applications are available throughout many different domains (manufacturing, health, cities, homes), enabling a high degree of automation to ease people’s lives. For example, automated heating systems in a smart home can lead to reduced costs and an increased comfort for the residents. In the IoT, situations can be detected through interpretation of data produced by heterogeneous sensors, which typically lead to an invocation of actuators. In such applications, sensor data is usually streamed to a central instance for processing. However, especially in time-critical applications, this is not feasible, since high latency is an issue. To cope with this problem, in this paper, we introduce an approach for decentralized data processing in the IoT. This leads to decreased latency as well as a reduction of costs.","PeriodicalId":41265,"journal":{"name":"SICS Software-Intensive Cyber-Physical Systems","volume":"5 1","pages":"1 - 10"},"PeriodicalIF":2.4,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138517065","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}
Pub Date : 2019-08-26DOI: 10.1007/s00450-019-00419-4
Johanna Barzen, F. Leymann
{"title":"Quantum humanities: a vision for quantum computing in digital humanities","authors":"Johanna Barzen, F. Leymann","doi":"10.1007/s00450-019-00419-4","DOIUrl":"https://doi.org/10.1007/s00450-019-00419-4","url":null,"abstract":"","PeriodicalId":41265,"journal":{"name":"SICS Software-Intensive Cyber-Physical Systems","volume":"35 1","pages":"153-158"},"PeriodicalIF":2.4,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s00450-019-00419-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44933589","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}
Pub Date : 2019-08-26DOI: 10.1007/s00450-019-00413-w
G. Casale, M. Artač, W.-J. van den Heuvel, A. van Hoorn, P. Jakovits, F. Leymann, M. Long, V. Papanikolaou, D. Presenza, A. Russo, S. N. Srirama, D. A. Tamburri, M. Wurster, L. Zhu
Emerging serverless computing technologies, such as function as a service (FaaS), enable developers to virtualize the internal logic of an application, simplifying the management of cloud-native services and allowing cost savings through billing and scaling at the level of individual functions. Serverless computing is therefore rapidly shifting the attention of software vendors to the challenge of developing cloud applications deployable on FaaS platforms. In this vision paper, we present the research agenda of the RADON project (http://radon-h2020.eu), which aims to develop a model-driven DevOps framework for creating and managing applications based on serverless computing. RADON applications will consist of fine-grained and independent microservices that can efficiently and optimally exploit FaaS and container technologies. Our methodology strives to tackle complexity in designing such applications, including the solution of optimal decomposition, the reuse of serverless functions as well as the abstraction and actuation of event processing chains, while avoiding cloud vendor lock-in through models.
{"title":"RADON: rational decomposition and orchestration for serverless computing","authors":"G. Casale, M. Artač, W.-J. van den Heuvel, A. van Hoorn, P. Jakovits, F. Leymann, M. Long, V. Papanikolaou, D. Presenza, A. Russo, S. N. Srirama, D. A. Tamburri, M. Wurster, L. Zhu","doi":"10.1007/s00450-019-00413-w","DOIUrl":"https://doi.org/10.1007/s00450-019-00413-w","url":null,"abstract":"Emerging serverless computing technologies, such as function as a service (FaaS), enable developers to virtualize the internal logic of an application, simplifying the management of cloud-native services and allowing cost savings through billing and scaling at the level of individual functions. Serverless computing is therefore rapidly shifting the attention of software vendors to the challenge of developing cloud applications deployable on FaaS platforms. In this vision paper, we present the research agenda of the RADON project (http://radon-h2020.eu), which aims to develop a model-driven DevOps framework for creating and managing applications based on serverless computing. RADON applications will consist of fine-grained and independent microservices that can efficiently and optimally exploit FaaS and container technologies. Our methodology strives to tackle complexity in designing such applications, including the solution of optimal decomposition, the reuse of serverless functions as well as the abstraction and actuation of event processing chains, while avoiding cloud vendor lock-in through models.","PeriodicalId":41265,"journal":{"name":"SICS Software-Intensive Cyber-Physical Systems","volume":"310 7","pages":"1 - 11"},"PeriodicalIF":2.4,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138495263","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}
Pub Date : 2019-08-26DOI: 10.1007/s00450-019-00415-8
Lukas Harzenetter, Uwe Breitenbücher, Kálmán Képes, Frank Leymann
In recent years, several technologies were developed enabling the automated provisioning and decommissioning of cloud applications. To reduce costs, these applications can be terminated and restarted on demand. However, as an application is terminated, its current application state, i.e., all application specific data is deleted along with the running application instance. This application state may be holding all business-critical information, and, hence, must be saved before the application is terminated. One possibility to save application states is to create VM snapshots although this is not always possible or sufficient. Therefore, we introduce two approaches: (1) a concept to generically terminate applications and save their internal state, and (2) an approach to reinstate the application in the same state again. To evaluate their practical feasibility, we implemented a proof of concept in the OpenTOSCA ecosystem.
{"title":"Freezing and defrosting cloud applications: automated saving and restoring of running applications","authors":"Lukas Harzenetter, Uwe Breitenbücher, Kálmán Képes, Frank Leymann","doi":"10.1007/s00450-019-00415-8","DOIUrl":"https://doi.org/10.1007/s00450-019-00415-8","url":null,"abstract":"In recent years, several technologies were developed enabling the automated provisioning and decommissioning of cloud applications. To reduce costs, these applications can be terminated and restarted on demand. However, as an application is terminated, its current application state, i.e., all application specific data is deleted along with the running application instance. This application state may be holding all business-critical information, and, hence, must be saved before the application is terminated. One possibility to save application states is to create VM snapshots although this is not always possible or sufficient. Therefore, we introduce two approaches: (1) a concept to generically terminate applications and save their internal state, and (2) an approach to reinstate the application in the same state again. To evaluate their practical feasibility, we implemented a proof of concept in the OpenTOSCA ecosystem.","PeriodicalId":41265,"journal":{"name":"SICS Software-Intensive Cyber-Physical Systems","volume":"309 12","pages":"1 - 14"},"PeriodicalIF":2.4,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138495276","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}
Pub Date : 2019-08-26DOI: 10.1007/s00450-019-00416-7
Jasmin Guth, Frank Leymann
With the continuous growth of IT application systems, the complexity of architecture modeling and development increases. Patterns document proven solutions for recurring problems in an abstract and human readable manner. Within the domain of IT architectures, they should support the architecture modeling and development process. Due to the documentation of patterns as text documents, they cannot be applied to an architecture automatically: patterns have to be read, understood, adapted to the corresponding use case, and realized manually over and over again. Consequently, architecture modeling considering the variety of documented patterns becomes even more complex and time-consuming. To tackle these issues, we introduce an approach and for an automated application and realization of patterns in architectural graphs using graph transformation techniques. This eases the architecture modeling process in which proven solutions for recurring problems can be selected as required and applied automatically. We present the concept, formalization, and validate our approach based on an application example.
{"title":"Pattern-based rewrite and refinement of architectures using graph theory","authors":"Jasmin Guth, Frank Leymann","doi":"10.1007/s00450-019-00416-7","DOIUrl":"https://doi.org/10.1007/s00450-019-00416-7","url":null,"abstract":"With the continuous growth of IT application systems, the complexity of architecture modeling and development increases. Patterns document proven solutions for recurring problems in an abstract and human readable manner. Within the domain of IT architectures, they should support the architecture modeling and development process. Due to the documentation of patterns as text documents, they cannot be applied to an architecture automatically: patterns have to be read, understood, adapted to the corresponding use case, and realized manually over and over again. Consequently, architecture modeling considering the variety of documented patterns becomes even more complex and time-consuming. To tackle these issues, we introduce an approach and for an automated application and realization of patterns in architectural graphs using graph transformation techniques. This eases the architecture modeling process in which proven solutions for recurring problems can be selected as required and applied automatically. We present the concept, formalization, and validate our approach based on an application example.","PeriodicalId":41265,"journal":{"name":"SICS Software-Intensive Cyber-Physical Systems","volume":"310 2","pages":"1 - 12"},"PeriodicalIF":2.4,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138495266","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}
Pub Date : 2019-08-26DOI: 10.1007/s00450-019-00409-6
Leonardo Gazzarri, Melanie Herschel
Entity resolution (ER) refers to the problem of finding which virtual representations in one or more data sources refer to the same real-world entity. A central question in ER is how to find matching entity representations (so called duplicates) efficiently and in a scalable way. One general technique to address these issues is to leverage parallelization. In particular, almost all work on parallel ER focus on data parallelism. This paper focuses on task parallelism for ER. This type of parallelism allows to support incremental ER that offers incremental computation of the solution by streaming results of intermediate stages of ER as soon as they are computed. This possibly allows to obtain results in a more timely fashion and can also serve in a service-oriented setting with limited time or monetary budget. In summary, this paper presents a framework for task-parallelization of ER, supporting in particular ER of large amounts of semi-structured and heterogeneous data. We also discuss a possible implementation of our framework.
{"title":"Towards task-based parallelization for entity resolution","authors":"Leonardo Gazzarri, Melanie Herschel","doi":"10.1007/s00450-019-00409-6","DOIUrl":"https://doi.org/10.1007/s00450-019-00409-6","url":null,"abstract":"Entity resolution (ER) refers to the problem of finding which virtual representations in one or more data sources refer to the same real-world entity. A central question in ER is how to find matching entity representations (so called duplicates) efficiently and in a scalable way. One general technique to address these issues is to leverage parallelization. In particular, almost all work on parallel ER focus on data parallelism. This paper focuses on task parallelism for ER. This type of parallelism allows to support incremental ER that offers incremental computation of the solution by streaming results of intermediate stages of ER as soon as they are computed. This possibly allows to obtain results in a more timely fashion and can also serve in a service-oriented setting with limited time or monetary budget. In summary, this paper presents a framework for task-parallelization of ER, supporting in particular ER of large amounts of semi-structured and heterogeneous data. We also discuss a possible implementation of our framework.","PeriodicalId":41265,"journal":{"name":"SICS Software-Intensive Cyber-Physical Systems","volume":"310 8","pages":"1 - 8"},"PeriodicalIF":2.4,"publicationDate":"2019-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138495262","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}
Pub Date : 2019-08-17DOI: 10.1007/s00450-019-00408-7
Manuel Fritz, Osama Muazzen, Michael Behringer, Holger Schwarz
The plethora of analytic platforms escalates the difficulty of selecting the most appropriate analytic platform that fits the needed data mining task, the dataset as well as additional user-defined criteria. Especially analysts, who are rather focused on the analytics domain, experience difficulties to keep up with the latest developments. In this work, we introduce the ASAP-DM framework, which enables analysts to seamlessly use several platforms, whereas programmers can easily add several platforms to the framework. Furthermore, we investigate how to predict a platform based on specific criteria, such as lowest runtime or resource consumption during the execution of a data mining task. We formulate this task as an optimization problem, which can be solved by today’s classification algorithms. We evaluate the proposed framework on several analytic platforms such as Spark, Mahout, and WEKA along with several data mining algorithms for classification, clustering, and association rule discovery. Our experiments unveil that the automatic selection process can save up to 99.71% of the execution time due to automatically choosing a faster platform.
{"title":"ASAP-DM: a framework for automatic selection of analytic platforms for data mining","authors":"Manuel Fritz, Osama Muazzen, Michael Behringer, Holger Schwarz","doi":"10.1007/s00450-019-00408-7","DOIUrl":"https://doi.org/10.1007/s00450-019-00408-7","url":null,"abstract":"The plethora of analytic platforms escalates the difficulty of selecting the most appropriate analytic platform that fits the needed data mining task, the dataset as well as additional user-defined criteria. Especially analysts, who are rather focused on the analytics domain, experience difficulties to keep up with the latest developments. In this work, we introduce the ASAP-DM framework, which enables analysts to seamlessly use several platforms, whereas programmers can easily add several platforms to the framework. Furthermore, we investigate how to predict a platform based on specific criteria, such as lowest runtime or resource consumption during the execution of a data mining task. We formulate this task as an optimization problem, which can be solved by today’s classification algorithms. We evaluate the proposed framework on several analytic platforms such as Spark, Mahout, and WEKA along with several data mining algorithms for classification, clustering, and association rule discovery. Our experiments unveil that the automatic selection process can save up to 99.71% of the execution time due to automatically choosing a faster platform.","PeriodicalId":41265,"journal":{"name":"SICS Software-Intensive Cyber-Physical Systems","volume":"310 10","pages":"1 - 13"},"PeriodicalIF":2.4,"publicationDate":"2019-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138495260","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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