Laerte Xavier, Rodrigo dos Santos, Sândalo Bessa, Marco Tulio Valente
The Technical Debt (TD) metaphor refers to the unavoidable maintenance and evolution costs of the notquite- right decisions commonly taken by software developers. Due to its clear importance, developers usually document and manage TD by adopting ad-hoc and informal artifacts and activities. Thus, in this paper, we first propose a lightweight framework to support agile teams to manage and increase the awareness on TD. This framework, called LTD: Less Technical Debt Framework, has four key activities-TD Consensus, TD Discovery, TD Planning, and TD Payment-that can be easily plugged into current agile methodologies, such as Scrum. To assess the applicability of LTD in a real context, we also conduct a case study with two Scrum teams from a large public company. As a result, we achieved promising outcomes after adopting the framework. For example, the teams could reduce TD by creating a backlog of issues to pay during sprints.
{"title":"Agile Technical Debt Management usingthe LTD Framework","authors":"Laerte Xavier, Rodrigo dos Santos, Sândalo Bessa, Marco Tulio Valente","doi":"10.1145/3635439.3635443","DOIUrl":"https://doi.org/10.1145/3635439.3635443","url":null,"abstract":"The Technical Debt (TD) metaphor refers to the unavoidable maintenance and evolution costs of the notquite- right decisions commonly taken by software developers. Due to its clear importance, developers usually document and manage TD by adopting ad-hoc and informal artifacts and activities. Thus, in this paper, we first propose a lightweight framework to support agile teams to manage and increase the awareness on TD. This framework, called LTD: Less Technical Debt Framework, has four key activities-TD Consensus, TD Discovery, TD Planning, and TD Payment-that can be easily plugged into current agile methodologies, such as Scrum. To assess the applicability of LTD in a real context, we also conduct a case study with two Scrum teams from a large public company. As a result, we achieved promising outcomes after adopting the framework. For example, the teams could reduce TD by creating a backlog of issues to pay during sprints.","PeriodicalId":432885,"journal":{"name":"ACM SIGSOFT Software Engineering Notes","volume":"169 6","pages":"13 - 23"},"PeriodicalIF":0.0,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139153763","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}
Reyhaneh Jabbarvand, Saeid Tizpaz-Niari, Earl T. Barr, Satish Chandra
InteNSE is an interdisciplinary workshop for research at the intersection of Machine Learning (ML) and Software Engineering (SE) and would be a pioneer in emphasizing the implicit properties of neural software engineering and analysis. Due to recent computational advancements, ML has become an inseparable part of the SE research community. ML can indeed improve and revolutionize many SE tasks. However, most research in the AI and SE communities consider ML as a closed box, i.e., only considering the final performance of the developed models as an evaluation metric. Ignoring the implicit properties of neural models, such as interpretability and robustness, one cannot validate the model's actual performance, generalizability, and whether it is learning what it is supposed to do. Specifically, in the domain of SE, where the result of ML4SE tools is code synthesis, bug finding, or repair, interpretability and robustness are crucial to ensure the reliability of the products.
InteNSE 是机器学习（ML）和软件工程（SE）交叉研究的跨学科研讨会，将成为强调神经软件工程和分析隐含特性的先驱。由于近年来计算技术的进步，机器学习已成为 SE 研究界不可分割的一部分。ML 确实可以改进和革新许多 SE 任务。然而，人工智能和 SE 界的大多数研究都将 ML 视为一个封闭的盒子，即只将所开发模型的最终性能作为评估指标。忽略了神经模型的隐含属性，如可解释性和鲁棒性，就无法验证模型的实际性能、可泛化性以及它是否在学习它应该做的事情。具体来说，在 SE 领域，ML4SE 工具的结果是代码合成、错误查找或修复，因此可解释性和鲁棒性对于确保产品的可靠性至关重要。
{"title":"Summary of the 1st Interpretability and Robustness in Neural Software Engineering (InteNSE 2023)","authors":"Reyhaneh Jabbarvand, Saeid Tizpaz-Niari, Earl T. Barr, Satish Chandra","doi":"10.1145/3635439.3635446","DOIUrl":"https://doi.org/10.1145/3635439.3635446","url":null,"abstract":"InteNSE is an interdisciplinary workshop for research at the intersection of Machine Learning (ML) and Software Engineering (SE) and would be a pioneer in emphasizing the implicit properties of neural software engineering and analysis. Due to recent computational advancements, ML has become an inseparable part of the SE research community. ML can indeed improve and revolutionize many SE tasks. However, most research in the AI and SE communities consider ML as a closed box, i.e., only considering the final performance of the developed models as an evaluation metric. Ignoring the implicit properties of neural models, such as interpretability and robustness, one cannot validate the model's actual performance, generalizability, and whether it is learning what it is supposed to do. Specifically, in the domain of SE, where the result of ML4SE tools is code synthesis, bug finding, or repair, interpretability and robustness are crucial to ensure the reliability of the products.","PeriodicalId":432885,"journal":{"name":"ACM SIGSOFT Software Engineering Notes","volume":"46 1","pages":"30 - 33"},"PeriodicalIF":0.0,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139153299","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}
Rodrigo Santos, Pablo Antonino, Antonia Bertolino, Doo-Hwan Bae
This article reports on the results of the 11th ACM/IEEE International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems (SESoS 2023) in which researchers and practitioners discussed ideas and experiences on the research and practice for the development and evolution of complex softwareintensive systems, more specifically systems-of-systems (SoS) and software ecosystems (SECO). SESoS 2023 was co-located with the 45th IEEE/ACM International Conference on Software Engineering (ICSE 2023). After a decade running this workshop, the SESoS community is advancing on how to cope with the different dimensions that should be considered in the engineering of those classes of systems (i.e. technological, organizational, and social). In addition, benchmarks for conducting research on the areas as well as approaches for investigating emerging domains (smart ecosystems) and non-functional requirements on those systems were also pointed out as relevant challenges.
{"title":"Report on the 11th ACM/IEEE International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems - SESoS@ICSE 2023","authors":"Rodrigo Santos, Pablo Antonino, Antonia Bertolino, Doo-Hwan Bae","doi":"10.1145/3635439.3635447","DOIUrl":"https://doi.org/10.1145/3635439.3635447","url":null,"abstract":"This article reports on the results of the 11th ACM/IEEE International Workshop on Software Engineering for Systems-of-Systems and Software Ecosystems (SESoS 2023) in which researchers and practitioners discussed ideas and experiences on the research and practice for the development and evolution of complex softwareintensive systems, more specifically systems-of-systems (SoS) and software ecosystems (SECO). SESoS 2023 was co-located with the 45th IEEE/ACM International Conference on Software Engineering (ICSE 2023). After a decade running this workshop, the SESoS community is advancing on how to cope with the different dimensions that should be considered in the engineering of those classes of systems (i.e. technological, organizational, and social). In addition, benchmarks for conducting research on the areas as well as approaches for investigating emerging domains (smart ecosystems) and non-functional requirements on those systems were also pointed out as relevant challenges.","PeriodicalId":432885,"journal":{"name":"ACM SIGSOFT Software Engineering Notes","volume":"7 1","pages":"34 - 37"},"PeriodicalIF":0.0,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139154681","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}
Farhad Arbab, Marco Autili, Federico Ciccozzi, Pascal Poizat, Massimo Tivoli
Over the past three decades, automation in software development has gone mainstream. Software development teams strive to automate as much of the software development activities as possible, spanning requirements specification, system modeling, code generation, testing, deployment, verification, as well as release phases, project status reporting and system maintenance. Automation helps to reduce development time and cost, as well as to concentrate knowledge by bringing quality into every step of the development process. The Workshop on Automated and verifiable Software sYstem DEvelopment (ASYDE) provided a forum to share and discuss innovative contributions to research and practice related to novel software engineering approaches to automated and verifiable development of software systems. The 5th edition took place on September 11th, 2023, in Kirchberg, Luxembourg. Notably, this marked the inaugural co-location of ASYDE with the IEEE/ACM International Conference on Automated Software Engineering (ASE).
{"title":"Summary of the 5th International Workshop on Automated andverifiable Software sYstem DEvelopment (ASYDE)co-located with the 38th IEEE/ACM ASE 2023","authors":"Farhad Arbab, Marco Autili, Federico Ciccozzi, Pascal Poizat, Massimo Tivoli","doi":"10.1145/3635439.3635444","DOIUrl":"https://doi.org/10.1145/3635439.3635444","url":null,"abstract":"Over the past three decades, automation in software development has gone mainstream. Software development teams strive to automate as much of the software development activities as possible, spanning requirements specification, system modeling, code generation, testing, deployment, verification, as well as release phases, project status reporting and system maintenance. Automation helps to reduce development time and cost, as well as to concentrate knowledge by bringing quality into every step of the development process. The Workshop on Automated and verifiable Software sYstem DEvelopment (ASYDE) provided a forum to share and discuss innovative contributions to research and practice related to novel software engineering approaches to automated and verifiable development of software systems. The 5th edition took place on September 11th, 2023, in Kirchberg, Luxembourg. Notably, this marked the inaugural co-location of ASYDE with the IEEE/ACM International Conference on Automated Software Engineering (ASE).","PeriodicalId":432885,"journal":{"name":"ACM SIGSOFT Software Engineering Notes","volume":"51 5","pages":"24 - 26"},"PeriodicalIF":0.0,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139154445","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}
The Eighth International Workshop on Empirical Requirements Engineering (EmpiRE 2023), co-located with the 31st IEEE International Requirements Engineering conference (RE 2023), was held on September 5, 2023 in Hannover, Germany. This report presents the workshop structure, the keynote speech, the themes of the presented papers, and the panel discussion.
{"title":"Report of the 8th Workshop on Empirical RequirementsEngineering (EmpiRE 2023)","authors":"Vincenzo Gervasi, Alessandro Marchetto, Maya Daneva","doi":"10.1145/3635439.3635445","DOIUrl":"https://doi.org/10.1145/3635439.3635445","url":null,"abstract":"The Eighth International Workshop on Empirical Requirements Engineering (EmpiRE 2023), co-located with the 31st IEEE International Requirements Engineering conference (RE 2023), was held on September 5, 2023 in Hannover, Germany. This report presents the workshop structure, the keynote speech, the themes of the presented papers, and the panel discussion.","PeriodicalId":432885,"journal":{"name":"ACM SIGSOFT Software Engineering Notes","volume":"188 1","pages":"27 - 29"},"PeriodicalIF":0.0,"publicationDate":"2023-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139153821","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}
Natural language processing (NLP) involves the automated anal- ysis and manipulation of human language. This includes algo- rithms that can analyze text created by humans and algorithms that can generate text that appears natural. Nowadays, NLP methods are becoming increasingly prevalent to enhance various aspects of software development. Indeed, throughout the software development lifecycle, numerous natural language artifacts are produced. Therefore, the existence of NLP-based approaches and tools has opened up possibilities for improving the e ectiveness and productivity of software engineers, processes, and products. The second edition of the Natural Language-Based Software Engi- neering Workshop (NLBSE) took place in 2023 alongside the 45th International Conference on Software Engineering (ICSE 2023), where the research community engaged in discussions about these approaches. This event brought together researchers and practi- tioners from the elds of NLP and software engineering to ex- change experiences, establish future research directions, and pro- mote the adoption of NLP techniques and tools in tackling chal- lenges speci c to software engineering. In this paper, we present a summary of the 2nd edition of the workshop, which comprised three full papers, four short/position papers, ve tool competi- tion/demonstration papers, two keynote talks (Automated Bug Management: Re ections & the Road Ahead" by David Lo and Trends and Opportunities in the Application of Large Language Models: the Quest for Maximum E ect" by Albert Ziegler), fol- lowed by extensive discussion among NLBSE participants. More details can be found at https://nlbse2023.github.io/index. html
{"title":"Summary of the 2nd Natural Language-based Software Engineering Workshop (NLBSE 2023)","authors":"Sebastiano Panichella, Andrea Di Sorbo","doi":"10.1145/3617946.3617957","DOIUrl":"https://doi.org/10.1145/3617946.3617957","url":null,"abstract":"Natural language processing (NLP) involves the automated anal- ysis and manipulation of human language. This includes algo- rithms that can analyze text created by humans and algorithms that can generate text that appears natural. Nowadays, NLP methods are becoming increasingly prevalent to enhance various aspects of software development. Indeed, throughout the software development lifecycle, numerous natural language artifacts are produced. Therefore, the existence of NLP-based approaches and tools has opened up possibilities for improving the e ectiveness and productivity of software engineers, processes, and products. The second edition of the Natural Language-Based Software Engi- neering Workshop (NLBSE) took place in 2023 alongside the 45th International Conference on Software Engineering (ICSE 2023), where the research community engaged in discussions about these approaches. This event brought together researchers and practi- tioners from the elds of NLP and software engineering to ex- change experiences, establish future research directions, and pro- mote the adoption of NLP techniques and tools in tackling chal- lenges speci c to software engineering. In this paper, we present a summary of the 2nd edition of the workshop, which comprised three full papers, four short/position papers, ve tool competi- tion/demonstration papers, two keynote talks (Automated Bug Management: Re ections & the Road Ahead\" by David Lo and Trends and Opportunities in the Application of Large Language Models: the Quest for Maximum E ect\" by Albert Ziegler), fol- lowed by extensive discussion among NLBSE participants. More details can be found at https://nlbse2023.github.io/index. html","PeriodicalId":432885,"journal":{"name":"ACM SIGSOFT Software Engineering Notes","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135919561","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}
Sydney Padua's The Thrilling Adventures of Lovelace and Babbage violates the rules of Passages in a technical sense; the book was published in 2015, so cannot be a classic, right? I could excuse cheating on the grounds that covering this delightful book is so important that I can't wait until 2025. After all, I might be hit by a bus; ACM SIGSOFT might dissolve; rogue AI might go all Skynet and murder us all; less catastrophically, I might tire of doing these columns or you might tire of reading them. A much better excuse,however, is that Padua's book really dates from a throwaway cartoon she posted on the web in 2009. In any case, this month's column is a review of Sydney Padua's 2015 book, The Thrilling Adventures of Lovelace and Babbage - with Interesting Curious Anecdotes of Celebrated and Distinguished Characters, Fully Illustrating a Variety of Instructive and Amusing Scenes; As Performed Within and Without the Remarkable Difference Engine (Embellished with Portraits and Scientific Diagrams).
{"title":"Passages","authors":"Alex Groce","doi":"10.1145/3617946.3617948","DOIUrl":"https://doi.org/10.1145/3617946.3617948","url":null,"abstract":"Sydney Padua's The Thrilling Adventures of Lovelace and Babbage violates the rules of Passages in a technical sense; the book was published in 2015, so cannot be a classic, right? I could excuse cheating on the grounds that covering this delightful book is so important that I can't wait until 2025. After all, I might be hit by a bus; ACM SIGSOFT might dissolve; rogue AI might go all Skynet and murder us all; less catastrophically, I might tire of doing these columns or you might tire of reading them. A much better excuse,however, is that Padua's book really dates from a throwaway cartoon she posted on the web in 2009. In any case, this month's column is a review of Sydney Padua's 2015 book, The Thrilling Adventures of Lovelace and Babbage - with Interesting Curious Anecdotes of Celebrated and Distinguished Characters, Fully Illustrating a Variety of Instructive and Amusing Scenes; As Performed Within and Without the Remarkable Difference Engine (Embellished with Portraits and Scientific Diagrams).","PeriodicalId":432885,"journal":{"name":"ACM SIGSOFT Software Engineering Notes","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135919568","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}
This column is a change of pace, a report on Formula Hybrid+Electric contest held last May at the New Hampshire Motor Speedway in Loudon, NH. Formula Hybrid was founded by the Thayer School of Engineering at Dartmouth and is sponsored by, among others, IEEE and SAE. Formula Hybrid racers are modeled on scaled down formula race cars, and are single seat, open cockpit, and open wheel. Universities and colleges competing at the May event included Dartmouth, BU, Carnegie Mellon, Illinois Institute of Technology, Indiana and Purdue Universities, Lafayette, Lawrence Tech, MIT, Middlebury, Milwaukee School of Engineering, Princeton, RPI, Tufts, UVM, U. Victoria, U. Waterloo, U. Wyoming, WPI, and Yale.
{"title":"Formula Hybrid + Electric: Because it's crazy to try","authors":"Robert Schaefer","doi":"10.1145/3617946.3617949","DOIUrl":"https://doi.org/10.1145/3617946.3617949","url":null,"abstract":"This column is a change of pace, a report on Formula Hybrid+Electric contest held last May at the New Hampshire Motor Speedway in Loudon, NH. Formula Hybrid was founded by the Thayer School of Engineering at Dartmouth and is sponsored by, among others, IEEE and SAE. Formula Hybrid racers are modeled on scaled down formula race cars, and are single seat, open cockpit, and open wheel. Universities and colleges competing at the May event included Dartmouth, BU, Carnegie Mellon, Illinois Institute of Technology, Indiana and Purdue Universities, Lafayette, Lawrence Tech, MIT, Middlebury, Milwaukee School of Engineering, Princeton, RPI, Tufts, UVM, U. Victoria, U. Waterloo, U. Wyoming, WPI, and Yale.","PeriodicalId":432885,"journal":{"name":"ACM SIGSOFT Software Engineering Notes","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135919575","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}
Deep Learning (DL) techniques help software developers thanks to their ability to learn from historical information which is useful in several program analysis and testing tasks (e.g., malware detection, fuzz testing, bug-finding, and type-checking). DL-based software systems are also increasingly adopted in safety-critical domains, such as autonomous driving, medical diagnosis, and aircraft collision avoidance systems. In particular, testing the correctness and reliability of DL-based systems is paramount, since a failure of such systems would cause a significant safety risk for the involved people and/or environment. The 4th International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest 2023) was co-located with the 45th International Conference on Software Engineering (ICSE), with the goal of targeting research at the intersection of software engineering and deep learning and devise novel approaches and tools to ensure the interpretability and dependability of software systems that depends on DL components.
{"title":"Summary of the Fourth International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest 2023)","authors":"Matteo Biagiola, Nicolás Cardozo, Donghwan Shin, Foutse Khomh, Andrea Stocco, Vincenzo Riccio","doi":"10.1145/3617946.3617953","DOIUrl":"https://doi.org/10.1145/3617946.3617953","url":null,"abstract":"Deep Learning (DL) techniques help software developers thanks to their ability to learn from historical information which is useful in several program analysis and testing tasks (e.g., malware detection, fuzz testing, bug-finding, and type-checking). DL-based software systems are also increasingly adopted in safety-critical domains, such as autonomous driving, medical diagnosis, and aircraft collision avoidance systems. In particular, testing the correctness and reliability of DL-based systems is paramount, since a failure of such systems would cause a significant safety risk for the involved people and/or environment. The 4th International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest 2023) was co-located with the 45th International Conference on Software Engineering (ICSE), with the goal of targeting research at the intersection of software engineering and deep learning and devise novel approaches and tools to ensure the interpretability and dependability of software systems that depends on DL components.","PeriodicalId":432885,"journal":{"name":"ACM SIGSOFT Software Engineering Notes","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135919563","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}
Danny Weyns, Radu Calinescu, Raffaela Mirandola, Kenji Tei, Maribel Acosta, Amel Bennaceur, Nicolas Boltz, Tomas Bures, Javier Camara, Ada Diaconescu, Gregor Engels, Simos Gerasimou, Ilias Gerostathopoulos, Sinem Getir Yaman, Vincenzo Grassi, Sebastian Hahner, Emmanuel Letier, Marin Litoiu, Lina Marsso, Angelika Musil, Juergen Musil, Genaina Nunes Rodrigues, Diego Perez-Palacin, Federico Quin, Patrizia Scandurra, Antonio Vallecillo, Andrea Zisman
Despite considerable research efforts on handling uncertainty in self-adaptive systems, a comprehensive understanding of the precise nature of uncertainty is still lacking. This paper summarises the findings of the 2023 Bertinoro Seminar on Uncertainty in Self- Adaptive Systems, which aimed at thoroughly investigating the notion of uncertainty, and outlining open challenges associated with its handling in self-adaptive systems. The seminar discussions were centered around five core topics: (1) agile end-toend handling of uncertainties in goal-oriented self-adaptive systems, (2) managing uncertainty risks for self-adaptive systems, (3) uncertainty propagation and interaction, (4) uncertainty in self-adaptive machine learning systems, and (5) human empowerment under uncertainty. Building on the insights from these discussions, we propose a research agenda listing key open challenges, and a possible way forward for addressing them in the coming years.
{"title":"Towards a Research Agenda for Understanding and ManagingUncertainty in Self-Adaptive Systems","authors":"Danny Weyns, Radu Calinescu, Raffaela Mirandola, Kenji Tei, Maribel Acosta, Amel Bennaceur, Nicolas Boltz, Tomas Bures, Javier Camara, Ada Diaconescu, Gregor Engels, Simos Gerasimou, Ilias Gerostathopoulos, Sinem Getir Yaman, Vincenzo Grassi, Sebastian Hahner, Emmanuel Letier, Marin Litoiu, Lina Marsso, Angelika Musil, Juergen Musil, Genaina Nunes Rodrigues, Diego Perez-Palacin, Federico Quin, Patrizia Scandurra, Antonio Vallecillo, Andrea Zisman","doi":"10.1145/3617946.3617951","DOIUrl":"https://doi.org/10.1145/3617946.3617951","url":null,"abstract":"Despite considerable research efforts on handling uncertainty in self-adaptive systems, a comprehensive understanding of the precise nature of uncertainty is still lacking. This paper summarises the findings of the 2023 Bertinoro Seminar on Uncertainty in Self- Adaptive Systems, which aimed at thoroughly investigating the notion of uncertainty, and outlining open challenges associated with its handling in self-adaptive systems. The seminar discussions were centered around five core topics: (1) agile end-toend handling of uncertainties in goal-oriented self-adaptive systems, (2) managing uncertainty risks for self-adaptive systems, (3) uncertainty propagation and interaction, (4) uncertainty in self-adaptive machine learning systems, and (5) human empowerment under uncertainty. Building on the insights from these discussions, we propose a research agenda listing key open challenges, and a possible way forward for addressing them in the coming years.","PeriodicalId":432885,"journal":{"name":"ACM SIGSOFT Software Engineering Notes","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135919574","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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