Fitting models to data is all the rage nowadays but has long been an essential skill of engineers. Veterans know that real-world systems foil textbook techniques by interleaving routine operating conditions with bouts of overload and failure; to be practical, a method must model the former without distortion by the latter. Surprisingly effective aid comes from an unlikely quarter: a simple and intuitive model-fitting approach that predates the Babbage Engine. The foundation of industrial-strength decision support and anomaly detection for production datacenters, this approach yields accurate yet intelligible models without hand-holding or fuss. It is easy to practice with modern analytics software and is widely applicable to computing systems and beyond.
{"title":"Steampunk Machine Learning","authors":"T. Kelly","doi":"10.1145/3511543","DOIUrl":"https://doi.org/10.1145/3511543","url":null,"abstract":"Fitting models to data is all the rage nowadays but has long been an essential skill of engineers. Veterans know that real-world systems foil textbook techniques by interleaving routine operating conditions with bouts of overload and failure; to be practical, a method must model the former without distortion by the latter. Surprisingly effective aid comes from an unlikely quarter: a simple and intuitive model-fitting approach that predates the Babbage Engine. The foundation of industrial-strength decision support and anomaly detection for production datacenters, this approach yields accurate yet intelligible models without hand-holding or fuss. It is easy to practice with modern analytics software and is widely applicable to computing systems and beyond.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"19 1","pages":"5 - 17"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45548207","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}
Valerie Chen, Jeffrey Li, Joon Sik Kim, Gregory Plumb, Ameet Talwalkar
The emergence of machine learning as a society-changing technology in the past decade has triggered concerns about people's inability to understand the reasoning of increasingly complex models. The field of IML (interpretable machine learning) grew out of these concerns, with the goal of empowering various stakeholders to tackle use cases, such as building trust in models, performing model debugging, and generally informing real human decision-making.
{"title":"Interpretable Machine Learning","authors":"Valerie Chen, Jeffrey Li, Joon Sik Kim, Gregory Plumb, Ameet Talwalkar","doi":"10.1145/3511299","DOIUrl":"https://doi.org/10.1145/3511299","url":null,"abstract":"The emergence of machine learning as a society-changing technology in the past decade has triggered concerns about people's inability to understand the reasoning of increasingly complex models. The field of IML (interpretable machine learning) grew out of these concerns, with the goal of empowering various stakeholders to tackle use cases, such as building trust in models, performing model debugging, and generally informing real human decision-making.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"46 8","pages":"28 - 56"},"PeriodicalIF":0.0,"publicationDate":"2021-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41248287","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}
When you look at a function program's source code, how do you know what it means? Is the meaning found in the return values of the function, or is it located inside the function body? What about the function name? Answering these questions is important to understanding how to share domain knowledge among programmers using the source code as the medium. The program is the medium of communication among programmers to share their solutions.
{"title":"Meaning and Context in Computer Programs","authors":"A. Videla","doi":"10.1145/3494834.3498852","DOIUrl":"https://doi.org/10.1145/3494834.3498852","url":null,"abstract":"When you look at a function program's source code, how do you know what it means? Is the meaning found in the return values of the function, or is it located inside the function body? What about the function name? Answering these questions is important to understanding how to share domain knowledge among programmers using the source code as the medium. The program is the medium of communication among programmers to share their solutions.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"19 1","pages":"60 - 68"},"PeriodicalIF":0.0,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43044174","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}
Reynold Xin, Wes McKinney, Alan Gates, Chris McCubbin
Of the many challenges faced by open-source developers, among the most daunting are some that other programmers scarcely ever think about. Building a successful open-source community depends on many different elements, some of which are familiar to any developer. Just as important are the skills to recruit, to inspire, to mentor, to manage, and to mediate disputes. But what exactly does it take to pull all that off?
{"title":"It Takes a Community","authors":"Reynold Xin, Wes McKinney, Alan Gates, Chris McCubbin","doi":"10.1145/3494834.3498568","DOIUrl":"https://doi.org/10.1145/3494834.3498568","url":null,"abstract":"Of the many challenges faced by open-source developers, among the most daunting are some that other programmers scarcely ever think about. Building a successful open-source community depends on many different elements, some of which are familiar to any developer. Just as important are the skills to recruit, to inspire, to mentor, to manage, and to mediate disputes. But what exactly does it take to pull all that off?","PeriodicalId":39042,"journal":{"name":"Queue","volume":"19 1","pages":"115 - 136"},"PeriodicalIF":0.0,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44048711","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}
Kallista A. Bonawitz, P. Kairouz, H. B. McMahan, Daniel Ramage
Centralized data collection can expose individuals to privacy risks and organizations to legal risks if data is not properly managed. Federated learning is a machine learning setting where multiple entities collaborate in solving a machine learning problem, under the coordination of a central server or service provider. Each client's raw data is stored locally and not exchanged or transferred; instead, focused updates intended for immediate aggregation are used to achieve the learning objective. This article provides a brief introduction to key concepts in federated learning and analytics with an emphasis on how privacy technologies may be combined in real-world systems and how their use charts a path toward societal benefit from aggregate statistics in new domains and with minimized risk to individuals and to the organizations who are custodians of the data.
{"title":"Federated Learning and Privacy","authors":"Kallista A. Bonawitz, P. Kairouz, H. B. McMahan, Daniel Ramage","doi":"10.1145/3494834.3500240","DOIUrl":"https://doi.org/10.1145/3494834.3500240","url":null,"abstract":"Centralized data collection can expose individuals to privacy risks and organizations to legal risks if data is not properly managed. Federated learning is a machine learning setting where multiple entities collaborate in solving a machine learning problem, under the coordination of a central server or service provider. Each client's raw data is stored locally and not exchanged or transferred; instead, focused updates intended for immediate aggregation are used to achieve the learning objective. This article provides a brief introduction to key concepts in federated learning and analytics with an emphasis on how privacy technologies may be combined in real-world systems and how their use charts a path toward societal benefit from aggregate statistics in new domains and with minimized risk to individuals and to the organizations who are custodians of the data.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"19 1","pages":"87 - 114"},"PeriodicalIF":0.0,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48111161","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}
Kirk McKusick sat down with Margo Seltzer and Mike Olson to discuss the history of Berkeley DB, for which they won the ACM Software System Award in 2021. Kirk McKusick has spent his career as a BSD and FreeBSD developer. Margo Seltzer has spent her career as a professor of computer science and as an entrepreneur of database software companies. Mike Olson started his career as a software developer and later started and managed several open-source software companies. Berkeley DB is a production-quality, scalable, NoSQL, Open Source platform for embedded transactional data management.
{"title":"A Conversation with Margo Seltzer and Mike Olson","authors":"M. Seltzer, Mike Olson, Kirk McCusick","doi":"10.1145/3494834.3498582","DOIUrl":"https://doi.org/10.1145/3494834.3498582","url":null,"abstract":"Kirk McKusick sat down with Margo Seltzer and Mike Olson to discuss the history of Berkeley DB, for which they won the ACM Software System Award in 2021. Kirk McKusick has spent his career as a BSD and FreeBSD developer. Margo Seltzer has spent her career as a professor of computer science and as an entrepreneur of database software companies. Mike Olson started his career as a software developer and later started and managed several open-source software companies. Berkeley DB is a production-quality, scalable, NoSQL, Open Source platform for embedded transactional data management.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"19 1","pages":"69 - 86"},"PeriodicalIF":0.0,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48593579","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}
Dear Popcorn, Some people would say that it’s unfair to pick on any company after such a spectacular failure, and that it’s not nice to kick people, or companies, when they’re down. KV, of course, is not one of those people. Like the rest of the world, I watched in amusement as one of the wealthiest companies on earth seemingly shot itself in the foot with a configuration error. Some watched in horror, and yes, KV watched in amusement. It goes without saying that I know only what I’ve read in the news and on various “feeds,” but some of the failure seems fairly well externally documented. The lessons here are broader than just a simple “Don’t do that,” and there are numerous examples of companies doing similar things to themselves before this most recent incident. The real root cause that made this all so catastrophic isn’t just the pushing of a bad configuration; I Unplugged What?
{"title":"I Unplugged What?","authors":"George Neville-Neil","doi":"10.1145/3494834.3498576","DOIUrl":"https://doi.org/10.1145/3494834.3498576","url":null,"abstract":"Dear Popcorn, Some people would say that it’s unfair to pick on any company after such a spectacular failure, and that it’s not nice to kick people, or companies, when they’re down. KV, of course, is not one of those people. Like the rest of the world, I watched in amusement as one of the wealthiest companies on earth seemingly shot itself in the foot with a configuration error. Some watched in horror, and yes, KV watched in amusement. It goes without saying that I know only what I’ve read in the news and on various “feeds,” but some of the failure seems fairly well externally documented. The lessons here are broader than just a simple “Don’t do that,” and there are numerous examples of companies doing similar things to themselves before this most recent incident. The real root cause that made this all so catastrophic isn’t just the pushing of a bad configuration; I Unplugged What?","PeriodicalId":39042,"journal":{"name":"Queue","volume":"19 1","pages":"1 - 4"},"PeriodicalIF":0.0,"publicationDate":"2021-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44985621","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 main reason a lawyer will give for not reading a software patent is that, if you run afoul of the patent and it can be shown that you had knowledge of it, your company will incur triple the damages that they would have, had you not had knowledge of the patent. That seems like reason enough to avoid reading them, but there is an even better reason, and that is, as design or technical documents, software patents suck.
{"title":"Patent Absurdity","authors":"","doi":"10.1145/3487019.3489047","DOIUrl":"https://doi.org/10.1145/3487019.3489047","url":null,"abstract":"The main reason a lawyer will give for not reading a software patent is that, if you run afoul of the patent and it can be shown that you had knowledge of it, your company will incur triple the damages that they would have, had you not had knowledge of the patent. That seems like reason enough to avoid reading them, but there is an even better reason, and that is, as design or technical documents, software patents suck.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"19 1","pages":"19 - 22"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43187777","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 time is way overdue for IT engineers to be subject to professional liability, like almost every other engineering profession. Before you tell me that is impossible, please study how the very same thing happened with electricity, planes, cranes, trains, ships, automobiles, lifts, food processing, buildings, and, for that matter, driving a car.
{"title":"The Software Industry IS STILL the Problem","authors":"Poul-Henning Kamp","doi":"10.1145/3487019.3489045","DOIUrl":"https://doi.org/10.1145/3487019.3489045","url":null,"abstract":"The time is way overdue for IT engineers to be subject to professional liability, like almost every other engineering profession. Before you tell me that is impossible, please study how the very same thing happened with electricity, planes, cranes, trains, ships, automobiles, lifts, food processing, buildings, and, for that matter, driving a car.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"19 1","pages":"23 - 28"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43384220","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}
Static-analysis tools suffer from usability issues such as a high rate of false positives, lack of responsiveness, and unclear warning descriptions and classifications. Here, we explore the effect of applying user-centered approach and design guidelines to SWAN, a security-focused static-analysis tool for the Swift programming language. SWAN is an interesting case study for exploring static-analysis tool usability because of its large target audience, its potential to integrate easily into developers' workflows, and its independence from existing analysis platforms.
{"title":"Designing UIs for Static Analysis Tools","authors":"Daniil Tiganov, Lisa Nguyen Quang Do, Karim Ali","doi":"10.1145/3487019.3487026","DOIUrl":"https://doi.org/10.1145/3487019.3487026","url":null,"abstract":"Static-analysis tools suffer from usability issues such as a high rate of false positives, lack of responsiveness, and unclear warning descriptions and classifications. Here, we explore the effect of applying user-centered approach and design guidelines to SWAN, a security-focused static-analysis tool for the Swift programming language. SWAN is an interesting case study for exploring static-analysis tool usability because of its large target audience, its potential to integrate easily into developers' workflows, and its independence from existing analysis platforms.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"19 1","pages":"97 - 118"},"PeriodicalIF":0.0,"publicationDate":"2021-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48566808","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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