Wherever possible, business logic should be described by code rather than training data. This keeps our system's behavior principled, predictable, and easy to change. Our approach to conversational interfaces allows them to be built much like any other application, using familiar tools, conventions, and processes, while still taking advantage of cutting-edge machine-learning techniques.
{"title":"Designing a Framework for Conversational Interfaces","authors":"Zachary Tellman","doi":"10.1145/3587715","DOIUrl":"https://doi.org/10.1145/3587715","url":null,"abstract":"Wherever possible, business logic should be described by code rather than training data. This keeps our system's behavior principled, predictable, and easy to change. Our approach to conversational interfaces allows them to be built much like any other application, using familiar tools, conventions, and processes, while still taking advantage of cutting-edge machine-learning techniques.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"21 1","pages":"85 - 101"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42966250","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 greater the risk, the greater the reward, and if you do succeed, it will be an achievement that you can look back on and smile wryly about. Postdocs never laugh because postdocs are post-laughter. However, there are some things to consider before plunking down your application fee and writing all those essays.
{"title":"The Parchment Path?","authors":"George Neville-Neil","doi":"10.1145/3587482","DOIUrl":"https://doi.org/10.1145/3587482","url":null,"abstract":"The greater the risk, the greater the reward, and if you do succeed, it will be an achievement that you can look back on and smile wryly about. Postdocs never laugh because postdocs are post-laughter. However, there are some things to consider before plunking down your application fee and writing all those essays.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"21 1","pages":"5 - 11"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48262261","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}
C. Bird, Denae Ford, Thomas Zimmermann, Nicole Forsgren, Eirini Kalliamvakou, Travis Lowdermilk, Idan Gazit
Over the next five years, AI-powered tools likely will be helping developers in many diverse tasks. For example, such models may be used to improve code review, directing reviewers to parts of a change where review is most needed or even directly providing feedback on changes. Models such as Codex may suggest fixes for defects in code, build failures, or failing tests. These models are able to write tests automatically, helping to improve code quality and downstream reliability of distributed systems. This study of Copilot shows that developers spend more time reviewing code than actually writing code. As AI-powered tools are integrated into more software development tasks, developer roles will shift so that more time is spent assessing suggestions related to the task than doing the task itself.
{"title":"Taking Flight with Copilot","authors":"C. Bird, Denae Ford, Thomas Zimmermann, Nicole Forsgren, Eirini Kalliamvakou, Travis Lowdermilk, Idan Gazit","doi":"10.1145/3582083","DOIUrl":"https://doi.org/10.1145/3582083","url":null,"abstract":"Over the next five years, AI-powered tools likely will be helping developers in many diverse tasks. For example, such models may be used to improve code review, directing reviewers to parts of a change where review is most needed or even directly providing feedback on changes. Models such as Codex may suggest fixes for defects in code, build failures, or failing tests. These models are able to write tests automatically, helping to improve code quality and downstream reliability of distributed systems. This study of Copilot shows that developers spend more time reviewing code than actually writing code. As AI-powered tools are integrated into more software development tasks, developer roles will shift so that more time is spent assessing suggestions related to the task than doing the task itself.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"20 1","pages":"35 - 57"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47976995","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}
Stefan Nagy, an assistant professor in the Kahlert School of Computing at the University of Utah, takes us on a tour of recent research in software fuzzing, or the systematic testing of programs via the generation of novel or unexpected inputs. The first paper he discusses extends the state of the art in coverage-guided fuzzing with the semantic notion of "likely invariants," inferred via techniques from property-based testing. The second explores encoding domain-specific knowledge about certain bug classes into test-case generation. His last selection takes us through the looking glass, randomly generating entire C programs and using differential analysis to compare traces of optimized and unoptimized executions, in order to find bugs in the compilers themselves.
{"title":"The Fun in Fuzzing","authors":"Stefan Nagy, P. Alvaro","doi":"10.1145/3580504","DOIUrl":"https://doi.org/10.1145/3580504","url":null,"abstract":"Stefan Nagy, an assistant professor in the Kahlert School of Computing at the University of Utah, takes us on a tour of recent research in software fuzzing, or the systematic testing of programs via the generation of novel or unexpected inputs. The first paper he discusses extends the state of the art in coverage-guided fuzzing with the semantic notion of \"likely invariants,\" inferred via techniques from property-based testing. The second explores encoding domain-specific knowledge about certain bug classes into test-case generation. His last selection takes us through the looking glass, randomly generating entire C programs and using differential analysis to compare traces of optimized and unoptimized executions, in order to find bugs in the compilers themselves.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"20 1","pages":"80 - 87"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42220812","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 article examines three tools in the system acquisitions toolbox that can work to expedite development and procurement while mitigating programmatic risk: OSS, open standards, and the Agile/Scrum software development processes are all powerful additions to the DoD acquisition program management toolbox.
{"title":"Three-part Harmony for Program Managers Who Just Don't Get It, Yet","authors":"Guenever Aldrich, Danny Tsang, J. McKenney","doi":"10.1145/3576027","DOIUrl":"https://doi.org/10.1145/3576027","url":null,"abstract":"This article examines three tools in the system acquisitions toolbox that can work to expedite development and procurement while mitigating programmatic risk: OSS, open standards, and the Agile/Scrum software development processes are all powerful additions to the DoD acquisition program management toolbox.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"20 1","pages":"58 - 79"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48206518","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}
There are many reasons why this year's model isn't any better than last year's, and many reasons why performance fails to scale, some of which KV has covered in these pages. It is true that the days of upgrading every year and getting a free performance boost are long gone, as we're not really getting single cores that are faster than about 4GHz. One thing that many software developers fail to understand is the hardware on which their software runs at a sufficiently deep level.
{"title":"All Sliders to the Right","authors":"George Neville-Neil","doi":"10.1145/3580505","DOIUrl":"https://doi.org/10.1145/3580505","url":null,"abstract":"There are many reasons why this year's model isn't any better than last year's, and many reasons why performance fails to scale, some of which KV has covered in these pages. It is true that the days of upgrading every year and getting a free performance boost are long gone, as we're not really getting single cores that are faster than about 4GHz. One thing that many software developers fail to understand is the hardware on which their software runs at a sufficiently deep level.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"20 1","pages":"4 - 8"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47521157","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}
As artificial intelligence becomes a pervasive tool for the billions of IoT (Internet of things) devices at the edge, the data movement bottleneck imposes severe limitations on the performance and autonomy of these systems. PiM (processing-in-memory) is emerging as a way of mitigating the data movement bottleneck while satisfying the stringent performance, energy efficiency, and accuracy requirements of edge imaging applications that rely on CNNs (convolutional neural networks).
{"title":"To PiM or Not to PiM","authors":"Gabriel Falcao, João Dinis Ferreira","doi":"10.1145/3580503","DOIUrl":"https://doi.org/10.1145/3580503","url":null,"abstract":"As artificial intelligence becomes a pervasive tool for the billions of IoT (Internet of things) devices at the edge, the data movement bottleneck imposes severe limitations on the performance and autonomy of these systems. PiM (processing-in-memory) is emerging as a way of mitigating the data movement bottleneck while satisfying the stringent performance, energy efficiency, and accuracy requirements of edge imaging applications that rely on CNNs (convolutional neural networks).","PeriodicalId":39042,"journal":{"name":"Queue","volume":"20 1","pages":"9 - 34"},"PeriodicalIF":0.0,"publicationDate":"2022-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47547902","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}
OCCAM-v2 leverages scalable pointer analysis, value analysis, and dynamic analysis to create an effective and efficient tool for specializing LLVM bitcode. The extent of the code-size reduction achieved depends on the specific deployment configuration. Each application that is to be specialized is accompanied by a manifest that specifies concrete arguments that are known a priori, as well as a count of residual arguments that will be provided at runtime. The best case for partial evaluation occurs when the arguments are completely concretely specified. OCCAM-v2 uses a pointer analysis to devirtualize calls, allowing it to eliminate the entire body of functions that are not reachable by any direct calls. The hybrid analysis feature can handle cases that are challenging for static analysis, such as input loops, string processing, and external data (in files, for example). On the suite of evaluated programs, OCCAM-v2 was able to reduce the instruction count by 40.6 percent on average, taking a median of 2.4 seconds.
{"title":"OCCAM-v2: Combining Static and Dynamic Analysis for Effective and Efficient Whole-program Specialization","authors":"J. Navas, Ashish Gehani","doi":"10.1145/3570922","DOIUrl":"https://doi.org/10.1145/3570922","url":null,"abstract":"OCCAM-v2 leverages scalable pointer analysis, value analysis, and dynamic analysis to create an effective and efficient tool for specializing LLVM bitcode. The extent of the code-size reduction achieved depends on the specific deployment configuration. Each application that is to be specialized is accompanied by a manifest that specifies concrete arguments that are known a priori, as well as a count of residual arguments that will be provided at runtime. The best case for partial evaluation occurs when the arguments are completely concretely specified. OCCAM-v2 uses a pointer analysis to devirtualize calls, allowing it to eliminate the entire body of functions that are not reachable by any direct calls. The hybrid analysis feature can handle cases that are challenging for static analysis, such as input loops, string processing, and external data (in files, for example). On the suite of evaluated programs, OCCAM-v2 was able to reduce the instruction count by 40.6 percent on average, taking a median of 2.4 seconds.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"20 1","pages":"58 - 85"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45432178","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}
Maya Kaczorowski, Falcon Momot, George Neville-Neil, Chris McCubbin
While enterprise security teams naturally tend to turn their focus primarily to direct attacks on their own infrastructure, cybercrime exploits now are increasingly aimed at easier targets upstream. This has led to a perfect storm, since virtually all significant codebase repositories at this point include at least some amount of open-source software. But opportunities also abound there for the authors of malware. The broader cybercrime world, meanwhile, has noted that open-source supply chains are generally easy to penetrate. What's being done at this point to address the apparent risks?
{"title":"OSS Supply-chain Security: What Will It Take?","authors":"Maya Kaczorowski, Falcon Momot, George Neville-Neil, Chris McCubbin","doi":"10.1145/3570923","DOIUrl":"https://doi.org/10.1145/3570923","url":null,"abstract":"While enterprise security teams naturally tend to turn their focus primarily to direct attacks on their own infrastructure, cybercrime exploits now are increasingly aimed at easier targets upstream. This has led to a perfect storm, since virtually all significant codebase repositories at this point include at least some amount of open-source software. But opportunities also abound there for the authors of malware. The broader cybercrime world, meanwhile, has noted that open-source supply chains are generally easy to penetrate. What's being done at this point to address the apparent risks?","PeriodicalId":39042,"journal":{"name":"Queue","volume":"20 1","pages":"86 - 102"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41623652","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}
Literate executables redefine the relationship between compiled binaries and source code to be that of chicken and egg, so it's easy to derive either from the other. This episode of Drill Bits provides a general-purpose literacy tool and showcases the advantages of literacy by retrofitting it onto everyone's favorite command-line utility.
{"title":"Literate Executables","authors":"Terence Kelly","doi":"10.1145/3570938","DOIUrl":"https://doi.org/10.1145/3570938","url":null,"abstract":"Literate executables redefine the relationship between compiled binaries and source code to be that of chicken and egg, so it's easy to derive either from the other. This episode of Drill Bits provides a general-purpose literacy tool and showcases the advantages of literacy by retrofitting it onto everyone's favorite command-line utility.","PeriodicalId":39042,"journal":{"name":"Queue","volume":"20 1","pages":"20 - 32"},"PeriodicalIF":0.0,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49650179","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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