Soyeon Park, Yuanyuan Zhou, Weiwei Xiong, Zuoning Yin, Rini T. Kaushik, Kyuhyung Lee, Shan Lu
Bug reproduction is critically important for diagnosing a production-run failure. Unfortunately, reproducing a concurrency bug on multi-processors (e.g., multi-core) is challenging. Previous techniques either incur large overhead or require new non-trivial hardware extensions. This paper proposes a novel technique called PRES (probabilistic replay via execution sketching) to help reproduce concurrency bugs on multi-processors. It relaxes the past (perhaps idealistic) objective of "reproducing the bug on the first replay attempt" to significantly lower production-run recording overhead. This is achieved by (1) recording only partial execution information (referred to as "sketches") during the production run, and (2) relying on an intelligent replayer during diagnosis time (when performance is less critical) to systematically explore the unrecorded non-deterministic space and reproduce the bug. With only partial information, our replayer may require more than one coordinated replay run to reproduce a bug. However, after a bug is reproduced once, PRES can reproduce it every time. We implemented PRES along with five different execution sketching mechanisms. We evaluated them with 11 representative applications, including 4 servers, 3 desktop/client applications, and 4 scientific/graphics applications, with 13 real-world concurrency bugs of different types, including atomicity violations, order violations and deadlocks. PRES (with synchronization or system call sketching) significantly lowered the production-run recording overhead of previous approaches (by up to 4416 times), while still reproducing most tested bugs in fewer than 10 replay attempts. Moreover, PRES scaled well with the number of processors; PRES's feedback generation from unsuccessful replays is critical in bug reproduction.
{"title":"PRES: probabilistic replay with execution sketching on multiprocessors","authors":"Soyeon Park, Yuanyuan Zhou, Weiwei Xiong, Zuoning Yin, Rini T. Kaushik, Kyuhyung Lee, Shan Lu","doi":"10.1145/1629575.1629593","DOIUrl":"https://doi.org/10.1145/1629575.1629593","url":null,"abstract":"Bug reproduction is critically important for diagnosing a production-run failure. Unfortunately, reproducing a concurrency bug on multi-processors (e.g., multi-core) is challenging. Previous techniques either incur large overhead or require new non-trivial hardware extensions.\u0000 This paper proposes a novel technique called PRES (probabilistic replay via execution sketching) to help reproduce concurrency bugs on multi-processors. It relaxes the past (perhaps idealistic) objective of \"reproducing the bug on the first replay attempt\" to significantly lower production-run recording overhead. This is achieved by (1) recording only partial execution information (referred to as \"sketches\") during the production run, and (2) relying on an intelligent replayer during diagnosis time (when performance is less critical) to systematically explore the unrecorded non-deterministic space and reproduce the bug. With only partial information, our replayer may require more than one coordinated replay run to reproduce a bug. However, after a bug is reproduced once, PRES can reproduce it every time.\u0000 We implemented PRES along with five different execution sketching mechanisms. We evaluated them with 11 representative applications, including 4 servers, 3 desktop/client applications, and 4 scientific/graphics applications, with 13 real-world concurrency bugs of different types, including atomicity violations, order violations and deadlocks. PRES (with synchronization or system call sketching) significantly lowered the production-run recording overhead of previous approaches (by up to 4416 times), while still reproducing most tested bugs in fewer than 10 replay attempts. Moreover, PRES scaled well with the number of processors; PRES's feedback generation from unsuccessful replays is critical in bug reproduction.","PeriodicalId":20672,"journal":{"name":"Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86625477","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}
Jed Liu, Michael D. George, K. Vikram, Xin Qi, Lucas Waye, A. Myers
Fabric is a new system and language for building secure distributed information systems. It is a decentralized system that allows heterogeneous network nodes to securely share both information and computation resources despite mutual distrust. Its high-level programming language makes distribution and persistence largely transparent to programmers. Fabric supports data-shipping and function-shipping styles of computation: both computation and information can move between nodes to meet security requirements or to improve performance. Fabric provides a rich, Java-like object model, but data resources are labeled with confidentiality and integrity policies that are enforced through a combination of compile-time and run-time mechanisms. Optimistic, nested transactions ensure consistency across all objects and nodes. A peer-to-peer dissemination layer helps to increase availability and to balance load. Results from applications built using Fabric suggest that Fabric has a clean, concise programming model, offers good performance, and enforces security.
{"title":"Fabric: a platform for secure distributed computation and storage","authors":"Jed Liu, Michael D. George, K. Vikram, Xin Qi, Lucas Waye, A. Myers","doi":"10.1145/1629575.1629606","DOIUrl":"https://doi.org/10.1145/1629575.1629606","url":null,"abstract":"Fabric is a new system and language for building secure distributed information systems. It is a decentralized system that allows heterogeneous network nodes to securely share both information and computation resources despite mutual distrust. Its high-level programming language makes distribution and persistence largely transparent to programmers. Fabric supports data-shipping and function-shipping styles of computation: both computation and information can move between nodes to meet security requirements or to improve performance. Fabric provides a rich, Java-like object model, but data resources are labeled with confidentiality and integrity policies that are enforced through a combination of compile-time and run-time mechanisms. Optimistic, nested transactions ensure consistency across all objects and nodes. A peer-to-peer dissemination layer helps to increase availability and to balance load. Results from applications built using Fabric suggest that Fabric has a clean, concise programming model, offers good performance, and enforces security.","PeriodicalId":20672,"journal":{"name":"Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84271838","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}
Giuseppe deCandia, Deniz Hastorun, M. Jampani, Gunavardhan Kakulapati, A. Lakshman, A. Pilchin, S. Sivasubramanian, Peter Vosshall, W. Vogels
Reliability at massive scale is one of the biggest challenges we face at Amazon.com, one of the largest e-commerce operations in the world; even the slightest outage has significant financial consequences and impacts customer trust. The Amazon.com platform, which provides services for many web sites worldwide, is implemented on top of an infrastructure of tens of thousands of servers and network components located in many datacenters around the world. At this scale, small and large components fail continuously and the way persistent state is managed in the face of these failures drives the reliability and scalability of the software systems. This paper presents the design and implementation of Dynamo, a highly available key-value storage system that some of Amazon's core services use to provide an "always-on" experience. To achieve this level of availability, Dynamo sacrifices consistency under certain failure scenarios. It makes extensive use of object versioning and application-assisted conflict resolution in a manner that provides a novel interface for developers to use.
{"title":"Dynamo: amazon's highly available key-value store","authors":"Giuseppe deCandia, Deniz Hastorun, M. Jampani, Gunavardhan Kakulapati, A. Lakshman, A. Pilchin, S. Sivasubramanian, Peter Vosshall, W. Vogels","doi":"10.1145/1294261.1294281","DOIUrl":"https://doi.org/10.1145/1294261.1294281","url":null,"abstract":"Reliability at massive scale is one of the biggest challenges we face at Amazon.com, one of the largest e-commerce operations in the world; even the slightest outage has significant financial consequences and impacts customer trust. The Amazon.com platform, which provides services for many web sites worldwide, is implemented on top of an infrastructure of tens of thousands of servers and network components located in many datacenters around the world. At this scale, small and large components fail continuously and the way persistent state is managed in the face of these failures drives the reliability and scalability of the software systems.\u0000 This paper presents the design and implementation of Dynamo, a highly available key-value storage system that some of Amazon's core services use to provide an \"always-on\" experience. To achieve this level of availability, Dynamo sacrifices consistency under certain failure scenarios. It makes extensive use of object versioning and application-assisted conflict resolution in a manner that provides a novel interface for developers to use.","PeriodicalId":20672,"journal":{"name":"Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90666547","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}
Shan Lu, Soyeon Park, Chongfeng Hu, Xiao Ma, Weihang Jiang, Zhenmin Li, R. A. Popa, Yuanyuan Zhou
Software defects significantly reduce system dependability. Among various types of software bugs, semantic and concurrency bugs are two of the most difficult to detect. This paper proposes a novel method, called MUVI, that detects an important class of semantic and concurrency bugs. MUVI automatically infers commonly existing multi-variable access correlations through code analysis and then detects two types of related bugs: (1) inconsistent updates--correlated variables are not updated in a consistent way, and (2) multi-variable concurrency bugs--correlated accesses are not protected in the same atomic sections in concurrent programs.We evaluate MUVI on four large applications: Linux, Mozilla,MySQL, and PostgreSQL. MUVI automatically infers more than 6000 variable access correlations with high accuracy (83%).Based on the inferred correlations, MUVI detects 39 new inconsistent update semantic bugs from the latest versions of these applications, with 17 of them recently confirmed by the developers based on our reports.We also implemented MUVI multi-variable extensions to tworepresentative data race bug detection methods (lock-set and happens-before). Our evaluation on five real-world multi-variable concurrency bugs from Mozilla and MySQL shows that the MUVI-extension correctly identifies the root causes of four out of the five multi-variable concurrency bugs with 14% additional overhead on average. Interestingly, MUVI also helps detect four new multi-variable concurrency bugs in Mozilla that have never been reported before. None of the nine bugs can be identified correctly by the original race detectors without our MUVI extensions.
{"title":"MUVI: automatically inferring multi-variable access correlations and detecting related semantic and concurrency bugs","authors":"Shan Lu, Soyeon Park, Chongfeng Hu, Xiao Ma, Weihang Jiang, Zhenmin Li, R. A. Popa, Yuanyuan Zhou","doi":"10.1145/1294261.1294272","DOIUrl":"https://doi.org/10.1145/1294261.1294272","url":null,"abstract":"Software defects significantly reduce system dependability. Among various types of software bugs, semantic and concurrency bugs are two of the most difficult to detect. This paper proposes a novel method, called MUVI, that detects an important class of semantic and concurrency bugs. MUVI automatically infers commonly existing multi-variable access correlations through code analysis and then detects two types of related bugs: (1) inconsistent updates--correlated variables are not updated in a consistent way, and (2) multi-variable concurrency bugs--correlated accesses are not protected in the same atomic sections in concurrent programs.We evaluate MUVI on four large applications: Linux, Mozilla,MySQL, and PostgreSQL. MUVI automatically infers more than 6000 variable access correlations with high accuracy (83%).Based on the inferred correlations, MUVI detects 39 new inconsistent update semantic bugs from the latest versions of these applications, with 17 of them recently confirmed by the developers based on our reports.We also implemented MUVI multi-variable extensions to tworepresentative data race bug detection methods (lock-set and happens-before). Our evaluation on five real-world multi-variable concurrency bugs from Mozilla and MySQL shows that the MUVI-extension correctly identifies the root causes of four out of the five multi-variable concurrency bugs with 14% additional overhead on average. Interestingly, MUVI also helps detect four new multi-variable concurrency bugs in Mozilla that have never been reported before. None of the nine bugs can be identified correctly by the original race detectors without our MUVI extensions.","PeriodicalId":20672,"journal":{"name":"Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89549943","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}
M. Aguilera, A. Merchant, Mehul A. Shah, Alistair C. Veitch, C. Karamanolis
We propose a new paradigm for building scalable distributed systems. Our approach does not require dealing with message-passing protocols -- a major complication in existing distributed systems. Instead, developers just design and manipulate data structures within our service called Sinfonia. Sinfonia keeps data for applications on a set of memory nodes, each exporting a linear address space. At the core of Sinfonia is a novel minitransaction primitive that enables efficient and consistent access to data, while hiding the complexities that arise from concurrency and failures. Using Sinfonia, we implemented two very different and complex applications in a few months: a cluster file system and a group communication service. Our implementations perform well and scale to hundreds of machines.
{"title":"Sinfonia: a new paradigm for building scalable distributed systems","authors":"M. Aguilera, A. Merchant, Mehul A. Shah, Alistair C. Veitch, C. Karamanolis","doi":"10.1145/1294261.1294278","DOIUrl":"https://doi.org/10.1145/1294261.1294278","url":null,"abstract":"We propose a new paradigm for building scalable distributed systems. Our approach does not require dealing with message-passing protocols -- a major complication in existing distributed systems. Instead, developers just design and manipulate data structures within our service called Sinfonia. Sinfonia keeps data for applications on a set of memory nodes, each exporting a linear address space. At the core of Sinfonia is a novel minitransaction primitive that enables efficient and consistent access to data, while hiding the complexities that arise from concurrency and failures. Using Sinfonia, we implemented two very different and complex applications in a few months: a cluster file system and a group communication service. Our implementations perform well and scale to hundreds of machines.","PeriodicalId":20672,"journal":{"name":"Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91216566","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}
Haryadi S. Gunawi, Vijayan Prabhakaran, S. Krishnan, A. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau
We introduce a new reliability infrastructure for file systems called I/O shepherding. I/O shepherding allows a file system developer to craft nuanced reliability policies to detect and recover from a wide range of storage system failures. We incorporate shepherding into the Linux ext3 file system through a set of changes to the consistency management subsystem, layout engine, disk scheduler, and buffer cache. The resulting file system, CrookFS, enables a broad class of policies to be easily and correctly specified. We implement numerous policies, incorporating data protection techniques such as retry, parity, mirrors, checksums, sanity checks, and data structure repairs; even complex policies can be implemented in less than 100 lines of code, confirming the power and simplicity of the shepherding framework. We also demonstrate that shepherding is properly integrated, adding less than 5% overhead to the I/O path.
{"title":"Improving file system reliability with I/O shepherding","authors":"Haryadi S. Gunawi, Vijayan Prabhakaran, S. Krishnan, A. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau","doi":"10.1145/1294261.1294290","DOIUrl":"https://doi.org/10.1145/1294261.1294290","url":null,"abstract":"We introduce a new reliability infrastructure for file systems called I/O shepherding. I/O shepherding allows a file system developer to craft nuanced reliability policies to detect and recover from a wide range of storage system failures. We incorporate shepherding into the Linux ext3 file system through a set of changes to the consistency management subsystem, layout engine, disk scheduler, and buffer cache. The resulting file system, CrookFS, enables a broad class of policies to be easily and correctly specified. We implement numerous policies, incorporating data protection techniques such as retry, parity, mirrors, checksums, sanity checks, and data structure repairs; even complex policies can be implemented in less than 100 lines of code, confirming the power and simplicity of the shepherding framework. We also demonstrate that shepherding is properly integrated, adding less than 5% overhead to the I/O path.","PeriodicalId":20672,"journal":{"name":"Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85339609","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}
Stephen Chong, Jed Liu, A. Myers, Xin Qi, K. Vikram, Lantian Zheng, Xin Zheng
Swift is a new, principled approach to building web applications that are secure by construction. In modern web applications, some application functionality is usually implemented as client-side code written in JavaScript. Moving code and data to the client can create security vulnerabilities, but currently there are no good methods for deciding when it is secure to do so. Swift automatically partitions application code while providing assurance that the resulting placement is secure and efficient. Application code is written as Java-like code annotated with information flow policies that specify the confidentiality and integrity of web application information. The compiler uses these policies to automatically partition the program into JavaScript code running in the browser, and Java code running on the server. To improve interactive performance, code and data are placed on the client side. However, security-critical code and data are always placed on the server. Code and data can also be replicated across the client and server, to obtain both security and performance. A max-flow algorithm is used to place code and data in a way that minimizes client-server communication.
{"title":"Secure web applications via automatic partitioning","authors":"Stephen Chong, Jed Liu, A. Myers, Xin Qi, K. Vikram, Lantian Zheng, Xin Zheng","doi":"10.1145/1294261.1294265","DOIUrl":"https://doi.org/10.1145/1294261.1294265","url":null,"abstract":"Swift is a new, principled approach to building web applications that are secure by construction. In modern web applications, some application functionality is usually implemented as client-side code written in JavaScript. Moving code and data to the client can create security vulnerabilities, but currently there are no good methods for deciding when it is secure to do so. Swift automatically partitions application code while providing assurance that the resulting placement is secure and efficient. Application code is written as Java-like code annotated with information flow policies that specify the confidentiality and integrity of web application information. The compiler uses these policies to automatically partition the program into JavaScript code running in the browser, and Java code running on the server. To improve interactive performance, code and data are placed on the client side. However, security-critical code and data are always placed on the server. Code and data can also be replicated across the client and server, to obtain both security and performance. A max-flow algorithm is used to place code and data in a way that minimizes client-server communication.","PeriodicalId":20672,"journal":{"name":"Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89470867","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. Rossbach, O. S. Hofmann, Donald E. Porter, Hany E. Ramadan, Bhandari Aditya, E. Witchel
TxLinux is a variant of Linux that is the first operating system to use hardware transactional memory (HTM) as a synchronization primitive, and the first to manage HTM in the scheduler. This paper describes and measures TxLinux and discusses two innovations in detail: cooperation between locks and transactions, and theintegration of transactions with the OS scheduler. Mixing locks and transactions requires a new primitive, cooperative transactional spinlocks (cxspinlocks) that allow locks and transactions to protect the same data while maintaining the advantages of both synchronization primitives. Cxspinlocks allow the system to attemptexecution of critical regions with transactions and automatically roll back to use locking if the region performs I/O. Integrating the scheduler with HTM eliminates priority inversion. On a series ofreal-world benchmarks TxLinux has similar performance to Linux, exposing concurrency with as many as 32 concurrent threads on 32 CPUs in the same critical region.
{"title":"TxLinux: using and managing hardware transactional memory in an operating system","authors":"C. Rossbach, O. S. Hofmann, Donald E. Porter, Hany E. Ramadan, Bhandari Aditya, E. Witchel","doi":"10.1145/1294261.1294271","DOIUrl":"https://doi.org/10.1145/1294261.1294271","url":null,"abstract":"TxLinux is a variant of Linux that is the first operating system to use hardware transactional memory (HTM) as a synchronization primitive, and the first to manage HTM in the scheduler. This paper describes and measures TxLinux and discusses two innovations in detail: cooperation between locks and transactions, and theintegration of transactions with the OS scheduler. Mixing locks and transactions requires a new primitive, cooperative transactional spinlocks (cxspinlocks) that allow locks and transactions to protect the same data while maintaining the advantages of both synchronization primitives. Cxspinlocks allow the system to attemptexecution of critical regions with transactions and automatically roll back to use locking if the region performs I/O. Integrating the scheduler with HTM eliminates priority inversion. On a series ofreal-world benchmarks TxLinux has similar performance to Linux, exposing concurrency with as many as 32 concurrent threads on 32 CPUs in the same critical region.","PeriodicalId":20672,"journal":{"name":"Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74513706","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}
Byung-Gon Chun, Petros Maniatis, S. Shenker, J. Kubiatowicz
Researchers have made great strides in improving the fault tolerance of both centralized and replicated systems against arbitrary (Byzantine) faults. However, there are hard limits to how much can be done with entirely untrusted components; for example, replicated state machines cannot tolerate more than a third of their replica population being Byzantine. In this paper, we investigate how minimal trusted abstractions can push through these hard limits in practical ways. We propose Attested Append-Only Memory (A2M), a trusted system facility that is small, easy to implement and easy to verify formally. A2M provides the programming abstraction of a trusted log, which leads to protocol designs immune to equivocation -- the ability of a faulty host to lie in different ways to different clients or servers -- which is a common source of Byzantine headaches. Using A2M, we improve upon the state of the art in Byzantine-fault tolerant replicated state machines, producing A2M-enabled protocols (variants of Castro and Liskov's PBFT) that remain correct (linearizable) and keep making progress (live) even when half the replicas are faulty, in contrast to the previous upper bound. We also present an A2M-enabled single-server shared storage protocol that guarantees linearizability despite server faults. We implement A2M and our protocols, evaluate them experimentally through micro- and macro-benchmarks, and argue that the improved fault tolerance is cost-effective for a broad range of uses, opening up new avenues for practical, more reliable services.
{"title":"Attested append-only memory: making adversaries stick to their word","authors":"Byung-Gon Chun, Petros Maniatis, S. Shenker, J. Kubiatowicz","doi":"10.1145/1294261.1294280","DOIUrl":"https://doi.org/10.1145/1294261.1294280","url":null,"abstract":"Researchers have made great strides in improving the fault tolerance of both centralized and replicated systems against arbitrary (Byzantine) faults. However, there are hard limits to how much can be done with entirely untrusted components; for example, replicated state machines cannot tolerate more than a third of their replica population being Byzantine. In this paper, we investigate how minimal trusted abstractions can push through these hard limits in practical ways. We propose Attested Append-Only Memory (A2M), a trusted system facility that is small, easy to implement and easy to verify formally. A2M provides the programming abstraction of a trusted log, which leads to protocol designs immune to equivocation -- the ability of a faulty host to lie in different ways to different clients or servers -- which is a common source of Byzantine headaches. Using A2M, we improve upon the state of the art in Byzantine-fault tolerant replicated state machines, producing A2M-enabled protocols (variants of Castro and Liskov's PBFT) that remain correct (linearizable) and keep making progress (live) even when half the replicas are faulty, in contrast to the previous upper bound. We also present an A2M-enabled single-server shared storage protocol that guarantees linearizability despite server faults. We implement A2M and our protocols, evaluate them experimentally through micro- and macro-benchmarks, and argue that the improved fault tolerance is cost-effective for a broad range of uses, opening up new avenues for practical, more reliable services.","PeriodicalId":20672,"journal":{"name":"Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78586235","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}
Commenting source code has long been a common practice in software development. Compared to source code, comments are more direct, descriptive and easy-to-understand. Comments and sourcecode provide relatively redundant and independent information regarding a program's semantic behavior. As software evolves, they can easily grow out-of-sync, indicating two problems: (1) bugs -the source code does not follow the assumptions and requirements specified by correct program comments; (2) bad comments - comments that are inconsistent with correct code, which can confuse and mislead programmers to introduce bugs in subsequent versions. Unfortunately, as most comments are written in natural language, no solution has been proposed to automatically analyze commentsand detect inconsistencies between comments and source code. This paper takes the first step in automatically analyzing commentswritten in natural language to extract implicit program rulesand use these rules to automatically detect inconsistencies between comments and source code, indicating either bugs or bad comments. Our solution, iComment, combines Natural Language Processing(NLP), Machine Learning, Statistics and Program Analysis techniques to achieve these goals. We evaluate iComment on four large code bases: Linux, Mozilla, Wine and Apache. Our experimental results show that iComment automatically extracts 1832 rules from comments with 90.8-100% accuracy and detects 60 comment-code inconsistencies, 33 newbugs and 27 bad comments, in the latest versions of the four programs. Nineteen of them (12 bugs and 7 bad comments) have already been confirmed by the corresponding developers while the others are currently being analyzed by the developers.
{"title":"/*icomment: bugs or bad comments?*/","authors":"Lin Tan, Ding Yuan, G. Krishna, Yuanyuan Zhou","doi":"10.1145/1294261.1294276","DOIUrl":"https://doi.org/10.1145/1294261.1294276","url":null,"abstract":"Commenting source code has long been a common practice in software development. Compared to source code, comments are more direct, descriptive and easy-to-understand. Comments and sourcecode provide relatively redundant and independent information regarding a program's semantic behavior. As software evolves, they can easily grow out-of-sync, indicating two problems: (1) bugs -the source code does not follow the assumptions and requirements specified by correct program comments; (2) bad comments - comments that are inconsistent with correct code, which can confuse and mislead programmers to introduce bugs in subsequent versions. Unfortunately, as most comments are written in natural language, no solution has been proposed to automatically analyze commentsand detect inconsistencies between comments and source code. This paper takes the first step in automatically analyzing commentswritten in natural language to extract implicit program rulesand use these rules to automatically detect inconsistencies between comments and source code, indicating either bugs or bad comments. Our solution, iComment, combines Natural Language Processing(NLP), Machine Learning, Statistics and Program Analysis techniques to achieve these goals. We evaluate iComment on four large code bases: Linux, Mozilla, Wine and Apache. Our experimental results show that iComment automatically extracts 1832 rules from comments with 90.8-100% accuracy and detects 60 comment-code inconsistencies, 33 newbugs and 27 bad comments, in the latest versions of the four programs. Nineteen of them (12 bugs and 7 bad comments) have already been confirmed by the corresponding developers while the others are currently being analyzed by the developers.","PeriodicalId":20672,"journal":{"name":"Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2007-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78905539","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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