3.1 Program analysis

A fundamental goal of the research in the Whisper team is to elicit and exploit the knowledge found in existing code. To do this in a way that scales to a large code base, systematic methods are needed to infer code properties. We may build on either static 26, 28, 29 or dynamic analysis 45, 47, 50. Static analysis consists of approximating the behavior of the source code from the source code alone, while dynamic analysis draws conclusions from observations of sample executions, typically of test cases. While dynamic analysis can be more accurate, because it has access to information about actual program behavior, obtaining adequate test cases is difficult. This difficulty is compounded for infrastructure software, where many, often obscure, cases must be handled, and external effects such as timing can have a significant impact. Thus, we expect to primarily use static analyses. Static analyses come in a range of flavors, varying in the extent to which the analysis is sound, i.e., the extent to which the results are guaranteed to reflect possible run-time behaviors.

One form of sound static analysis is abstract interpretation28. In abstract interpretation, atomic terms are interpreted as sound abstractions of their values, and operators are interpreted as functions that soundly manipulate these abstract values. The analysis is then performed by interpreting the program in a compositional manner using these abstracted values and operators. Alternatively, dataflow analysis37 iteratively infers connections between variable definitions and uses, in terms of local transition rules that describe how various kinds of program constructs may impact variable values. Schmidt has explored the relationship between abstract interpretation and dataflow analysis 58. More recently, more general forms of symbolic execution 26 have emerged as a means of understanding complex code. In symbolic execution, concrete values are used when available, and these are complemented by constraints that are inferred from terms for which only partial information is available. Reasoning about these constraints is then used to prune infeasible paths, and obtain more precise results. A number of works apply symbolic execution to operating systems code 24, 25.

While sound approaches are guaranteed to give correct results, they typically do not scale to the very diverse code bases that are prevalent in infrastructure software. An important insight of Engler et al. 31 was that valuable information could be obtained even when sacrificing soundness, and that sacrificing soundness could make it possible to treat software at the scales of the kernels of the Linux or BSD operating systems. Indeed, for certain types of problems, on certain code bases, that may mostly follow certain coding conventions, it may mostly be safe to e.g., ignore the effects of aliases, assume that variable values are unchanged by calls to unanalyzed functions, etc. Real code has to be understood by developers and thus cannot be too complicated, so such simplifying assumptions are likely to hold in practice. Nevertheless, approaches that sacrifice soundness also require the user to manually validate the results. Still, it is likely to be much more efficient for the user to perform a potentially complex manual analysis in a specific case, rather than to implement all possible required analyses and apply them everywhere in the code base. A refinement of unsound analysis is the CEGAR approach 27, in which a highly approximate analysis is complemented by a sound analysis that checks the individual reports of the approximate analysis, and then any errors in reasoning detected by the sound analysis are used to refine the approximate analysis. The CEGAR approach has been applied effectively on device driver code in tools developed at Microsoft  21. The environment in which the driver executes, however, is still represented by possibly unsound approximations.

Going further in the direction of sacrificing soundness for scalability, the software engineering community has recently explored a number of approaches to code understanding based on techniques developed in the areas of natural language understanding, data mining, and information retrieval. These approaches view code, as well as other software-reated artifacts, such as documentation and postings on mailing lists, as bags of words structured in various ways. Statistical methods are then used to collect words or phrases that seem to be highly correlated, independently of the semantics of the program constructs that connect them. The obliviousness to program semantics can lead to many false positives (invalid conclusions) 32, but can also highlight trends that are not apparent at the low level of individual program statements. We have previously explored combining such statistical methods with more traditional static analysis in identifying faults in the usage of constants in Linux kernel code 41.

3.2 Domain Specific Languages

Writing low-level infrastructure code is tedious and difficult, and verifying it is even more so. To produce non-trivial programs, we could benefit from moving up the abstraction stack to enable both programming and proving as quickly as possible. Domain-specific languages (DSLs), also known as little languages, are a means to that end 548.

3.3 Research direction: Tools for improving legacy infrastructure software

A cornerstone of our work on legacy infrastructure software is the Coccinelle program matching and transformation tool for C code. Coccinelle has been in continuous development since 2005. Today, Coccinelle is extensively used in the context of Linux kernel development, as well as in the development of other software, such as wine, python, kvm, git, and systemd. Currently, Coccinelle is a mature software project, and no research is being conducted on Coccinelle itself. Instead, we leverage Coccinelle in other research projects  22, 23, 49, 51, 55, 57, 59, 46, 42, both for code exploration, to better understand at a large scale problems in Linux development, and as an essential component in tools that require program matching and transformation. The continuing development and use of Coccinelle is also a source of visibility in the Linux kernel developer community. We submitted the first patches to the Linux kernel based on Coccinelle in 2007. Since then, almost 9000 patches have been accepted into the Linux kernel based on the use of Coccinelle, including thousands by over 400 developers from outside our research group.

Our recent work has focused on driver porting. Specifically, we have considered the problem of porting a Linux device driver across versions, particularly backporting, in which a modern driver needs to be used by a client who, typically for reasons of stability, is not able to update their Linux kernel to the most recent version. When multiple drivers need to be backported, they typically need many common changes, suggesting that Coccinelle could be applicable. Using Coccinelle, however, requires writing backporting transformation rules. In order to more fully automate the backporting (or symmetrically forward porting) process, these rules should be generated automatically. We have carried out a preliminary study in this direction with David Lo of Singapore Management University; this work, published at ICSME 2016 62, is limited to a port from one version to the next one, in the case where the amount of change required is limited to a single line of code. Whisper has been awarded an ANR PRCI grant (completed in 2021) to collaborate with the group of David Lo on scaling up the rule inference process and proposing a fully automatic porting solution.

3.4 Research direction: developing infrastructure software using Domain Specific Languages

We wish to pursue a declarative approach to developing infrastructure software. Indeed, there exists a significant gap between the high-level objectives of these systems and their implementation in low-level, imperative programming languages. To bridge that gap, we propose an approach based on domain-specific languages (DSLs). By abstracting away boilerplate code, DSLs increase the productivity of systems programmers. By providing a more declarative language, DSLs reduce the complexity of code, thus the likelihood of bugs.

Traditionally, systems are built by accretion of several, independent DSLs. For example, one might use Devil 4 to interact with devices, Bossa 6 to implement the scheduling policies. However, much effort is duplicated in implementing the back-ends of the individual DSLs. Our long term goal is to design a unified framework for developing and composing DSLs. By providing a single conceptual framework, we hope to amortize the development cost of a myriad of DSLs through a principled approach to reusing and composing them.

Beyond the software engineering aspects, a unified platform brings us closer to the implementation of mechanically-verified DSLs. A key benefit would be to provide – by construction – a formal, mechanized semantics to the DSLs thus developed. Such a semantics would offer a foundation on which to base further verification efforts, while allowing interaction with non-verified code. We advocate a methodology based on incremental, piece-wise verification. While building fully-certified systems from the top-down is a worthwhile endeavor 38, we wish to explore a bottom-up approach by which one focuses first and foremost on crucial subsystems and their associated properties.

Our current work on DSLs focuses on the design of domain-specific languages for domains where there is a critical need for code correctness, and corresponding methodologies for proving properties of the run-time behavior of the system.

4.1 Linux

Linux is an open-source operating system that is used in settings ranging from embedded systems to supercomputers. The most recent release of the Linux kernel, v5.15, comprises over 20 million lines of code, and supports 30 different families of CPU architectures, around 50 file systems, and thousands of device drivers. Linux is also in a rapid stage of development, with new versions being released roughly every 2.5 months. Recent versions have each incorporated around 13,500 commits, from around 1500 developers. These developers have a wide range of expertise, with some providing hundreds of patches per release, while others have contributed only one. Overall, the Linux kernel is critical software, but software in which the quality of the developed source code is highly variable. These features, combined with the fact that the Linux community is open to contributions and to the use of tools, make the Linux kernel an attractive target for software researchers. Tools that result from research can be directly integrated into the development of real software, where it can have a high, visible impact.

Starting from the work of Engler et al.  30, numerous research tools have been applied to the Linux kernel, typically for finding bugs  29, 44, 52, 61 or for computing software metrics  35, 63. In our work, we have studied generic C bugs in Linux code 8, bugs in function protocol usage  39, 40, issues related to the processing of bug reports  56 and crash dumps  34, and the problem of backporting  51, 62, illustrating the variety of issues that can be explored on this code base. Unique among research groups working in this area, we have furthermore developed numerous contacts in the Linux developer community. These contacts provide insights into the problems actually faced by developers and serve as a means of validating the practical relevance of our work.

4.2 Device Drivers

Device drivers are essential to modern computing, to provide applications with access, via the operating system, to physical devices such as keyboards, disks, networks, and cameras. Development of new computing paradigms, such as the internet of things, is hampered because device driver development is challenging and error-prone, requiring a high level of expertise in both the targeted OS and the specific device. Furthermore, implementing just one driver is often not sufficient; today's computing landscape is characterized by a number of OSes, e.g., Linux, Windows, MacOS, BSD and many real time OSes, and each is found in a wide range of variants and versions. All of these factors make the development, porting, backporting, and maintenance of device drivers a critical problem for device manufacturers, industry that requires specific devices, and even for ordinary users.

The last twenty years have seen a number of approaches directed towards easing device driver development. Réveillère, who was supervised by G. Muller, proposes Devil 4, a domain-specific language for describing the low-level interface of a device. Chipounov et al. propose RevNic, 25 a template-based approach for porting device drivers from one OS to another. Ryzhyk et al. propose Termite, 53, 54 an approach for synthesizing device driver code from a specification of an OS and a device. Currently, these approaches have been successfully applied to only a small number of toy drivers. Indeed, Kadav and Swift 36 observe that these approaches make assumptions that are not satisfied by many drivers; for example, the assumption that a driver involves little computation other than the direct interaction between the OS and the device. At the same time, a number of tools have been developed for finding bugs in driver code. These tools include SDV 21, Coverity 30, CP-Miner, 43 PR-Miner 44, and Coccinelle 7. These approaches, however, focus on analyzing existing code, and do not provide guidelines on structuring drivers.

In summary, there is still a need for a methodology that first helps the developer understand the software architecture of drivers for commonly used operating systems, and then provides tools for the maintenance of existing drivers.

5.1 Impact of research results

6.1 Awards

• Reda Gouicem's 2020 PhD thesis on "Thread Scheduling in Multi-core Operating Systems", supervised by Gilles Muller and Julien Sopena was recognized (accessit) as part of the Prix de Thèse du GDR RSD/ASF 2021 (link).
• Gilles Muller received the Senior researcher prize of the GDR RSD/ASF for 2021 (link)

7.1 New software

8.1 Software engineering for infrastructure software

Our main work in this area has been on the problem of inferring transformation rules from change examples for the purpose of fully automating large-scale evolutions in infrastructure software. This work has been carried out in collaboration with David Lo and Lingxiao Jiang of Singapore Management University, in the context of the ANR ITrans project. We also have further explored the use of Coccinelle for HPC code, with Michele Martone of the Leibniz Supercomputing Centre.

8.2 Scalability

Participants: Gilles Muller [Orange Labs], Yoann Ghigoff [Orange Labs], Kahina Lazri [Orange Labs], Julien Sopena [Delys].

In-memory key-value stores are critical components that help scale large internet services by providing low-latency access to popular data. Memcached, one of the most popular key-value stores, suffers from performance limitations inherent to the Linux networking stack and fails to achieve high performance when using high-speed network interfaces. While the Linux network stack can be bypassed using DPDK based solutions, such approaches require a complete redesign of the software stack and induce high CPU utilization even when client load is low.

To overcome these limitations, in the paper "BMC: Accelerating Memcached using Safe In-kernel Caching and Pre-stack Processing", presented at NSDI 2021 12, we present BMC, an in-kernel cache for Memcached that serves requests before the execution of the standard network stack. Requests to the BMC cache are treated as part of the NIC interrupts, which allows performance to scale with the number of cores serving the NIC queues. To ensure safety, BMC is implemented using eBPF. Despite the safety constraints of eBPF, we show that it is possible to implement a complex cache service. Because BMC runs on commodity hardware and requires modification of neither the Linux kernel nor the Memcached application, it can be widely deployed on existing systems. BMC optimizes the processing time of Facebook-like small-size requests. On this target workload, our evaluations show that BMC improves throughput by up to 18x compared to the vanilla Memcached application and up to 6x compared to an optimized version of Memcached that uses the SO_REUSEPORT socket flag. In addition, our results also show that BMC has negligible overhead and does not deteriorate throughput when treating non-target workloads.

This work was done as part of the PhD of Yoann Ghigoff in collaboration with Orange Labs (Section 9.1).

8.3 Virtualization

Participants: Gilles Muller [ENS Lyon], Alain Tchana [ENS Lyon], Antonio Barbalace [University of Edinburgh].

8.4 Real-time systems

Participants: Gilles Muller [Inria Rennes], Isabelle Puaut [Inria Rennes].

Modern processors raise a challenge for WCET estimation, since detailed knowledge of the processor microarchitecture is not available. In the paper "WE-HML: hybrid WCET estimation using machine learning for architectures with caches", published at RTCSA 2021 11, we propose a novel hybrid WCET estimation technique, WE-HML, in which the longest path is estimated using static techniques, whereas machine learning (ML) is used to determine the WCET of basic blocks. In contrast to existing literature using ML techniques for WCET estimation, WE-HML (i) operates on binary code for improved precision of learning, as compared to the related techniques operating at source code or intermediate code level; (ii) trains the ML algorithms on a large set of automatically generated programs for improved quality of learning; (iii) proposes a technique to take into account data caches. Experiments on an ARM Cortex-A53 processor show that for all benchmarks, WCET estimates obtained by WE-HML are larger than all possible execution times. Moreover, the cache modeling technique of WE-HML allows an improvement of 65 percent on average of WCET estimates compared to its cache-agnostic equivalent.

9.1 Bilateral contracts with industry

9.2 Bilateral grants with industry

10.1 International initiatives

10.2 National initiatives

11.1 Promoting scientific activities

12.1 Major publications

• 1 inproceedingsJ.Julien Brunel, D.Damien Doligez, R. R.René Rydhof Hansen, J. L.Julia L. Lawall and G.Gilles Muller. A foundation for flow-based program matching using temporal logic and model checking.POPLSavannah, GA, USAACMJanuary 2009, 114--126
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• 2 articleL.Laurent Burgy, L.Laurent Réveillère, J. L.Julia L. Lawall and G.Gilles Muller. Zebu: A Language-Based Approach for Network Protocol Message Processing.IEEE Trans. Software Eng.3742011, 575-591
• 3 inproceedingsB.Baptiste Lepers, R.Redha Gouicem, D.Damien Carver, J.-P.Jean-Pierre Lozi, N.Nicolas Palix, M.-V.Maria-Virginia Aponte, W.Willy Zwaenepoel, J.Julien Sopena, J.Julia Lawall and G.Gilles Muller. Provable Multicore Schedulers with Ipanema: Application to Work Conservation.Eurosys 2020 - European Conference on Computer SystemsHeraklion / Virtual, GreeceApril 2020
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• 4 inproceedingsF.Fabrice Mérillon, L.Laurent Réveillère, C.Charles Consel, R.Renaud Marlet and G.Gilles Muller. Devil: An IDL for hardware programming.Proceedings of the Fourth Symposium on Operating Systems Design and Implementation (OSDI)San Diego, CaliforniaUSENIX AssociationOctober 2000, 17--30
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• 5 inproceedingsG.Gilles Muller, C.Charles Consel, R.Renaud Marlet, L. P.Luciano P. Barreto, F.Fabrice Mérillon and L.Laurent Réveillère. Towards Robust OSes for Appliances: A New Approach Based on Domain-specific Languages.Proceedings of the 9th Workshop on ACM SIGOPS European Workshop: Beyond the PC: New Challenges for the Operating SystemKolding, Denmark2000, 19--24
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• 6 inproceedingsG.Gilles Muller, J. L.Julia L. Lawall and H.Hervé Duchesne. A Framework for Simplifying the Development of Kernel Schedulers: Design and Performance Evaluation.HASE - High Assurance Systems Engineering ConferenceHeidelberg, GermanyIEEEOctober 2005, 56--65
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• 7 inproceedingsY.Yoann Padioleau, J. L.Julia L. Lawall, R. R.René Rydhof Hansen and G.Gilles Muller. Documenting and Automating Collateral Evolutions in Linux Device Drivers.EuroSysGlasgow, ScotlandMarch 2008, 247--260
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• 8 articleN.Nicolas Palix, G.Gaël Thomas, S.Suman Saha, C.Christophe Calvès, J. L.Julia L. Lawall and G.Gilles Muller. Faults in Linux 2.6.ACM Transactions on Computer Systems322June 2014, 4:1--4:40
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• 9 inproceedingsL.Lucas Serrano, V.-A.Van-Anh Nguyen, F.Ferdian Thung, L.Lingxiao Jiang, D.David Lo, J.Julia Lawall and G.Gilles Muller. SPINFER: Inferring Semantic Patches for the Linux Kernel.USENIX Annual Technical ConferenceBoston / Virtual, United StatesJuly 2020
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12.2 Publications of the year

12.3 Cited publications

• 21 inproceedingsT.Thomas Ball, E.Ella Bounimova, B.Byron Cook, V.Vladimir Levin, J.Jakob Lichtenberg, C.Con McGarvey, B.Bohus Ondrusek, S. K.Sriram K. Rajamani and A.Abdullah Ustuner. Thorough Static Analysis of Device Drivers.EuroSys2006, 73--85
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• 22 articleT. F.Tegawendé F. Bissyandé, L.Laurent Réveillère, J. L.Julia L. Lawall, Y.-D.Yérom-David Bromberg and G.Gilles Muller. Implementing an Embedded Compiler using Program Transformation Rules.Software: Practice and Experience452February 2015, 177-196
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• 23 articleT. F.Tegawendé F. Bissyandé, L.Laurent Réveillère, J. L.Julia L. Lawall and G.Gilles Muller. Ahead of Time Static Analysis for Automatic Generation of Debugging Interfaces to the Linux Kernel.Automated Software EngineeringMay 2014, 1-39
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• 24 inproceedingsC.Cristian Cadar, D.Daniel Dunbar and D. R.Dawson R. Engler. KLEE: Unassisted and Automatic Generation of High-Coverage Tests for Complex Systems Programs.OSDI2008, 209--224
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• 25 inproceedingsV.Vitaly Chipounov and G.George Candea. Reverse Engineering of Binary Device Drivers with RevNIC.EuroSys2010, 167--180
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• 26 articleL. A.L. A. Clarke. A system to generate test data and symbolically execute programs.IEEE Transactions on Software Engineering231976, 215--222
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• 27 articleE.E.M. Clarke, O.O. Grumberg, S.S. Jha, Y.Y. Lu and H.H. Veith. Counterexample-guided abstraction refinement for symbolic model checking.J. ACM5052003, 752--794
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• 28 inproceedingsP.Patrick Cousot and R.Radhia Cousot. Abstract Interpretation: Past, Present and Future.CSL-LICS2014, 2:1--2:10
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• 29 inproceedingsI.Isil Dillig, T.Thomas Dillig and A.Alex Aiken. Sound, complete and scalable path-sensitive analysis.PLDIJune 2008, 270--280
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• 30 inproceedingsD. R.Dawson R. Engler, B.Benjamin Chelf, A.Andy Chou and S.Seth Hallem. Checking System Rules Using System-Specific, Programmer-Written Compiler Extensions.OSDI2000, 1--16
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• 31 inproceedingsD. R.Dawson R. Engler, D. Y.David Yu Chen, A.Andy Chou and B.Benjamin Chelf. Bugs as Deviant Behavior: A General Approach to Inferring Errors in Systems Code.SOSP2001, 57--72
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• 32 inproceedingsC. L.Claire Le Goues and W.Westley Weimer. Specification Mining with Few False Positives.TACAS5505Lecture Notes in Computer ScienceYork, UKMarch 2009, 292--306
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• 33 inproceedingsL.Liang Gu, A.Alexander Vaynberg, B.Bryan Ford, Z.Zhong Shao and D.David Costanzo. CertiKOS: A Certified Kernel for Secure Cloud Computing.Proceedings of the Second Asia-Pacific Workshop on Systems (APSys)2011, 3:1--3:5
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• 34 inproceedingsL.Lisong Guo, J. L.Julia L. Lawall and G.Gilles Muller. Oops! Where did that code snippet come from?11th Working Conference on Mining Software Repositories, MSRHyderabad, IndiaACMMay 2014, 52--61
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• 35 articleA.Ayelet Israeli and D. G.Dror G. Feitelson. The Linux kernel as a case study in software evolution.Journal of Systems and Software8332010, 485--501
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• 36 inproceedingsA.Asim Kadav and M. M.Michael M. Swift. Understanding modern device drivers.ASPLOS2012, 87--98
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• 37 inproceedingsG. A.Gary A. Kildall. A Unified Approach to Global Program Optimization.POPL1973, 194--206
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• 38 inproceedingsG.Gerwin Klein, K.Kevin Elphinstone, G.Gernot Heiser, J.June Andronick, D.David Cock, P.Philip Derrin, D.Dhammika Elkaduwe, K.Kai Engelhardt, R.Rafal Kolanski, M.Michael Norrish, T.Thomas Sewell, H.Harvey Tuch and S.Simon Winwood. seL4: formal verification of an OS kernel.SOSP2009, 207--220
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• 39 articleJ. L.Julia L. Lawall, J.Julien Brunel, N.Nicolas Palix, R. R.René Rydhof Hansen, H.Henrik Stuart and G.Gilles Muller. WYSIWIB: Exploiting fine-grained program structure in a scriptable API-usage protocol-finding process.Software, Practice Experience4312013, 67--92
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• 40 inproceedingsJ. L.Julia L. Lawall, B.Ben Laurie, R. R.René Rydhof Hansen, N.Nicolas Palix and G.Gilles Muller. Finding Error Handling Bugs in OpenSSL using Coccinelle.Proceeding of the 8th European Dependable Computing Conference (EDCC)Valencia, SpainApril 2010, 191--196
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• 41 inproceedingsJ. L.Julia L. Lawall and D.David Lo. An automated approach for finding variable-constant pairing bugs.25th IEEE/ACM International Conference on Automated Software EngineeringAntwerp, BelgiumSeptember 2010, 103--112
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• 42 inproceedingsJ. L.Julia L. Lawall, D.Derek Palinski, L.Lukas Gnirke and G.Gilles Muller. Fast and Precise Retrieval of Forward and Back Porting Information for Linux Device Drivers.2017 USENIX Annual Technical ConferenceSanta Clara, CA, United StatesJuly 2017, 12
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• 43 inproceedingsZ.Zhenmin Li, S.Shan Lu, S.Suvda Myagmar and Y.Yuanyuan Zhou. CP-Miner: A Tool for Finding Copy-paste and Related Bugs in Operating System Code.OSDI2004, 289--302
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• 44 inproceedingsZ.Zhenmin Li and Y.Yuanyuan Zhou. PR-Miner: automatically extracting implicit programming rules and detecting violations in large software code.Proceedings of the 10th European Software Engineering Conference2005, 306--315
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• 45 inproceedingsD.David Lo and S.-C.Siau-Cheng Khoo. SMArTIC: towards building an accurate, robust and scalable specification miner.FSE2006, 265--275
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• 46 articleJ.-P.Jean-Pierre Lozi, F.Florian David, G.Gaël Thomas, J. L.Julia L. Lawall and G.Gilles Muller. Fast and Portable Locking for Multicore Architectures.ACM Transactions on Computer SystemsJanuary 2016
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• 47 articleS.Shan Lu, S.Soyeon Park and Y.Yuanyuan Zhou. Finding Atomicity-Violation Bugs through Unserializable Interleaving Testing.IEEE Transactions on Software Engineering3842012, 844--860
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• 48 articleM.Marjan Mernik, J.Jan Heering and A. M.Anthony M. Sloane. When and How to Develop Domain-specific Languages.ACM Comput. Surv.374December 2005, 316--344URL: http://dx.doi.org/10.1145/1118890.1118892
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• 49 articleM. C.Mads Chr. Olesen, R. R.René Rydhof Hansen, J. L.Julia L. Lawall and N.Nicolas Palix. Coccinelle: Tool support for automated CERT C Secure Coding Standard certification.Science of Computer Programming91BOctober 2014, 141--160
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• 50 inproceedingsT.Thomas Reps, T.Thomas Ball, M.Manuvir Das and J.James Larus. The Use of Program Profiling for Software Maintenance with Applications to the Year 2000 Problem.ESEC/FSE1997, 432--449
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• 51 inproceedingsL. R.Luis R. Rodriguez and J. L.Julia L. Lawall. Increasing Automation in the Backporting of Linux Drivers Using Coccinelle.11th European Dependable Computing Conference - Dependability in Practice11th European Dependable Computing Conference - Dependability in PracticeParis, FranceNovember 2015
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• 52 inproceedingsC.Cindy Rubio-González, H. S.Haryadi S. Gunawi, B.Ben Liblit, R. H.Remzi H. Arpaci-Dusseau and A. C.Andrea C. Arpaci-Dusseau. Error propagation analysis for file systems.PLDIDublin, IrelandACMJune 2009, 270--280
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• 53 inproceedingsL.Leonid Ryzhyk, P.Peter Chubb, I.Ihor Kuz, E.Etienne Le Sueur and G.Gernot Heiser. Automatic device driver synthesis with Termite.SOSP2009, 73--86
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• 54 inproceedingsL.Leonid Ryzhyk, A.Adam Walker, J.John Keys, A.Alexander Legg, A.Arun Raghunath, M.Michael Stumm and M.Mona Vij. User-Guided Device Driver Synthesis.OSDI2014, 661--676
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• 55 inproceedingsR. k.Ripon k. Saha, J. L.Julia L. Lawall, S.Sarfraz Khurshid and D. E.Dewayne E. Perry. On the Effectiveness of Information Retrieval Based Bug Localization for C Programs.ICSME 2014 - 30th International Conference on Software Maintenance and EvolutionIEEEVictoria, CanadaSeptember 2014, 161-170
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• 56 inproceedingsR.Ripon Saha, J. L.Julia L. Lawall, S.Sarfraz Khurshid and D. E.Dewayne E Perry. On the Effectiveness of Information Retrieval based Bug Localization for C Programs.International Conference on Software Maintenance and Evolution (ICSME)Victoria, BC, CanadaSeptember 2014
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• 57 inproceedingsS.Suman Saha, J.-P.Jean-Pierre Lozi, G.Gaël Thomas, J. L.Julia L. Lawall and G.Gilles Muller. Hector: Detecting resource-release omission faults in error-handling code for systems software.DSN 2013 - 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN)IEEE/IFIPBudapest, HungaryIEEE Computer SocietyJune 2013, 1-12
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• 58 inproceedingsD. A.David A. Schmidt. Data Flow Analysis is Model Checking of Abstract Interpretations.POPL1998, 38--48
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• 59 inproceedingsP.Peter Senna Tschudin, J. L.Julia L. Lawall and G.Gilles Muller. 3L: Learning Linux Logging.BElgian-NEtherlands software eVOLution seminar (BENEVOL 2015)Lille, FranceDecember 2015
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• 60 articleM.Mike Shapiro. Purpose-built languages.Commun. ACM5242009, 36--41
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• 61 inproceedingsR.Reinhard Tartler, D.Daniel Lohmann, J.Julio Sincero and W.Wolfgang Schröder-Preikschat. Feature consistency in compile-time-configurable system software: facing the Linux 10,000 feature problem.EuroSys2011, 47--60
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• 62 inproceedingsF.Ferdian Thung, D. X.Dinh Xuan Bach Le, D.David Lo and J. L.Julia L. Lawall. Recommending Code Changes for Automatic Backporting of Linux Device Drivers.32nd IEEE International Conference on Software Maintenance and Evolution (ICSME)IEEERaleigh, North Carolina, United StatesOctober 2016
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• 63 inproceedingsW.Wei Wang and M.M.W. Godfrey. A Study of Cloning in the Linux SCSI Drivers.Source Code Analysis and Manipulation (SCAM)IEEE2011
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• 64 inproceedingsJ.Jean Yang and C.Chris Hawblitzel. Safe to the Last Instruction: Automated Verification of a Type-safe Operating System.PLDI2010, 99--110
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