Preventing Atomicity Violations with Contracts

Software developers are expected to protect concurrent accesses to shared regions of memory with some mutual exclusion primitive that ensures atomicity properties to a sequence of program statements. This approach prevents data races but may fail to provide all necessary correctness properties.The composition of correlated atomic operations without further synchronization may cause atomicity violations. Atomic violations may be avoided by grouping the correlated atomic regions in a single larger atomic scope. Concurrent programs are particularly prone to atomicity violations when they use services provided by third party packages or modules, since the programmer may fail to identify which services are correlated. In this paper we propose to use contracts for concurrency, where the developer of a module writes a set of contract terms that specify which methods are correlated and must be executed in the same atomic scope. These contracts are then used to verify the correctness of the main program with respect to the usage of the module(s). If a contract is well defined and complete, and the main program respects it, then the program is safe from atomicity violations with respect to that module. We also propose a static analysis based methodology to verify contracts for concurrency that we applied to some real-world software packages. The bug we found in Tomcat 6.0 was immediately acknowledged and corrected by its development team

Faster linearizability checking via PP-compositionality

Linearizability is a well-established consistency and correctness criterion for concurrent data types. An important feature of linearizability is Herlihy and Wing's locality principle, which says that a concurrent system is linearizable if and only if all of its constituent parts (so-called objects) are linearizable. This paper presents $P$-compositionality, which generalizes the idea behind the locality principle to operations on the same concurrent data type. We implement $P$-compositionality in a novel linearizability checker. Our experiments with over nine implementations of concurrent sets, including Intel's TBB library, show that our linearizability checker is one order of magnitude faster and/or more space efficient than the state-of-the-art algorithm.Comment: 15 pages, 2 figure

A Method and Tool for Finding Concurrency Bugs Involving Multiple Variables with Application to Modern Distributed Systems

Concurrency bugs are extremely hard to detect due to huge interleaving space. They are happening in the real world more often because of the prevalence of multi-threaded programs taking advantage of multi-core hardware, and microservice based distributed systems moving more and more applications to the cloud. As the most common non-deadlock concurrency bugs, atomicity violations are studied in many recent works, however, those methods are applicable only to single-variable atomicity violation, and don\u27t consider the specific challenge in distributed systems that have both pessimistic and optimistic concurrency control. This dissertation presents a tool using model checking to predict atomicity violation concurrency bugs involving two shared variables or shared resources. We developed a unique method inferring correlation between shared variables in multi-threaded programs and shared resources in microservice based distributed systems, that is based on dynamic analysis and is able to detect the correlation that would be missed by static analysis. For multi-threaded programs, we use a binary instrumentation tool to capture runtime information about shared variables and synchronization events, and for microservice based distributed systems, we use a web proxy to capture HTTP based traffic about API calls and the shared resources they access including distributed locks. Based on the detected correlation and runtime trace, the tool is powerful and can explore a vast interleaving space of a multi-threaded program or a microservice based distributed system given a small set of captured test runs. It is applicable to large real-world systems and can predict atomicity violations missed by other related works for multi-threaded programs and a couple of previous unknown atomicity violation in real world open source microservice based systems. A limitation is that redundant model checking may be performed if two recorded interleaved traces yield the same partial order model

ORCA: Ordering-free Regions for Consistency and Atomicity

Writing correct synchronization is one of the main difficulties of multithreaded programming. Incorrect synchronization causes many subtle concurrency errors such as data races and atomicity violations. Previous work has proposed stronger memory consistency models to rule out certain classes of concurrency bugs. However, these approaches are limited by a program’s original (and possibly incorrect) synchronization. In this work, we provide stronger guarantees than previous memory consistency models by punctuating atomicity only at ordering constructs like barriers, but not at lock operations. We describe the Ordering-free Regions for Consistency and Atomicity (ORCA) system which enforces atomicity at the granularity of ordering-free regions (OFRs). While many atomicity violations occur at finer granularity, in an empirical study of many large multithreaded workloads we find no examples of code that requires atomicity coarser than OFRs. Thus, we believe OFRs are a conservative approximation of the atomicity requirements of many programs. ORCA assists programmers by throwing an exception when OFR atomicity is threatened, and, in exception-free executions, guaranteeing that all OFRs execute atomically. In our evaluation, we show that ORCA automatically prevents real concurrency bugs. A user-study of ORCA demonstrates that synchronizing a program with ORCA is easier than using a data race detector. We evaluate modest hardware support that allows ORCA to run with just 18% slowdown on average over pthreads, with very similar scalability

Rigorous concurrency analysis of multithreaded programs

technical reportThis paper explores the practicality of conducting program analysis for multithreaded software using constraint solv- ing. By precisely defining the underlying memory consis- tency rules in addition to the intra-thread program seman- tics, our approach orders a unique advantage for program ver- ification | it provides an accurate and exhaustive coverage of all thread interleavings for any given memory model. We demonstrate how this can be achieved by formalizing sequen- tial consistency for a source language that supports control branches and a monitor-style mutual exclusion mechanism. We then discuss how to formulate programmer expectations as constraints and propose three concrete applications of this approach: execution validation, race detection, and atom- icity analysis. Finally, we describe the implementation of a formal analysis tool using constraint logic programming, with promising initial results for reasoning about small but non-trivial concurrent programs

Dynamic Analysis of Embedded Software

abstract: Most embedded applications are constructed with multiple threads to handle concurrent events. For optimization and debugging of the programs, dynamic program analysis is widely used to collect execution information while the program is running. Unfortunately, the non-deterministic behavior of multithreaded embedded software makes the dynamic analysis difficult. In addition, instrumentation overhead for gathering execution information may change the execution of a program, and lead to distorted analysis results, i.e., probe effect. This thesis presents a framework that tackles the non-determinism and probe effect incurred in dynamic analysis of embedded software. The thesis largely consists of three parts. First of all, we discusses a deterministic replay framework to provide reproducible execution. Once a program execution is recorded, software instrumentation can be safely applied during replay without probe effect. Second, a discussion of probe effect is presented and a simulation-based analysis is proposed to detect execution changes of a program caused by instrumentation overhead. The simulation-based analysis examines if the recording instrumentation changes the original program execution. Lastly, the thesis discusses data race detection algorithms that help to remove data races for correctness of the replay and the simulation-based analysis. The focus is to make the detection efficient for C/C++ programs, and to increase scalability of the detection on multi-core machines.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Locality and Singularity for Store-Atomic Memory Models

Robustness is a correctness notion for concurrent programs running under relaxed consistency models. The task is to check that the relaxed behavior coincides (up to traces) with sequential consistency (SC). Although computationally simple on paper (robustness has been shown to be PSPACE-complete for TSO, PGAS, and Power), building a practical robustness checker remains a challenge. The problem is that the various relaxations lead to a dramatic number of computations, only few of which violate robustness. In the present paper, we set out to reduce the search space for robustness checkers. We focus on store-atomic consistency models and establish two completeness results. The first result, called locality, states that a non-robust program always contains a violating computation where only one thread delays commands. The second result, called singularity, is even stronger but restricted to programs without lightweight fences. It states that there is a violating computation where a single store is delayed. As an application of the results, we derive a linear-size source-to-source translation of robustness to SC-reachability. It applies to general programs, regardless of the data domain and potentially with an unbounded number of threads and with unbounded buffers. We have implemented the translation and verified, for the first time, PGAS algorithms in a fully automated fashion. For TSO, our analysis outperforms existing tools

Predicting Errors in Concurrent Systems

Die Verbreitung von Multikernprozessoren hat die parallele Programmierung allgegenwärtig gemacht. Parallele Programmierung ist schwierig, da sie die Entwicklung auf Grund vielfacher Kontrollflüsse und Nicht-Determinismus fehleranfällig macht. Zusätzlich gibt es neue Arten von Fehlern, wie z.B. Wettläufe, Verklemmungen oder Reihenfolgeverletzung. Diese Fehler sind wegen der großen Anzahl von möglichen Verschränkungen schwer zu finden. Dynamische Analyseansätze führen das Programm aus und untersuchen die beobachtete Ausführung. Dynamische Analyse ist präzise, da sie eine tatsächliche Ausführung mit realen Werten und Zuständen beobachtet. Diese Ansätze erzeugen falsch Negative, wegen nicht erforschter Wege und Verschränkungen. Die unterschiedlichen Verschränkungen treten mit unterschiedlicher Häufigkeit auf, wegen externer Faktoren, wie z.B. Compiler, Prozessor oder Arbeitslast. In dieser Arbeit präsentieren wir einen Ansatz, der Fehler aus einer einzigen Spur eines parallelen Programms vorhersagt. Wir berechnen off-line alternative Verschränkungen, um den Zeitmessungseffekt der beobachteten Ausführung zu reduzieren. Wir bauen ein Modell mit Hilfe einer Prozessalgebra, das die Reihenfolge der Spur verallgemeinert; es extrapoliert mögliche Verschränkungen. Im Modell wird nach verschiedenen Nebenläufigkeitsfehlern gesucht. Ein vorhergesagter Fehler wird von einer Verschränkung begleitet, die in dem Programm erzwungen wird, um den Fehler zu reproduzieren. Der Ansatz wurde für Verklemmungs- und Wettlauferkennung im Vergleich zu anderen dynamischen Ansätzen evaluiert. Die Verringerung von falschen Warnungen bewegt sich im Bereich von 50% bis 86%, mit gleicher oder höherer Präzision. Das vorgestellte Werkzeug und sein Modell sind anpassbar für andere Reihenfolgeverletzungen. Diese Fehler erfordern eine Spezifikation, die die relevanten Ereignisse im Programm definiert und die gültigen oder ungültigen Ordnungen beschreibt. Wir zeigen dieses Vorgehen an sieben Anwendungsbeispielen

Strong Memory Consistency For Parallel Programming

Correctly synchronizing multithreaded programs is challenging, and errors can lead to program failures (e.g., atomicity violations). Existing memory consistency models rule out some possible failures, but are limited by depending on subtle programmer-defined locking code and by providing unintuitive semantics for incorrectly synchronized code. Stronger memory consistency models assist programmers by providing them with easier-to-understand semantics with regard to memory access interleavings in parallel code. This dissertation proposes a new strong memory consistency model based on ordering-free regions (OFRs), which are spans of dynamic instructions between consecutive ordering constructs (e.g. barriers). Atomicity over ordering-free regions provides stronger atomicity than existing strong memory consistency models with competitive performance. Ordering-free regions also simplify programmer reasoning by limiting the potential for atomicity violations to fewer points in the program’s execution. This dissertation explores both software-only and hardware-supported systems that provide OFR serializability