We present nesC, a programming language for networked embedded systems that represent a new design space for application developers. An example of a networked embedded system is a sensor network, which consists of (potentially) thousands of tiny, low-power "motes," each of which execute concurrent, reactive programs that must operate with severe memory and power constraints.nesC's contribution is to support the special needs of this domain by exposing a programming model that incorporates event-driven execution, a flexible concurrency model, and component-oriented application design. Restrictions on the programming model allow the nesC compiler to perform whole-program analyses, including data-race detection (which improves reliability) and aggressive function inlining (which reduces resource consumption).nesC has been used to implement TinyOS, a small operating system for sensor networks, as well as several significant sensor applications. nesC and TinyOS have been adopted by a large number of sensor network research groups, and our experience and evaluation of the language shows that it is effective at supporting the complex, concurrent programming style demanded by this new class of deeply networked systems.

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The nesC language: a holistic approach to networked embedded systems

The majority of the work carried out in the formal methods community throughout the last three decades has (for good reasons) been devoted to special languages designed to make it easier to experiment with mechanized formal methods such as theorem provers and model checkers. In this paper, we give arguments for why we believe it is time for the formal methods community to shift some of its attention towards the analysis of programs written in modern programming languages. In keeping with this philosophy, we have developed a verification and testing environment for Java, called Java PathFinder (JPF), which integrates model checking, program analysis and testing. Part of this work has consisted of building a new Java Virtual Machine that interprets Java bytecode. JPF uses state compression to handle large states, and partial order reduction, slicing, abstraction and run-time analysis techniques to reduce the state space. JPF has been applied to a real-time avionics operating system developed at Honeywell, illustrating an intricate error, and to a model of a spacecraft controller, illustrating the combination of abstraction, run-time analysis and slicing with model checking.

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Model checking programs

Many techniques have been developed over the years to automatically find bugs in software. Often, these techniques rely on formal methods and sophisticated program analysis. While these techniques are valuable, they can be difficult to apply, and they aren't always effective in finding real bugs.Bug patterns are code idioms that are often errors. We have implemented automatic detectors for a variety of bug patterns found in Java programs. In this extended abstract1, we describe how we have used bug pattern detectors to find serious bugs in several widely used Java applications and libraries. We have found that the effort required to implement a bug pattern detector tends to be low, and that even extremely simple detectors find bugs in real applications.From our experience applying bug pattern detectors to real programs, we have drawn several interesting conclusions. First, we have found that even well tested code written by experts contains a surprising number of obvious bugs. Second, Java (and similar languages) have many language features and APIs which are prone to misuse. Finally, that simple automatic techniques can be effective at countering the impact of both ordinary mistakes and misunderstood language features.

Finding bugs is easy

Software fault localization, the act of identifying the locations of faults in a program, is widely recognized to be one of the most tedious, time consuming, and expensive – yet equally critical – activities in program debugging. Due to the increasing scale and complexity of software today, manually locating faults when failures occur is rapidly becoming infeasible, and consequently, there is a strong demand for techniques that can guide software developers to the locations of faults in a program with minimal human intervention. This demand in turn has fueled the proposal and development of a broad spectrum of fault localization techniques, each of which aims to streamline the fault localization process and make it more effective by attacking the problem in a unique way. In this article, we catalog and provide a comprehensive overview of such techniques and discuss key issues and concerns that are pertinent to software fault localization as a whole.

A Survey on Software Fault Localization

The reality of multi-core hardware has made concurrent programs pervasive. Unfortunately, writing correct concurrent programs is difficult. Addressing this challenge requires advances in multiple directions, including concurrency bug detection, concurrent program testing, concurrent programming model design, etc. Designing effective techniques in all these directions will significantly benefit from a deep understanding of real world concurrency bug characteristics.This paper provides the first (to the best of our knowledge) comprehensive real world concurrency bug characteristic study. Specifically, we have carefully examined concurrency bug patterns, manifestation, and fix strategies of 105 randomly selected real world concurrency bugs from 4 representative server and client open-source applications (MySQL, Apache, Mozilla and OpenOffice). Our study reveals several interesting findings and provides useful guidance for concurrency bug detection, testing, and concurrent programming language design.Some of our findings are as follows: (1) Around one third of the examined non-deadlock concurrency bugs are caused by violation to programmers' order intentions, which may not be easily expressed via synchronization primitives like locks and transactional memories; (2) Around 34% of the examined non-deadlock concurrency bugs involve multiple variables, which are not well addressed by existing bug detection tools; (3) About 92% of the examined concurrency bugs canbe reliably triggered by enforcing certain orders among no more than 4 memory accesses. This indicates that testing concurrent programs can target at exploring possible orders among every small groups of memory accesses, instead of among all memory accesses; (4) About 73% of the examinednon-deadlock concurrency bugs were not fixed by simply adding or changing locks, and many of the fixes were not correct at the first try, indicating the difficulty of reasoning concurrent execution by programmers.

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Learning from mistakes: a comprehensive study on real world concurrency bug characteristics

Multithreaded programming is difficult and error prone. It is easy to make a mistake in synchronization that produces a data race, yet it can be extremely hard to locate this mistake during debugging. This article describes a new tool, called Eraser, for dynamically detecting data races in lock-based multithreaded programs. Eraser uses binary rewriting techniques to monitor every shared-monory reference and verify that consistent locking behavior is observed. We present several case studies, including undergraduate coursework and a multithreaded Web search engine, that demonstrate the effectiveness of this approach.

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Greg Nelson

Papers

Eraser: a dynamic data race detector for multithreaded programs