Control and Debugging of Distributed Programs Using Fiddle

The main goal of Fiddle, a distributed debugging engine, is to provide a flexible platform for developing debugging tools. Fiddle provides a layered set of interfaces with a minimal set of debugging functionalities, for the inspection and control of distributed and multi-threaded applications. This paper illustrates how Fiddle is used to support integrated testing and debugging. The approach described is based on a tool, called Deipa, that interprets sequences of commands read from an input file, generated by an independent testing tool. Deipa acts as a Fiddle client, in order to enforce specific execution paths in a distributed PVM program. Other Fiddle clients may be used along with Deipa for the fine debugging at process level. Fiddle and Deipa functionalities and architectures are described, and a working example shows a step-by-step application of these tools.Comment: In M. Ronsse, K. De Bosschere (eds), proceedings of the Fifth International Workshop on Automated Debugging (AADEBUG 2003), September 2003, Ghent. cs.SE/030902

Statistical Assertions for Validating Patterns and Finding Bugs in Quantum Programs

In support of the growing interest in quantum computing experimentation, programmers need new tools to write quantum algorithms as program code. Compared to debugging classical programs, debugging quantum programs is difficult because programmers have limited ability to probe the internal states of quantum programs; those states are difficult to interpret even when observations exist; and programmers do not yet have guidelines for what to check for when building quantum programs. In this work, we present quantum program assertions based on statistical tests on classical observations. These allow programmers to decide if a quantum program state matches its expected value in one of classical, superposition, or entangled types of states. We extend an existing quantum programming language with the ability to specify quantum assertions, which our tool then checks in a quantum program simulator. We use these assertions to debug three benchmark quantum programs in factoring, search, and chemistry. We share what types of bugs are possible, and lay out a strategy for using quantum programming patterns to place assertions and prevent bugs.Comment: In The 46th Annual International Symposium on Computer Architecture (ISCA '19). arXiv admin note: text overlap with arXiv:1811.0544

To parallelize or not to parallelize, bugs issue

Program correctness is one of the most difficult challenges in parallel programming. Message Passing Interface MPI is widely used in writing parallel applications. Since MPI is not a compiled language, the programmer will be enfaced with several programming bugs.This paper presents the most common programming bugs arise in MPI programs to help the programmer to compromise between the advantage of parallelism and the extra effort needed to detect and fix such bugs. An algebraic specification of an MPI-like programming language, called Simple MPI (SMPI), to be used in writing MPI programs specification has also been proposed. In addition, both nondeterminacy and deadlocks arise in SMPI programs have been verified using Maud system

Efficient System-Enforced Deterministic Parallelism

Deterministic execution offers many benefits for debugging, fault tolerance, and security. Running parallel programs deterministically is usually difficult and costly, however - especially if we desire system-enforced determinism, ensuring precise repeatability of arbitrarily buggy or malicious software. Determinator is a novel operating system that enforces determinism on both multithreaded and multi-process computations. Determinator's kernel provides only single-threaded, "shared-nothing" address spaces interacting via deterministic synchronization. An untrusted user-level runtime uses distributed computing techniques to emulate familiar abstractions such as Unix processes, file systems, and shared memory multithreading. The system runs parallel applications deterministically both on multicore PCs and across nodes in a cluster. Coarse-grained parallel benchmarks perform and scale comparably to - sometimes better than - conventional systems, though determinism is costly for fine-grained parallel applications.Comment: 14 pages, 12 figures, 3 table

Inspector: A Data Provenance Library for Multithreaded Programs

Data provenance strives for explaining how the computation was performed by recording a trace of the execution. The provenance trace is useful across a wide-range of workflows to improve the dependability, security, and efficiency of software systems. In this paper, we present Inspector, a POSIX-compliant data provenance library for shared-memory multithreaded programs. The Inspector library is completely transparent and easy to use: it can be used as a replacement for the pthreads library by a simple exchange of libraries linked, without even recompiling the application code. To achieve this result, we present a parallel provenance algorithm that records control, data, and schedule dependencies using a Concurrent Provenance Graph (CPG). We implemented our algorithm to operate at the compiled binary code level by leveraging a combination of OS-specific mechanisms, and recently released Intel PT ISA extensions as part of the Broadwell micro-architecture. Our evaluation on a multicore platform using applications from multithreaded benchmarks suites (PARSEC and Phoenix) shows reasonable provenance overheads for a majority of applications. Lastly, we briefly describe three case-studies where the generic interface exported by Inspector is being used to improve the dependability, security, and efficiency of systems. The Inspector library is publicly available for further use in a wide range of other provenance workflows.Comment: 13 page

McFly: Time-Travel Debugging for the Web

Time-traveling debuggers offer the promise of simplifying debugging by letting developers freely step forwards and backwards through a program's execution. However, web applications present multiple challenges that make time-travel debugging especially difficult. A time-traveling debugger for web applications must accurately reproduce all network interactions, asynchronous events, and visual states observed during the original execution, both while stepping forwards and backwards. This must all be done in the context of a complex and highly multithreaded browser runtime. At the same time, to be practical, a time-traveling debugger must maintain interactive speeds. This paper presents McFly, the first time-traveling debugger for web applications. McFly departs from previous approaches by operating on a high-level representation of the browser's internal state. This approach lets McFly provide accurate time-travel debugging - maintaining JavaScript and visual state in sync at all times - at interactive speeds. McFly's architecture is browser-agnostic, building on web standards supported by all major browsers. We have implemented McFly as an extension to the Microsoft Edge web browser, and core parts of McFly have been integrated into a time-traveling debugger product from Microsoft

Spectrum-based Software Fault Localization: A Survey of Techniques, Advances, and Challenges

Despite being one of the most basic tasks in software development, debugging is still performed in a mostly manual way, leading to high cost and low performance. To address this problem, researchers have studied promising approaches, such as Spectrum-based Fault Localization (SFL) techniques, which pinpoint program elements more likely to contain faults. This survey discusses the state-of-the-art of SFL, including the different techniques that have been proposed, the type and number of faults they address, the types of spectra they use, the programs they utilize in their validation, the testing data that support them, and their use at industrial settings. Notwithstanding the advances, there are still challenges for the industry to adopt these techniques, which we analyze in this paper. SFL techniques should propose new ways to generate reduced sets of suspicious entities, combine different spectra to fine-tune the fault localization ability, use strategies to collect fine-grained coverage levels from suspicious coarser levels for balancing execution costs and output precision, and propose new techniques to cope with multiple-fault programs. Moreover, additional user studies are needed to understand better how SFL techniques can be used in practice. We conclude by presenting a concept map about topics and challenges for future research in SFL.Comment: Submitted to Software Testing, Verification and Reliabilit

On Failure Diagnosis of the Storage Stack

Diagnosing storage system failures is challenging even for professionals. One example is the "When Solid State Drives Are Not That Solid" incident occurred at Algolia data center, where Samsung SSDs were mistakenly blamed for failures caused by a Linux kernel bug. With the system complexity keeps increasing, such obscure failures will likely occur more often. As one step to address the challenge, we present our on-going efforts called X-Ray. Different from traditional methods that focus on either the software or the hardware, X-Ray leverages virtualization to collects events across layers, and correlates them to generate a correlation tree. Moreover, by applying simple rules, X-Ray can highlight critical nodes automatically. Preliminary results based on 5 failure cases shows that X-Ray can effectively narrow down the search space for failures

Scientific Software Engineering in a Nutshell

Writing complex computer programs to study scientific problems requires careful planning and an in-depth knowledge of programming languages and tools. In this chapter the importance of using the right tool for the right problem is emphasized. Common tools to organize computer programs, as well as to debug and improve them are discussed, followed by simple data reduction strategies and visualization tools. Furthermore, some useful scientific libraries such as boost, GSL, LEDA and numerical recipes are outlined.Comment: lecture at the second international summer school "Modern Computation Science", 9 - 20 August 2010, Oldenburg (Germany), see http://www.mcs.uni-oldenburg.d

SONATA: Service Programming and Orchestration for Virtualized Software Networks

In conventional large-scale networks, creation and management of network services are costly and complex tasks that often consume a lot of resources, including time and manpower. Network softwarization and network function virtualization have been introduced to tackle these problems. They replace the hardware-based network service components and network control mechanisms with software components running on general-purpose hardware, aiming at decreasing costs and complexity of implementing new services, maintaining the implemented services, and managing available resources in service provisioning platforms and underlying infrastructures. To experience the full potential of these approaches, innovative development support tools and service provisioning environments are needed. To answer these needs, we introduce the SONATA architecture, a service programming, orchestration, and management framework. We present a development toolchain for virtualized network services, fully integrated with a service platform and orchestration system. We motivate the modular and flexible architecture of our system and discuss its main components and features, such as function- and service-specific managers that allow fine- grained service management, slicing support to facilitate multi-tenancy, recursiveness for improved scalability, and full-featured DevOps support