Out-Of-Place debugging: a debugging architecture to reduce debugging interference

Context. Recent studies show that developers spend most of their programming time testing, verifying and debugging software. As applications become more and more complex, developers demand more advanced debugging support to ease the software development process. Inquiry. Since the 70's many debugging solutions were introduced. Amongst them, online debuggers provide a good insight on the conditions that led to a bug, allowing inspection and interaction with the variables of the program. However, most of the online debugging solutions introduce \textit{debugging interference} to the execution of the program, i.e. pauses, latency, and evaluation of code containing side-effects. Approach. This paper investigates a novel debugging technique called \outofplace debugging. The goal is to minimize the debugging interference characteristic of online debugging while allowing online remote capabilities. An \outofplace debugger transfers the program execution and application state from the debugged application to the debugger application, both running in different processes. Knowledge. On the one hand, \outofplace debugging allows developers to debug applications remotely, overcoming the need of physical access to the machine where the debugged application is running. On the other hand, debugging happens locally on the remote machine avoiding latency. That makes it suitable to be deployed on a distributed system and handle the debugging of several processes running in parallel. Grounding. We implemented a concrete out-of-place debugger for the Pharo Smalltalk programming language. We show that our approach is practical by performing several benchmarks, comparing our approach with a classic remote online debugger. We show that our prototype debugger outperforms by a 1000 times a traditional remote debugger in several scenarios. Moreover, we show that the presence of our debugger does not impact the overall performance of an application. Importance. This work combines remote debugging with the debugging experience of a local online debugger. Out-of-place debugging is the first online debugging technique that can minimize debugging interference while debugging a remote application. Yet, it still keeps the benefits of online debugging ( e.g. step-by-step execution). This makes the technique suitable for modern applications which are increasingly parallel, distributed and reactive to streams of data from various sources like sensors, UI, network, etc

A Study of Concurrency Bugs and Advanced Development Support for Actor-based Programs

The actor model is an attractive foundation for developing concurrent applications because actors are isolated concurrent entities that communicate through asynchronous messages and do not share state. Thereby, they avoid concurrency bugs such as data races, but are not immune to concurrency bugs in general. This study taxonomizes concurrency bugs in actor-based programs reported in literature. Furthermore, it analyzes the bugs to identify the patterns causing them as well as their observable behavior. Based on this taxonomy, we further analyze the literature and find that current approaches to static analysis and testing focus on communication deadlocks and message protocol violations. However, they do not provide solutions to identify livelocks and behavioral deadlocks. The insights obtained in this study can be used to improve debugging support for actor-based programs with new debugging techniques to identify the root cause of complex concurrency bugs.Comment: - Submitted for review - Removed section 6 "Research Roadmap for Debuggers", its content was summarized in the Future Work section - Added references for section 1, section 3, section 4.3 and section 5.1 - Updated citation

Debugging real-time software in a host-target environment

A common paradigm for the development of process-control or embedded computer software is to do most of the implementation and testing on a large host computer, then retarget the code for final checkout and production execution on the target machine. The host machine is usually large and provides a variety of program development tools, while the target may be a small, bare machine. A difficulty with the paradigm arises when the software developed has real-time constraints and is composed of multiple communicating processes. If a test execution on the target fails, it may be exceptionally tedious to determine the cause of the failure. Host machine debuggers cannot normally be applied, because the same program processing the same data will frequently exhibit different behavior on the host. Differences in processor speed, scheduling algorithm, and the like, account for the disparity. This paper proposes a partial solution to this problem, in which the errant execution reconstructed and made amenable to source language level debugging on the host. The solution involves the integrated application of a static concurrency analyzer, an interactive interpreter, and a graphical program visualization aid. Though generally applicable, the solution is described here in the context of multi-tasked real-time Ada* programs

Arcadia, a software development environment research project

The research objectives of the Arcadia project are two-fold: discovery and development of environment architecture principles and creation of novel software development tools, particularly powerful analysis tools, which will function within an environment built upon these architectural principles.Work in the architecture area is concerned with providing the framework to support integration while also supporting the often conflicting goal of extensibility. Thus, this area of research is directed toward achieving external integration by providing a consistent, uniform user interface, while still admitting customization and addition of new tools and interface functions. In an effort to also attain internal integration, research is aimed at developing mechanisms for structuring and managing the tools and data objects that populate a software development environment, while facilitating the insertion of new kinds of tools and new classes of objects.The unifying theme of work in the tools area is support for effective analysis at every stage of a software development project. Research is directed toward tools suitable for analyzing pre-implementation descriptions of software, software itself, and towards the production of testing and debugging tools. In many cases, these tools are specifically tailored for applicability to concurrent, distributed, or real-time software systems.The initial focus of Arcadia research is on creating a prototype environment, embodying the architectural principles, which supports Ada1 software development. This prototype environment is itself being developed in Ada.Arcadia is being developed by a consortium of researchers from the University of California at Irvine, the University of Colorado at Boulder, the University of Massachusetts at Amherst, TRW, Incremental Systems Corporation, and The Aerospace Corporation. This paper delineates the research objectives and describes the approaches being taken, the organization of the research endeavor, and current status of the work

CONTEXT-AWARE DEBUGGING FOR CONCURRENT PROGRAMS

Concurrency faults are difficult to reproduce and localize because they usually occur under specific inputs and thread interleavings. Most existing fault localization techniques focus on sequential programs but fail to identify faulty memory access patterns across threads, which are usually the root causes of concurrency faults. Moreover, existing techniques for sequential programs cannot be adapted to identify faulty paths in concurrent programs. While concurrency fault localization techniques have been proposed to analyze passing and failing executions obtained from running a set of test cases to identify faulty access patterns, they primarily focus on using statistical analysis. We present a novel approach to fault localization using feature selection techniques from machine learning. Our insight is that the concurrency access patterns obtained from a large volume of coverage data generally constitute high dimensional data sets, yet existing statistical analysis techniques for fault localization are usually applied to low dimensional data sets. Each additional failing or passing run can provide more diverse information, which can help localize faulty concurrency access patterns in code. The patterns with maximum feature diversity information can point to the most suspicious pattern. We then apply data mining technique and identify the interleaving patterns that are occurred most frequently and provide the possible faulty paths. We also evaluate the effectiveness of fault localization using test suites generated from different test adequacy criteria. We have evaluated Cadeco on 10 real-world multi-threaded Java applications. Results indicate that Cadeco outperforms state-of-the-art approaches for localizing concurrency faults

A study of systems implementation languages for the POCCNET system

The results are presented of a study of systems implementation languages for the Payload Operations Control Center Network (POCCNET). Criteria are developed for evaluating the languages, and fifteen existing languages are evaluated on the basis of these criteria