Relevant bibliographies by topics / Debugging tools

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Debugging tools'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "Debugging tools"

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Etkin, J., and J. A. Zinky. "Distributed debugging: Network analysis tools." Microprocessing and Microprogramming 25, no. 1-5 (1989): 307–12. http://dx.doi.org/10.1016/0165-6074(89)90213-5.

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Law, Rob. "An overview of debugging tools." ACM SIGSOFT Software Engineering Notes 22, no. 2 (1997): 43–47. http://dx.doi.org/10.1145/251880.251926.

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Rountree, Barry, Todd Gamblin, Bronis R. de Supinski, et al. "Parallelizing heavyweight debugging tools with mpiecho." Parallel Computing 39, no. 3 (2013): 156–66. http://dx.doi.org/10.1016/j.parco.2012.11.002.

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Conlon, T., and S. Gregory. "Debugging Tools for Concurrent Logic Programming." Computer Journal 35, no. 2 (1992): 157–69. http://dx.doi.org/10.1093/comjnl/35.2.157.

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Brna, Paul, Mike Brayshaw, Alan Bundy, Mark Elsom-Cook, Pat Fung, and Tony Dodd. "An overview of Prolog debugging tools." Instructional Science 20, no. 2-3 (1991): 193–214. http://dx.doi.org/10.1007/bf00120882.

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Shu, Ji Shi, and Yuan Sheng Liu. "Test Methods Research and Verify for FPGA." Advanced Materials Research 760-762 (September 2013): 867–71. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.867.

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This paper mainly introduces the principle and usage of dynamic probe technology, and makes comparisons between traditional test method and the most popular debugging methodutilizes the embedded tool of debugging on chip to debug. The research depends on self-designed FPGA test service system based on dynamic probe technology. It also explores how to use existent tools and technology for high efficiency test method in FPGA debug and verify process. Through comparisons, it is possible conclude that dynamic probe technology is able to cope with the complex test requirements, and provide more accurate sampling data than the general method in the debugging process. More importantly, the dynamic probe can complete switching a group of the internal signal to be measured within a few seconds, which greatly reducing the waiting time of debugging.
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Vassilev, Martin, Vassil Vassilev, and Alexander Penev. "IDD – A Platform Enabling Differential Debugging." Cybernetics and Information Technologies 20, no. 1 (2020): 53–67. http://dx.doi.org/10.2478/cait-2020-0004.

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AbstractDebugging is a very time consuming task which is not well supported by existing tools. The existing methods do not provide tools enabling optimal developers’ productivity when debugging regressions in complex systems. In this paper we describe a possible solution aiding differential debugging. The differential debugging technique performs analysis of the regressed system and identifying the cause of the unexpected behavior by comparing to a previous version of the same system. The prototype, idd, inspects two versions of the executable – a baseline and a regressed version. The interactive debugging session runs side by side both executables and allows to examine and to compare various internal states. The architecture can work with multiple information sources comparing data from different tools. We also show how idd can detect performance regressions using information from third-party performance facilities. We illustrate how in practice we can quickly discover regressions in large systems such as the clang compiler.
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Martonosi, Margaret, Anoop Gupta, and Thomas Anderson. "Effectiveness of trace sampling for performance debugging tools." ACM SIGMETRICS Performance Evaluation Review 21, no. 1 (1993): 248–59. http://dx.doi.org/10.1145/166962.167023.

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Appelbe, William F., and Charles E. McDowell. "Integrating tools for debugging and developing multitasking programs." ACM SIGPLAN Notices 24, no. 1 (1989): 78–88. http://dx.doi.org/10.1145/69215.69223.

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Galatenko, V. A., and K. A. Kostyukhin. "Postmortem Analysis of Baget RTOS Processes." Programmnaya Ingeneria 12, no. 5 (2021): 227–32. http://dx.doi.org/10.17587/prin.12.227-232.

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Despite the best efforts of programmers to create high-quality software, some errors inevitably escape even the most rigorous testing process and are first encountered by end users of the software. When this happens, developers need to quickly understand the reasons for the errors that occurred and eliminate them. Back in 1951, at the dawn of modern computing, Stanley Gill wrote that special attention should be paid to those errors that occur after the program is started, and lead to its termination. Gill is considered the founder of the so-called postmortem debugging, when a program or system is modified to record its state at the time of failure, so that the programmer can later understand what happened and why such a situation occurred. Since then, postmortem debugging technology has been used in many different systems, including all major general-purpose operating systems (OS), as well as specialized OS such as embedded systems and real-time systems. To ensure the high level of reliability expected from such critical systems, it is necessary, on the one hand, to implement the possibility of rapid recovery of the system or its part after a failure. On the other hand, it is necessary to provide a mechanism for storing as much information as possible after each failure, so that the cause of its occurrence can be determined later. To understand the real potential of postmortem debugging tools, we will first consider the current state of debugging methods and the role of postmortem analysis tools, as well as the requirements for postmortem debugging tools for critical systems. Next, we will describe the mechanism of postmortem debugging implemented by the authors in the RTOS Baget and formulate tasks for further development.
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Dissertations / Theses on the topic "Debugging tools"

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Müller, Thomas. "OpenAFS: Debugging-Methoden und -Tools." Universitätsbibliothek Chemnitz, 2002. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-200201181.

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Unterlagen zu einem Vortrag im Rahmen des AFS-Workshops 2002 an der ETH Zürich. Gegenstand der Vortrags sind Tools zum Debugging und zur Analyse des Verhaltens von AFS-Servern und -Clients. Die meisten dieser Tools sind im Source-Baum von OpenAFS enthalten, jedoch kaum dokumentiert.
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Brickner, Hans. "A research on debugging tools’ platform independency." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-37231.

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Debugging of embedded systems is costly and time consuming,but imperative to system design. There are many different requirements on embedded systems and complying with these requirements has lead to many different kinds, and different configurations of embedded systems. The vast array of embedded systems, and the ever increasing complexity of the systems make debugging a growing challenge. Different domains impose different requirements on the systems and as embedded system pervade in our society, new requirement are introduced. ENEA’s products target various domains as: telecom, medical and the automotive domain. Targeting these three domains means that ENEA’s products need to comply with various, and stringent requirements. A debugging tool used in a tool chain like the tool chain developed in the iFEST project, as intended for ENEA’s debugging tool Optima, needs to support various debugging methods, ranging from software debugging methods to methods utilizing embedded hardware for debugging. The need for debugging tools in a tool chain to support various debugging methods lead to this master’s thesis, at and for ENEA. This thesis investigates methods to debug embedded systems in order to define enhancements of the debugging tool Optima that enables Optima to debug various systems and to debug all systems in ENEA’s target domains. The thesis is divided into two parts: a pre-study and a development part. The pre-study covers debugging of embedded systems by studying articles and ENEA’s operating system OSE and debugging tool Optima. Conclusion drawn from the study of methods to debug embedded systems and the study of the debugging support in Optima, show that Optima needs to utilize embedded hardware for debugging. Updates for Optima that enable utilization of embedded hardware for debugging are designed and implemented in the development part of the thesis. Hardware debugging facilities in the development platform targeted in this thesis are not fully incorporated. The lack of hardware debugging support in the platform makes it infeasible to debug the platform from software running on the processor core, and thus infeasible to improve Optima’s debugging capability by enhancing standard OSE debugging facilities to utilize embedded hardware for debugging. An external debugging tool, JTAG, is required to access the embedded debugging hardware in the target platform and to enable non-intrusive debugging.
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Searle, Aaron James. "Automatic relative debugging." Queensland University of Technology, 2006. http://eprints.qut.edu.au/16445/.

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Relative Debugging is a paradigm that assists users to locate errors in programs that have been corrected or enhanced. In particular, the contents of key data structures in the development version are compared with the contents of the corresponding data structures, in an existing version, as the two programs execute. If the values of two corresponding data structures differ at points where they should not, an error may exist and the user is notified. Relative Debugging requires users to identify the corresponding data structures within the two programs, and the locations at which the comparisons should be performed. To quickly and effectively identify useful data structures and comparison points requires that users have a detailed knowledge of the two programs under consideration. Without a detailed knowledge of the two programs, the task of locating useful data structures and comparison points can quickly become a difficult and time consuming process. Prior to the research detailed in this thesis, the Relative Debugging paradigm did not provide any assistance that allowed users to quickly and effectively identify suitable data structures and program points that will help discover the source of an error. Our research efforts have been directed at enhancing the Relative Debugging paradigm. The outcome of this research is the discovery of techniques that empower Relative Debugging users to become more productive and allow the Relative Debugging paradigm to be significantly enhanced. Specifically, the research has resulted in the following three contributions: 1. A Systematic Approach to Relative Debugging. 2. Data Flow Browsing for Relative Debugging. 3. Automatic Relative Debugging. These contributions have enhanced the Relative Debugging paradigm and allow errors to be localized with little human interaction. Minimizing the user's involvement reduces the cost of debugging programs that have been corrected or enhanced, and has a significant impact on current debugging practices.
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Woods, John Heath. "AN ASSESSMENT OF TOOLS TO ASSIST NEW C PROGRAMMERS IN FINDING BUGS." OpenSIUC, 2019. https://opensiuc.lib.siu.edu/theses/2541.

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The C programming language offers a high degree of control and freedom to programmers. This makes it a powerful tool, but it also gives the language a steep learning curve. One difficulty that many new C programmers face is in figuring out how to analyze and debug their code, as well as the output. There exists a variety of tools that can be used to assist in debugging. They can offer aid by identifying certain types of errors and by providing meaningful output that helps the user understand and correct those errors. The following seven debugging tools have been tested and analyzed in order to ascertain when and how each one of them might be most useful: Valgrind, GCC Address Sanitizer, Clang Address Sanitizer, Mtrace, Memwatch, Electric Fence, and Dmalloc. They have been tested using anonymous code submitted by actual students for C programming labs in order to see how many errors, and of which sort, each tool catches. The results of these tests, as well as their implications, are presented here.
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Schöne, Robert, Joseph Schuchart, Thomas Ilsche, and Daniel Hackenberg. "Scalable Tools for Non-Intrusive Performance Debugging of Parallel Linux Workloads." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-156199.

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There is a variety of tools to measure the performance of Linux systems and the applications running on them. However, the resulting performance data is often presented in plain text format or only with a very basic user interface. For large systems with many cores and concurrent threads, it is increasingly difficult to present the data in a clear way for analysis. Moreover, certain performance analysis and debugging tasks require the use of a high-resolution time-line based approach, again entailing data visualization challenges. Tools in the area of High Performance Computing (HPC) have long been able to scale to hundreds or thousands of parallel threads and help finding performance anomalies. We therefore present a solution to gather performance data using Linux performance monitoring interfaces. A combination of sampling and careful instrumentation allows us to obtain detailed performance traces with manageable overhead. We then convert the resulting output to the Open Trace Format (OTF) to bridge the gap between the recording infrastructure and HPC analysis tools. We explore ways to visualize the data by using the graphical tool Vampir. The combination of established Linux and HPC tools allows us to create an interface for easy navigation through time-ordered performance data grouped by thread or CPU and to help users find opportunities for performance optimizations.
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Schöne, Robert, Joseph Schuchart, Thomas Ilsche, and Daniel Hackenberg. "Scalable Tools for Non-Intrusive Performance Debugging of Parallel Linux Workloads." Ottawa Linux Symposium Comittee, 2014. https://tud.qucosa.de/id/qucosa%3A28410.

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There is a variety of tools to measure the performance of Linux systems and the applications running on them. However, the resulting performance data is often presented in plain text format or only with a very basic user interface. For large systems with many cores and concurrent threads, it is increasingly difficult to present the data in a clear way for analysis. Moreover, certain performance analysis and debugging tasks require the use of a high-resolution time-line based approach, again entailing data visualization challenges. Tools in the area of High Performance Computing (HPC) have long been able to scale to hundreds or thousands of parallel threads and help finding performance anomalies. We therefore present a solution to gather performance data using Linux performance monitoring interfaces. A combination of sampling and careful instrumentation allows us to obtain detailed performance traces with manageable overhead. We then convert the resulting output to the Open Trace Format (OTF) to bridge the gap between the recording infrastructure and HPC analysis tools. We explore ways to visualize the data by using the graphical tool Vampir. The combination of established Linux and HPC tools allows us to create an interface for easy navigation through time-ordered performance data grouped by thread or CPU and to help users find opportunities for performance optimizations.
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Shofahi, Masoud. "Evaluation And Analysis Of Dynamic Memory Debugging Tools For C/C++." Thesis, Umeå universitet, Institutionen för datavetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-155402.

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Memory error can cause a program to behave not as expected or worse, causing the program to halt. The time put into looking for memory errors can instead be invested in solving other project related problems. Developers use dynamic memory debugging tools to save both time and energy, since discovering memory errors could cause costly and time consuming execution errors or faulty results that could be nearly impossibleto discover. This thesis analyzes and evaluates three different open source dynamic memory debugging tools. The study mainly focuses on what type of memory errors the tools are capable of finding and what algorithms and techniques are used by the tools to find the errors.
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Tammana, Praveen Aravind Babu. "Software-defined datacenter network debugging." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31326.

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Software-defined Networking (SDN) enables flexible network management, but as networks evolve to a large number of end-points with diverse network policies, higher speed, and higher utilization, abstraction of networks by SDN makes monitoring and debugging network problems increasingly harder and challenging. While some problems impact packet processing in the data plane (e.g., congestion), some cause policy deployment failures (e.g., hardware bugs); both create inconsistency between operator intent and actual network behavior. Existing debugging tools are not sufficient to accurately detect, localize, and understand the root cause of problems observed in a large-scale networks; either they lack in-network resources (compute, memory, or/and network bandwidth) or take long time for debugging network problems. This thesis presents three debugging tools: PathDump, SwitchPointer, and Scout, and a technique for tracing packet trajectories called CherryPick. We call for a different approach to network monitoring and debugging: in contrast to implementing debugging functionality entirely in-network, we should carefully partition the debugging tasks between end-hosts and network elements. Towards this direction, we present CherryPick, PathDump, and SwitchPointer. The core of CherryPick is to cherry-pick the links that are key to representing an end-to-end path of a packet, and to embed picked linkIDs into its header on its way to destination. PathDump is an end-host based network debugger based on tracing packet trajectories, and exploits resources at the end-hosts to implement various monitoring and debugging functionalities. PathDump currently runs over a real network comprising only of commodity hardware, and yet, can support surprisingly a large class of network debugging problems with minimal in-network functionality. The key contributions of SwitchPointer is to efficiently provide network visibility to end-host based network debuggers like PathDump by using switch memory as a "directory service" - each switch, rather than storing telemetry data necessary for debugging functionalities, stores pointers to end hosts where relevant telemetry data is stored. The key design choice of thinking about memory as a directory service allows to solve performance problems that were hard or infeasible with existing designs. Finally, we present and solve a network policy fault localization problem that arises in operating policy management frameworks for a production network. We develop Scout, a fully-automated system that localizes faults in a large scale policy deployment and further pin-points the physical-level failures which are most likely cause for observed faults.
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Renieris, Emmanuel. "A research framework for software-fault localization tools /." View online version; access limited to Brown University users, 2005. http://wwwlib.umi.com/dissertations/fullcit/3174662.

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Sjölund, Martin. "Tools for Understanding, Debugging, and Simulation Performance Improvement of Equation-based Models." Licentiate thesis, Linköpings universitet, Programvara och system, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-90096.

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Equation-based object-oriented (EOO) modelling languages provide a convenient, declarative method for describing models of cyber-physical systems.Because of the ease of use of EOO languages, large and complex models can be built with limited effort.However, current state-of-the-art tools do not provide the user with enough information when errors appear or simulation results are wrong.It is paramount that the tools give the user enough information to correct errors or understand where the problems that lead to wrong simulation results are located.However, understanding the model translation process of an EOO compiler is a daunting task that not only requires knowledge of the numerical algorithms that the tool executes during simulation, but also the complex symbolic transformations being performed. In this work, we develop and explore methods where the EOO tool records the transformations during the translation process in order to provide better diagnostics, explanations, and analysis.This information can be used to generate better error-messages during translation.It can also be used to provide better debugging for a simulation that produces unexpected results or where numerical methods fail. Meeting deadlines is particularly important for real-time applications.It is usually important to identify possible bottlenecks and either simplify the model or give hints to the compiler that enables it to generate faster code.When profiling and measuring execution times of parts of the model the recorded information can also be used to find out why a particular system is slow.Combined with debugging information, it is possible to find out why this system of equations is slow to solve, which helps understanding what can be done to simplify the model. Finally, we provide a method and tool prototype suitable for speeding up simulations by compiling a simulation executable for a parallel platform by partitioning the model at appropriate places.
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Books on the topic "Debugging tools"

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Palmer, Maurice Martin. High level debugging tools. The Author], 1989.

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Stitt, Martin. Debugging: Creative techniques and tools for software repair. Wiley, 1992.

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Debugging: Creative techniques and tools for software repair. Wiley, 1992.

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Debugging: Creative techniques and tools for software repair. Wiley, 1992.

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Poe, Curtis (Ovid). Perl Hacks: Tips & Tools for Programming, Debugging, and Surviving. Edited by Allison Randal. O’Reilly Media, 2013.

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Using Turbo debugger and tools 2.0. Addison-Wesley, 1991.

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International Workshop on Parallel Tools for High Performance Computing (3rd 2009 Dresden, Germany). Tools for high performance computing 2009: Proceedings of the 3rd International Workshop on Parallel Tools for High Performance Computing, September 2009, ZIH, Dresden. Edited by Müller Matthias S. Springer, 2010.

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Matloff, Norman S. The art of debugging with GDB, DDD, and Eclipse. No Starch Press, 2008.

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Corporation, Toshiba. 4-bit microcontroller TLCS-47E/47/470/470A (debugging tool): Development system manual. Toshiba Corporation, 1993.

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Paul, Miller Barton, ed. Monitoring systems and tool interoperability. Nova Science, 2004.

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Book chapters on the topic "Debugging tools"

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Rothwell, William “Bo.” "Debugging Tools." In Pro Perl Programming. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5605-3_9.

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Pearce, Mark. "Other Debugging Tools." In Comprehensive VB .NET Debugging. Apress, 2003. http://dx.doi.org/10.1007/978-1-4302-0778-8_5.

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D’Souza, Martin Giffy. "Debugging & Tools." In Expert Oracle Application Express Plug-Ins. Apress, 2011. http://dx.doi.org/10.1007/978-1-4302-3504-0_8.

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Egyed, Alexander, Bryan Horling, Raphen Becker, and Robert Balzer. "Visualization and Debugging Tools." In Multiagent Systems, Artificial Societies, and Simulated Organizations. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0363-7_4.

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Hajian, Majid. "Debugging and Measurement Tools." In Progressive Web Apps with Angular. Apress, 2019. http://dx.doi.org/10.1007/978-1-4842-4448-7_10.

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Brinkmann, Steffen, José Gracia, and Christoph Niethammer. "Task Debugging with TEMANEJO." In Tools for High Performance Computing 2012. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37349-7_2.

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Gburzyński, Paweł. "Tools for Testing and Debugging." In Modeling Communication Networks and Protocols. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-15391-5_11.

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Apers, Chris, and Daniel Paterson. "Introducing Developer and Debugging Tools." In Beginning iPhone and iPad Web Apps. Apress, 2010. http://dx.doi.org/10.1007/978-1-4302-3046-5_3.

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Rossi, Mattia, Nicola Toscani, Marco Mauri, and Francesco Castelli Dezza. "Debugging Tools and Firmware Profiling." In Introduction to Microcontroller Programming for Power Electronics Control Applications. CRC Press, 2021. http://dx.doi.org/10.1201/9781003196938-20.

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Kallioinen, Olli, and Tommi Mikkonen. "Debugging Tools for MIDP Java Devices." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29336-8_5.

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Conference papers on the topic "Debugging tools"

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Purcell, Tim. "Debugging tools." In ACM SIGGRAPH 2005 Courses. ACM Press, 2005. http://dx.doi.org/10.1145/1198555.1198773.

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Jin-Gu Kang, Seung-Won Yang, and Jong-Yeol Lee. "Debugging of assembly library functions without target debugging tools." In 2008 13th Asia-Pacific Computer Systems Architecture Conference (ACSAC). IEEE, 2008. http://dx.doi.org/10.1109/apcsac.2008.4625467.

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Pereira da Silva, Fabio. "A study based on TAM model about debugging tools." In Computer on the Beach. Universidade do Vale do Itajaí, 2021. http://dx.doi.org/10.14210/cotb.v12.p020-026.

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Debugging is the task of locating and fixing defects in a program.Despite the increase of its importance in last decades, debuggingis responsible for a large part of costs in a software project by organizations.Among the techniques proposed to minimize thesedifficulties, Spectrum-Based Fault Localization (SFL) is a promisingdebugging technique due to it is relative low execution cost.Recently, visualization tools have been proposed to represent thesuspicious values of program elements with SFL techniques in differentmetaphors. Some tools use textual representation and others avisual representation. In this paper, we compare two SFL debuggingtools. Jaguar presents the most suspicious elements of a programin a list sorted by suspicious values. CodeForest represents the programin a three dimensional cacti forest. In this article are presentedthe results of an evaluation with 119 students to assess the usabilityperception of these tools to the fault localization by TechnologyAcceptance Model (TAM). This model aims to help organizationsduring the evaluation of new technologies. The results of studyshow that Jaguar has greater usability than CodeForest; however,the statistical effect size observed is low between them.
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da Silva, Fabio Pereira, Higor Amario de Souza, and Marcos Lordello Chaim. "Usability evaluation of software debugging tools." In the XIV Brazilian Symposium. ACM Press, 2018. http://dx.doi.org/10.1145/3229345.3229410.

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Rossler, Jeremias. "How helpful are automated debugging tools?" In 2012 User Evaluation for Software Engineering Researchers (USER). IEEE, 2012. http://dx.doi.org/10.1109/user.2012.6226573.

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Nde, Gilbert N., and Rahamatullah Khondoker. "SDN testing and debugging tools: A survey." In 2016 International Conference on Informatics, Electronics and Vision (ICIEV). IEEE, 2016. http://dx.doi.org/10.1109/iciev.2016.7760078.

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Lieberman, Henry, and Earl Wagner. "End-user tools for debugging e-commerce." In the 4th ACM conference. ACM Press, 2003. http://dx.doi.org/10.1145/779928.779983.

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Kebianyor, Bewoayia, Philipp Ittershagen, and Kim Grüttner. "Towards Stateflow Model Aware Debugging with LLDB." In the Rapid Simulation and Performance Evaluation: Methods and Tools. ACM Press, 2019. http://dx.doi.org/10.1145/3300189.3300190.

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Khilko, Dmitry, Yury Stepchenkov, Yury Shikunov, and George Orlov. "Modeling and debugging tools development for recurrent architecture." In 2019 IEEE East-West Design & Test Symposium (EWDTS). IEEE, 2019. http://dx.doi.org/10.1109/ewdts.2019.8884412.

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Martonosi, Margaret, Anoop Gupta, and Thomas Anderson. "Effectiveness of trace sampling for performance debugging tools." In the 1993 ACM SIGMETRICS conference. ACM Press, 1993. http://dx.doi.org/10.1145/166955.167023.

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Reports on the topic "Debugging tools"

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Romao, A. Tools for DNS debugging. RFC Editor, 1994. http://dx.doi.org/10.17487/rfc1713.

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Enger, R., and J. Reynolds. FYI on a Network Management Tool Catalog: Tools for Monitoring and Debugging TCP/IP Internets and Interconnected Devices. RFC Editor, 1993. http://dx.doi.org/10.17487/rfc1470.

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Stine, R. H. FYI on a Network Management Tool Catalog: Tools for Monitoring and Debugging TCP/IP Internets and Interconnected Devices. RFC Editor, 1990. http://dx.doi.org/10.17487/rfc1147.

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