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"Debugging"
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Locating faults with program slicing: an empirical analysis
Statistical fault localization is an easily deployed technique for quickly determining candidates for faulty code locations. If a human programmer has to search the fault beyond the top candidate locations, though, more traditional techniques of following dependencies along dynamic slices may be better suited. In a large study of 457 bugs (369 single faults and 88 multiple faults) in 46 open source C programs, we compare the effectiveness of statistical fault localization against dynamic slicing. For single faults, we find that dynamic slicing was eight percentage points more effective than the best performing statistical debugging formula; for 66% of the bugs, dynamic slicing finds the fault earlier than the best performing statistical debugging formula. In our evaluation, dynamic slicing is more effective for programs with single fault, but statistical debugging performs better on multiple faults. Best results, however, are obtained by a hybrid approach: If programmers first examine at most the top five most suspicious locations from statistical debugging, and then switch to dynamic slices, on average, they will need to examine 15% (30 lines) of the code. These findings hold for 18 most effective statistical debugging formulas and our results are independent of the number of faults (i.e. single or multiple faults) and error type (i.e. artificial or real errors).
Journal Article
Pro Python best practices : debugging, testing and maintenance
Learn software engineering and coding best practices to write Python code right and error free. In this book you'll see how to properly debug, organize, test, and maintain your code, all of which leads to better, more efficient coding.
Book
Upstream bug management in Linux distributions
A Linux distribution consists of thousands of packages that are either developed by in-house developers (in-house packages) or by external projects (upstream packages). Leveraging upstream packages speeds up development and improves productivity, yet bugs might slip through into the packaged code and end up propagating into downstream Linux distributions. Maintainers, who integrate upstream projects into their distribution, typically lack the expertise of the upstream projects. Hence, they could try either to propagate the bug report upstream and wait for a fix, or fix the bug locally and maintain the fix until it is incorporated upstream. Both of these outcomes come at a cost, yet, to the best of our knowledge, no prior work has conducted an in-depth analysis of upstream bug management in the Linux ecosystem. Hence, this paper empirically studies how high-severity bugs are fixed in upstream packages for two Linux distributions, i.e., Debian and Fedora. Our results show that 13.9% of the upstream package bugs are explicitly reported being fixed by upstream, and 13.3% being fixed by the distribution, while the vast majority of bugs do not have explicit information about this in Debian. When focusing on the 27.2% with explicit information, our results also indicate that upstream fixed bugs make users wait for a longer time to get fixes and require more additional information compared to fixing upstream bugs locally by the distribution. Finally, we observe that the number of bug comment links to reference information (e.g., design docs, bug reports) of the distribution itself and the similarity score between upstream and distribution bug reports are important factors for the likelihood of a bug being fixed upstream. Our findings strengthen the need for traceability tools on bug fixes of upstream packages between upstream and distributions in order to find upstream fixes easier and lower the cost of upstream bug management locally.
Journal Article
Debugging Nano–Bio Interfaces: Systematic Strategies to Accelerate Clinical Translation of Nanotechnologies
Despite considerable efforts in the field of nanomedicine that have been made by researchers, funding agencies, entrepreneurs, and the media, fewer nanoparticle (NP) technologies than expected have made it to clinical trials. The wide gap between the efforts and effective clinical translation is, at least in part, due to multiple overlooked factors in both in vitro and in vivo environments, a poor understanding of the nano–bio interface, and misinterpretation of the data collected in vitro, all of which reduce the accuracy of predictions regarding the NPs’ fate and safety in humans. To minimize this bench-to-clinic gap, which may accelerate successful clinical translation of NPs, this opinion paper aims to introduce strategies for systematic debugging of nano–bio interfaces in the current literature.
Critical information on nano–bio interfaces (e.g., biomolecular corona) and cells, including their sex, type, size, and passage number, should be considered.
Standardization communities should propose standard units for nanoparticle dosage.
Mathematical and computational approaches should be developed to define underlying mechanisms at the nano–bio interfaces.
Interlaboratory comparison of characterization of nanoparticles, nano–bio interfaces, nanotoxicities, therapeutic efficacies, and others should be conducted to prevent conflicts produced by different instruments.
Researchers, various well-established laboratories, funding agencies, entrepreneurs, and the media should work closely to prepare reliable and precise data sets, not only to prevent further clutter in the nanomedicine literature but also to accelerate successful clinical translation of nanomedicine.
Journal Article
GenProg: A Generic Method for Automatic Software Repair
This paper describes GenProg, an automated method for repairing defects in off-the-shelf, legacy programs without formal specifications, program annotations, or special coding practices. GenProg uses an extended form of genetic programming to evolve a program variant that retains required functionality but is not susceptible to a given defect, using existing test suites to encode both the defect and required functionality. Structural differencing algorithms and delta debugging reduce the difference between this variant and the original program to a minimal repair. We describe the algorithm and report experimental results of its success on 16 programs totaling 1.25 M lines of C code and 120K lines of module code, spanning eight classes of defects, in 357 seconds, on average. We analyze the generated repairs qualitatively and quantitatively to demonstrate that the process efficiently produces evolved programs that repair the defect, are not fragile input memorizations, and do not lead to serious degradation in functionality.
Journal Article
Visual Studio code : end-to-end editing and debugging tools for web developers
The choice of a code editor is an important one for any web developer. Visual Studio Code, the free and open-source editor from Microsoft has swiftly become a favorite in the coding community. It provides all the basics in a lightweight package and adds a number of features that set it apart from other editors. Whether you are new to the program or are already a user, Visual Studio Code will equip you with a thorough knowledge of the out-of-the-box functionality and the available extensions for your cross-platform code editor of choice. This book is appropriate for developers using Visual Studio Code on Windows, Mac, or Unix, and guides you through the installation process for each platform. A detailed inventory of features, follows the development workflow, so you can follow along with this book to set up your workspace, project files, code editing tools, and source control integration as you go. Additionally, Visual Studio Code guides you through the extensibility features of the code editor, so you can locate and install key extension from additional language support to useful new functionality. Finally, this book will show you how to create your own extensions to make Visual Studio Code exactly what you need your code editor to be. Visual Studio Code is an essential guide to: Navigating and customizing the workspace ; Editing code in your language of choice using syntax coloring, refactoring support, and other productivity-enhancing features ; Choosing and implementing a file structure appropriate to your needs.
Book
A fast on-chip debugging design for RISC-V processor
In order to improve the efficiency of on-chip debugging, a fast on-chip debugging design is proposed, which adopts JTAG interface and is applied in RISC-V processor. In this paper, we extend some debugging instructions, effectively reducing data entry by operating the debugging bus directly, and realize the breakpoint, pause, single step, et al., providing conveniences for the development and debugging of the software system.
Journal Article