Section: New Results

Dynamic Languages: Debugging

Sindarin: A Versatile Scripting API for the Pharo Debugger Debugging is one of the most important and time consuming activities in software maintenance, yet mainstream debuggers are not well-adapted to several debugging scenarios. This has led to the research of new techniques covering specific families of complex bugs. Notably, recent research proposes to empower developers with scripting DSLs, plugin-based and moldable debuggers. However, these solutions are tailored to specific use-cases, or too costly for one-time-use scenarios. We argue that exposing a debugging scripting interface in mainstream debuggers helps in solving many challenging debugging scenarios. For this purpose, we present Sindarin, a scripting API that eases the expression and automation of different strategies developers pursue during their debugging sessions. Sindarin provides a GDB-like API, augmented with AST-bytecode-source code mappings and object-centric capabilities. To demonstrate the versatility of Sindarin, we reproduce several advanced breakpoints and non-trivial debugging mechanisms from the literature. [4]

Challenges in Debugging Bootstraps of Reflective Kernels The current explosion of embedded systems (i.e., IoT, Edge Computing) implies the need for generating tailored and customized software for these systems. Instead of using specific runtimes (e.g., MicroPython, eLua, mRuby), we advocate that bootstrapping specific language kernels is a promising higher-level approach because the process takes advantage of the generated language abstractions, easing the task for a language developer. Nevertheless, bootstrapping language kernels is still challenging because current debugging tools are not suitable for fixing the possible failures that occur during the process. We take the Pharo bootstrap process as an example to analyse the different challenges a language developer faces. We propose a taxonomy of failures appearing during bootstrap and their causes. Based on this analysis, we identify future research directions: (1) prevention measures based on the reification of implicit virtual machine contracts, and (2) hybrid debugging tools that unify the debugging of high-level code from the bootstrapped language with low-level code from the virtual machine. [6]