Programming Abstractions with Debugging Support for Resource-Constrained Devices

Abstractions are crucial in order to manage complex systems. In pervasive computing, though, common programming abstractions tend to be too expensive for the employed resource-constrained devices. In recent years, the wireless sensor network community has proposed several solutions to this problem. However, little has been done to also support debugging on the level of the abstraction. Instead, a developer is forced to understand the lower-level details in order to find and correct defects. This clearly hampers the development of applications. We aim at advancing the state of the art in programming of resource-constrained devices by introducing debugging support for programming abstractions.

Meta-Debugging Pervasive Computers

As computers get more complex, the task of programming them gets more complex as well. This is especially true for the "Pervasive Computer", which is a massively distributed system consisting of unreliable embedded devices that communicate with each other over lousy wireless links. A common approach to address the programming problem is to offer programming abstractions that hide certain aspects of the complexity from the programmer. While several such abstractions and mappings thereof to low-level target languages have been proposed, there is a glaring lack of debugging support. It is typically impossible to debug at the conceptual level offered by the programming abstractions, instead one has to resort to debugging the generated target code. In this position paper we argue that programming abstractions should be designed in a way that allows debugging at the same conceptual level as programming. We further present requirements for such debugging tools, a taxonomy of programming abstractions and discuss debugging challenges, existing solutions, and potential approaches in each class.

meta level debugging

One of the challenges in meta programming is the ability to debug on the meta level. It is not satisfying to have to step through the generated code in order to figure out what is wrong in the model. And indeed many meta programming toolchains have poor support for proper debugging.

But wait, this problem has in principle actually been solved since ages. When we reduce meta programming to code transformation and realize that a C compiler in that sense is a code transformer this becomes apparent. Almost nobody steps through the assembler code in order to find a bug in the C source. Instead the toolchain has support for so called source level debugging, which is exactly what we want: debugging on the meta level. So it seams advisable to understand the concepts of source level debugging so that we can copy or adapt them to meta programming. That's why I decided to explore the GCC and the GDB together with its graphical frontend DDD which are the tools I am most familiar with.