Confessions of a live coder

This paper describes the process involved when a live coder decides to learn a new musical programming language of another paradigm. The paper introduces the problems of running comparative experiments, or user studies, within the field of live coding. It suggests that an autoethnographic account of the process can be helpful for understanding the technological conditioning of contemporary musical tools. The author is conducting a larger research project on this theme: the part presented in this paper describes the adoption of a new musical programming environment, Impromptu, and how this affects the author’s musical practice

Better Sooner Rather Than Later

This article unifies and generalizes fundamental results related to $n$-process asynchronous crash-prone distributed computing. More precisely, it proves that for every $0\leq k \leq n$, assuming that process failures occur only before the number of participating processes bypasses a predefined threshold that equals $n-k$ (a participating process is a process that has executed at least one statement of its code), an asynchronous algorithm exists that solves consensus for $n$ processes in the presence of $f$ crash failures if and only if $f \leq k$. In a very simple and interesting way, the "extreme" case $k=0$ boils down to the celebrated FLP impossibility result (1985, 1987). Moreover, the second extreme case, namely $k=n$, captures the celebrated mutual exclusion result by E.W. Dijkstra (1965) that states that mutual exclusion can be solved for $n$ processes in an asynchronous read/write shared memory system where any number of processes may crash (but only) before starting to participate in the algorithm (that is, participation is not required, but once a process starts participating it may not fail). More generally, the possibility/impossibility stated above demonstrates that more failures can be tolerated when they occur earlier in the computation (hence the title).Comment: 10 page

The open source dynamics in geospatial research and education

Peer reviewing is one of the core processes of science. While the typical blind system helps to improve original submissions, there are opportunities for academic publishing to learn from open source practices (commits, bug reports, feature requests, documentation, etc.), which are entirely open and done in public view. But beyond, with greater significance, peer reviewing offers a good opportunity to illustrate how the characteristics of the open source model can favor simultaneously the acknowledgment of programming efforts, a high quality evaluation standard, but also reproducibility and transparency. Code has to be considered as a full research object in geospatial development. It should be made available in full and examined as part of any contribution, like the article going with it. A good example is the Journal of Statistical Software. Created in 1996, it publishes articles and code on statistics and algorithms. The contents are freely available on-line, code snippets and source code being published along with the paper. An advantage of this approach is to prevent the propagation of “black boxes”. The approach clearly also adds value to code by acknowledging programming efforts as scientific contributions. But publishing code along with a paper also results in the ability of subsequent research projects to build on this basis. This ability is even becoming a requirement for publicly funded research projects. In addition, we may notice that code malleability provides the researcher with the opportunity to adapt the software to the scientific questions, instead of being constrained by the limiting functionalities of the software. As regards education, there are two key freedoms inherent to open source software and practices that offer potential pedagogical wins for geospatial education. First, “free as in beer” allows students to indefinitely install software on computers without license limitations. A consequence of this unconstrained context is a greater degree of exploration and discovery by the students working by themselves and at their own pace. But there is still a long way to go before all the benefits are fully realized. Indeed, current demands and offerings are focusing on “buttonology”, which consists of learning how to use tools constrained by software licenses carefully negotiated over the years by universities. It raises then some important questions regarding the role of geospatial education. Is it not to train students to equip them with the skill sets and knowledge so that they are ready for, and can create, the future geospatial labor market? Therein, we can consider the second freedom, “free as in speech,” as able to empower the students by revealing the logic of particular algorithms and computational concepts. Open source code—as text—is available for reading, manipulating, and understanding. The expected advantage is that students’ engagement with fundamental concepts is deepened in a way that is per se not possible with closed source software. In other words, students come to see geospatial methods not only as tools they can use in their own research, but as possible subjects for research