Dartmouth Symposium on the Future of Computer Music Software: A Panel Discussion

Transcript of a Panel Discussion at the Dartmouth Symposium, chaired by Eric Lyon.

Towards an understanding of the causes and effects of software requirements change: two case studies

Changes to software requirements not only pose a risk to the successful delivery of software applications but also provide opportunity for improved usability and value. Increased understanding of the causes and consequences of change can support requirements management and also make progress towards the goal of change anticipation. This paper presents the results of two case studies that address objectives arising from that ultimate goal. The first case study evaluated the potential of a change source taxonomy containing the elements ‘market’, ‘organisation’, ‘vision’, ‘specification’, and ‘solution’ to provide a meaningful basis for change classification and measurement. The second case study investigated whether the requirements attributes of novelty, complexity, and dependency correlated with requirements volatility. While insufficiency of data in the first case study precluded an investigation of changes arising due to the change source of ‘market’, for the remainder of the change sources, results indicate a significant difference in cost, value to the customer and management considerations. Findings show that higher cost and value changes arose more often from ‘organisation’ and ‘vision’ sources; these changes also generally involved the co-operation of more stakeholder groups and were considered to be less controllable than changes arising from the ‘specification’ or ‘solution’ sources. Results from the second case study indicate that only ‘requirements dependency’ is consistently correlated with volatility and that changes coming from each change source affect different groups of requirements. We conclude that the taxonomy can provide a meaningful means of change classification, but that a single requirement attribute is insufficient for change prediction. A theoretical causal account of requirements change is drawn from the implications of the combined results of the two case studies.

Software-defined sphere decoding for FPGA-based MIMO detection

Sphere Decoding (SD) is a highly effective detection technique for Multiple-Input Multiple-Output (MIMO) wireless communications receivers, offering quasi-optimal accuracy with relatively low computational complexity as compared to the ideal ML detector. Despite this, the computational demands of even low-complexity SD variants, such as Fixed Complexity SD (FSD), remains such that implementation on modern software-defined network equipment is a highly challenging process, and indeed real-time solutions for MIMO systems such as 4 4 16-QAM 802.11n are unreported. This paper overcomes this barrier. By exploiting large-scale networks of fine-grained softwareprogrammable processors on Field Programmable Gate Array (FPGA), a series of unique SD implementations are presented, culminating in the only single-chip, real-time quasi-optimal SD for 44 16-QAM 802.11n MIMO. Furthermore, it demonstrates that the high performance software-defined architectures which enable these implementations exhibit cost comparable to dedicated circuit architectures.

Reproductive biomass in Holcus lanatus clones that differ in their phosphate uptake kinetics and mycorrhizal colonization

In normal populations of the common grass Holcus lanatus there is a polymorphism for arsenate resistance, manifested as suppressed phosphate uptake (SPU), and controlled by a major gene with dominant expression. A natural population of SPU plants had greater arbuscular-mycorrhizal colonization than wild type, nonSPU plants. It was hypothesized that, in order to survive alongside plants with a normal rate of phosphate (P) uptake, SPU plants would be more dependent on mycorrhizal associations. We performed an experiment using plants with SPU phenotypes from both arsenate mine spoils and uncontaminated soils, as well as plants with a nonSPU phenotype. They were grown with and without a mycorrhizal inoculum and added N, which altered plant P requirements. We showed that grasses with SPU phenotypes accumulated more shoot P than nonSPU plants, the opposite of the expected result. SPY plants also produced considerably more flower panicles, and had greater shoot and root biomass. The persistence of SPU phenotypes in normal populations is not necessarily related to mycorrhizal colonization as there were no differences in percentage AM colonization between the phenotypes. Being mycorrhizal reduced flower biomass production, as mycorrhizal SPU plants had lower shoot P concentrations and produced fewer flower panicles than non-mycorrhizal, nonSPU plants. We now hypothesize that the SPU phenotype is brought about by a genotype that results in increased accumulation of P in shoots, and that suppression of the rate of uptake is a consequence of this high shoot P concentration, operating by means of a homeostatic feedback mechanism. We also postulate that increased flower production is linked to a high shoot P concentration. SPU plants thus allocate more resources into seed production, leading to a higher frequency of SPU genes. Increased reproductive allocation reduces vegetative allocation and may affect competitive ability and hence survival, explaining the maintenance of the polymorphism. As mycorrhizal SPU plants behave more like nonSPU plants, AM colonization itself could play a major part in the maintenance of the SPU polymorphism.

Techniques and tools for parallelizing software

With the emergence of multicore and manycore processors, engineers must design and develop software in drastically new ways to benefit from the computational power of all cores. However, developing parallel software is much harder than sequential software because parallelism can't be abstracted away easily. Authors Hans Vandierendonck and Tom Mens provide an overview of technologies and tools to support developers in this complex and error-prone task. © 2012 IEEE.