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.

Selective Orthosteric Free Fatty Acid Receptor 2 (FFA2) Agonists IDENTIFICATION OF THE STRUCTURAL AND CHEMICAL REQUIREMENTS FOR SELECTIVE ACTIVATION OF FFA2 VERSUS FFA3

Free fatty acid receptor 2 (FFA2; GPR43) is a G protein-coupled seven-transmembrane receptor for short-chain fatty acids (SCFAs) that is implicated in inflammatory and metabolic disorders. The SCFA propionate has close to optimal ligand efficiency for FFA2 and can hence be considered as highly potent given its size. Propionate, however, does not discriminate between FFA2 and the closely related receptor FFA3 (GPR41). To identify FFA2-selective ligands and understand the molecular basis for FFA2 selectivity, a targeted library of small carboxylic acids was examined using holistic, label-free dynamic mass redistribution technology for primary screening and the receptor-proximal G protein [S-35] guanosine 5'-(3-O-thio) triphosphate activation, inositol phosphate, and cAMP accumulation assays for hit confirmation. Structure-activity relationship analysis allowed formulation of a general rule to predict selectivity for small carboxylic acids at the orthosteric binding site where ligands with substituted sp(3)-hybridized alpha-carbons preferentially activate FFA3, whereas ligands with sp(2)- or sp-hybridized alpha-carbons prefer FFA2. The orthosteric binding mode was verified by site-directed mutagenesis: replacement of orthosteric site arginine residues by alanine in FFA2 prevented ligand binding, and molecular modeling predicted the detailed mode of binding. Based on this, selective mutation of three residues to their non-conserved counterparts in FFA3 was sufficient to transfer FFA3 selectivity to FFA2. Thus, selective activation of FFA2 via the orthosteric site is achievable with rather small ligands, a finding with significant implications for the rational design of therapeutic compounds selectively targeting the SCFA receptors.

Evolutionary Requirements for Next-Generation Dataflow-Based FPGA System Design

The use of dataflow digital signal processing system modelling
and synthesis techniques has been a fruitful research theme for many years and has yielded many powerful rapid system synthesis and optimisation capabilities. However, recent years have seen the spectrum of languages and techniques splinter in an application specific manner, resulting in an ad-hoc design process which is increasingly dependent on the particular application under development. This poses a major problem for automated toolflows attempting to provide rapid system synthesis for a wide ranges of applications. By analysing a number of dataflow FPGA implementation case studies, this paper shows that despit ethis common traits may be found in current techniques, which fall largely into three classes. Further, it exposes limitations pertaining to their ability to adapt algorith models to implementations for different operating environments and target platforms.

Strategies for Energy-Efficient Resource Management of Hybrid Programming Models

Many scientific applications are programmed using hybrid programming models that use both message passing and shared memory, due to the increasing prevalence of large-scale systems with multicore, multisocket nodes. Previous work has shown that energy efficiency can be improved using software-controlled execution schemes that consider both the programming model and the power-aware execution capabilities of the system. However, such approaches have focused on identifying optimal resource utilization for one programming model, either shared memory or message passing, in isolation. The potential solution space, thus the challenge, increases substantially when optimizing hybrid models since the possible resource configurations increase exponentially. Nonetheless, with the accelerating adoption of hybrid programming models, we increasingly need improved energy efficiency in hybrid parallel applications on large-scale systems. In this work, we present new software-controlled execution schemes that consider the effects of dynamic concurrency throttling (DCT) and dynamic voltage and frequency scaling (DVFS) in the context of hybrid programming models. Specifically, we present predictive models and novel algorithms based on statistical analysis that anticipate application power and time requirements under different concurrency and frequency configurations. We apply our models and methods to the NPB MZ benchmarks and selected applications from the ASC Sequoia codes. Overall, we achieve substantial energy savings (8.74 percent on average and up to 13.8 percent) with some performance gain (up to 7.5 percent) or negligible performance loss.

Experimental demonstration of particle energy, conversion efficiency and spectral shape required for ion-based fast ignition

Research on fusion fast ignition (FI) initiated by laser-driven ion beams has made substantial progress in the last years. Compared with electrons, FI based on a beam of quasi-monoenergetic ions has the advantage of a more localized energy deposition, and stiffer particle transport, bringing the required total beam energy close to the theoretical minimum. Due to short pulse laser drive, the ion beam can easily deliver the 200 TW power required to ignite the compressed D-T fuel. In integrated calculations we recently simulated ion-based FI targets with high fusion gain targets and a proof of principle experiment [1]. These simulations identify three key requirements for the success of ion-driven fast ignition (IFI): (1) the generation of a sufficiently high-energetic ion beam (approximate to 400-500 MeV for C), with (2) less than 20% energy spread at (3) more than 10% conversion efficiency of laser to beam energy. Here we present for the first time new experimental results, demonstrating all three parameters in separate experiments. Using diamond nanotargets and ultrahigh contrast laser pulses we were able to demonstrate >500 MeV carbon ions, as well as carbon pulses with Delta E/E

Conversion Ratios, Efficiency and Obfuscation: A Study of the Impact of Changed UK Charity Accounting Requirements on External Stakeholders

Key stakeholders in the UK charity sector have, in recent years, advocated greater accountability for charity performance. Part of that debate has focussed on the use of conversion ratios as indicators of efficiency, with importance to stakeholders being contrasted with charities’ apparent reluctance to report such measures. Whilst, before 2005, conversion ratios could have been computed from financial statements, changes in the UK charity SORP have radically altered the ability of users to do this. This article explores the impact on the visibility of such information through an analysis of the financial statements of large UK charities before and after the 2005 changes. Overall, the findings suggest that, despite the stated intention of increasing transparency in respect of charity costs, the application of the changes has resulted in charities ‘managing’ the numbers and limiting their disclosures, possibly to the detriment of external stakeholders.

How Much Multiuser Diversity is Required for Energy Limited Multiuser Systems?

Multiuser diversity (MUDiv) is one of the central concepts in multiuser (MU) systems. In particular, MUDiv allows for scheduling among users in order to eliminate the negative effects of unfavorable channel fading conditions of some users on the system performance. Scheduling, however, consumes energy (e.g., for making users' channel state information available to the scheduler). This extra usage of energy, which could potentially be used for data transmission, can be very wasteful, especially if the number of users is large. In this paper, we answer the question of how much MUDiv is required for energy limited MU systems. Focusing on uplink MU wireless systems, we develop MU scheduling algorithms which aim at maximizing the MUDiv gain. Toward this end, we introduce a new realistic energy model which accounts for scheduling energy and describes the distribution of the total energy between scheduling and data transmission stages. Using the fact that such energy distribution can be controlled by varying the number of active users, we optimize this number by either i) minimizing the overall system bit error rate (BER) for a fixed total energy of all users in the system or ii) minimizing the total energy of all users for fixed BER requirements. We find that for a fixed number of available users, the achievable MUDiv gain can be improved by activating only a subset of users. Using asymptotic analysis and numerical simulations, we show that our approach benefits from MUDiv gains higher than that achievable by generic greedy access algorithm, which is the optimal scheduling method for energy unlimited systems. © 2010 IEEE.

A 75-81 GHz, 14.3 dBm Peak Output Power, 21 dB Peak Gain, SiGe Power-Combining Amplifier Operating from a Single 3.3 V Supply

A compact differential 4-way power combiner with 2.3 dB loss and high common-mode rejection characteristic for use in mm-wave PAs is presented. A complete circuit comprised of a power splitter, two-stage cascode PA array, and a power combiner was implemented in SiGe technology. Measured small-signal gain of at least 17 dB was obtained from 74.5 GHz to 80.5 GHz with a peak 21 dB at 79 GHz. The prototype delivered 13.2 dBm P1dB and 14.3 dBm Psat when operated from a single 3.3 V supply at 75 GHz.