Understanding cost drivers of software evolution: a quantitative and qualitative investigation of change effort in two evolving software systems

Making changes to software systems can prove costly and it remains a challenge to understand the factors that affect the costs of software evolution. This study sought to identify such factors by investigating the effort expended by developers to perform 336 change tasks in two different software organizations. We quantitatively analyzed data from version control systems and change trackers to identify factors that correlated with change effort. In-depth interviews with the developers about a subset of the change tasks further refined the analysis. Two central quantitative results found that dispersion of changed code and volatility of the requirements for the change task correlated with change effort. The analysis of the qualitative interviews pointed to two important, underlying cost drivers: Difficulties in comprehending dispersed code and difficulties in anticipating side effects of changes. This study demonstrates a novel method for combining qualitative and quantitative analysis to assess cost drivers of software evolution. Given our findings, we propose improvements to practices and development tools to manage and reduce the costs.     

Protected subspaces in quantum information

In certain situations the state of a quantum system, after transmission through a quantum channel, can be perfectly restored. This can be done by “coding” the state space of the system before transmission into a “protected” part of a larger state space, and by applying a proper “decoding” map afterwards. By a version of the Heisenberg Principle, which we prove, such a protected space must be “dark” in the sense that no information leaks out during the transmission. We explain the role of the Knill–Laflamme condition in relation to protection and darkness, and we analyze several degrees of protection, whether related to error correction, or to state restauration after a measurement. Recent results on higher rank numerical ranges of operators are used to construct examples. In particular, dark spaces are constructed for any map of rank 2, for a biased permutations channel and for certain separable maps acting on multipartite systems. Furthermore, error correction subspaces are provided for a class of tri-unitary noise models.     

Nano-structured solid oxide fuel cell design with superior power output at high and intermediate operation temperatures

A solid oxide fuel cell (SOFC) with a thin-film yttria-stabilized zirconia (YSZ) electrolyte was developed and tested. This novel SOFC shows a similar multilayer set-up as other current anode-supported SOFCs and is composed of a Ni/8YSZ anode, a gas-tight 8YSZ electrolyte layer, a dense Sr-diffusion barrier layer and a LSCF cathode. To increase the power density and lower the SOFC operating temperature, the thickness of the electrolyte layer was reduced from around 10 μm in current cells to 1 μm, using a nanoparticle deposition method. By using the novel 1 μm electrolyte layer, the current density of our SOFC progressed to 2.7, 2.1 and 1.6 A/cm² at operation temperatures of 800, 700 and 650°C, respectively, and out-performs all similar cells reported to date in the literature. An important consideration is also that cost-effective dip-coating and spin-coating methods are applied for the fabrication of the thin-film electrolyte. Processing of 1 μm layers on the very porous anode substrate material was initially experienced as very difficult and therefore 8YSZ nanoparticle coatings were developed and optimized on porous 8YSZ model substrates and transferred afterwards to regular anode substrates. In this paper, the preparation of the novel SOFC is shown and its morphology is illustrated with high resolution SEM pictures. Further, the performance in a standard SOFC test is demonstrated.     

FracMAP: A user-interactive package for performing simulation and orientation-specific morphology analysis of fractal-like solid nano-agglomerates

Computer simulation techniques have found extensive use in establishing empirical relationships between three-dimensional (3d) and two-dimensional (2d) projected properties of particles produced by the process of growth through the agglomeration of smaller particles (monomers). In this paper, we describe a package, FracMAP, that has been written to simulate 3d quasi-fractal agglomerates and create their 2d pixelated projection images by restricting them to stable orientations as commonly encountered for quasi-fractal agglomerates collected on filter media for electron microscopy. Resulting 2d images are analyzed for their projected morphological properties.

Program summary

Program title: FracMAPCatalogue identifier: AEDD_v1_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDD_v1_0.htmlProgram obtainable from: CPC Program Library, Queen's University, Belfast, N. IrelandLicensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.htmlNo. of lines in distributed program, including test data, etc.: 4722No. of bytes in distributed program, including test data, etc.: 27 229Distribution format: tar.gzProgramming language: C++Computer: PCOperating system: Windows, LinuxRAM: 2.0 MegabytesClassification: 7.7Nature of problem: Solving for a suitable fractal agglomerate construction under constraints of typical morphological parameters.Solution method: Monte Carlo approximation.Restrictions: Problem complexity is not representative of run-time, since Monte Carlo iterations are of a constant complexity.Additional comments: The distribution file contains two versions of the FracMAP code, one for Windows and one for Linux.Running time: 1 hour for a fractal agglomerate of size 25 on a single processor.     

Classifying species of individual trees by intensity and structure features derived from airborne laser scanner data

The objective of this study was to identify candidate features derived from airborne laser scanner (ALS) data suitable to discriminate between coniferous and deciduous tree species. Both features related to structure and intensity were considered. The study was conducted on 197 Norway spruce and 180 birch trees (leaves on conditions) in a boreal forest reserve in Norway. The ALS sensor used was capable of recording multiple echoes. The point density was 6.6 m^− 2. Laser echoes located within the vertical projection of the tree crowns, which were assumed to be circular and defined according to field measurements, were attributed to three categories: “first echoes of many”, “single echoes”, or “last echoes of many echoes”. They were denoted FIRST, SINGLE, and LAST, respectively. In tree species classification using ALS data features should be independent of tree heights. We found that many features were dependent on tree height and that this dependency influenced selection of candidate features. When we accounted for this dependency, it was revealed that FIRST and SINGLE echoes were located higher and LAST echoes lower in the birch crowns than in spruce crowns. The intensity features of the FIRST echoes differed more between species than corresponding features of the other echo categories. For the FIRST echoes the intensity values tended to be higher for birch than spruce. When using the various features for species classification, maximum overall classification accuracies of 77% and 73% were obtained for structural and intensity features, respectively. Combining candidate features related to structure and intensity resulted in an overall classification accuracy of 88%.     

Constrained multisine input signals for plant-friendly identification of chemical process systems

This paper considers the use of constrained minimum crest factor multisine signals as inputs for plant-friendly identification testing of chemical process systems. The methodology presented here effectively integrates operating restrictions, information-theoretic requirements, and state-of-the-art optimization techniques to design minimum crest factor multisine signals meeting important user-specified time and frequency domain properties. A series of optimization problem formulations relevant to problems in linear, nonlinear, and multivariable system identification are presented; these culminate with their application to the modeling of the Weischedel–McAvoy high-purity distillation column problem, a demanding nonlinear and highly interactive system. The effectiveness of these signals for modeling for control purposes and the ability to incorporate a priori nonlinear models in the signal design procedure are demonstrated in this distillation system case study.     

Democratizing Journalism – How User‐Generated Content and User Communities Affect Publishers’ Business Models

Publishers, today, are struggling with their business model: Their efforts to convert traditional content into digital products seem to be insufficient as recipients expect more than simply the mere digitalization of content. Dissatisfied with solely being informed by selected journalists, modern recipients are often interested in acquiring information from various sources, in discussing with others, or even in contributing with their own content. Hence, recipients seem to evolve from being simply readers to contributors themselves. With regard to the established term ‘user‐generated content’, we refer to those co‐creating recipients as users. To underline these assumptions, the present study explores (1) users’ expectations of sources of content and (2) their willingness to provide their own content. Our findings show that both user‐generated content and professional journalists’ content is of value to users. Second, we show that users are mainly driven to contribute by their own expertise, welfare of others, and personal acceptance in the community. With this study, we consider mainly the changed user behaviour in order to derive implications of user involvement for future business models of publishers, in particular on the customer value proposition as well as key resources and key processes.     

Big data in the public sector: Uncertainties and readiness

Big data is being implemented with success in the private sector and science. Yet the public sector seems to be falling behind, despite the potential value of big data for government. Government organizations do recognize the opportunities of big data but seem uncertain about whether they are ready for the introduction of big data, and if they are adequately equipped to use big data. This paper addresses those uncertainties. It presents an assessment framework for evaluating public organizations’ big data readiness. Doing so demystifies the concept of big data, as it is expressed in terms of specific and measureable organizational characteristics. The framework was tested by applying it to organizations in the Dutch public sector. The results suggest that organizations may be technically capable of using big data, but they will not significantly gain from these activities if the applications do not fit their organizations and main statutory tasks. The framework proved helpful in pointing out areas where public sector organizations could improve, providing guidance on how government can become more big data ready in the future.     

An auto-generated real-time iteration algorithm for nonlinear MPC in the microsecond range

In this paper, we present an automatic C-code generation strategy for real-time nonlinear model predictive control (NMPC), which is designed for applications with kilohertz sample rates. The corresponding code export module has been implemented within the software package ACADO Toolkit. It is capable of exporting fixed step-size integrators together with their sensitivities as well as a real-time Gauss–Newton method. Here, we employ the symbolic representation of optimal control problems in ACADO in order to auto-generate plain C-code which is optimized for final production. The exported code has been tested for model predictive control scenarios comprising constrained nonlinear dynamic systems with four states and a control horizon of ten samples. The numerical simulations show a promising performance of the exported code being able to provide feedback in much less than a millisecond.