Walking Through the Method Zoo: Does Higher Education Really Meet Software Industry Demands?

Software engineering educators are continually challenged by rapidly evolving concepts, technologies, and industry demands. Due to the omnipresence of software in a digitalized society, higher education institutions (HEIs) have to educate the students such that they learn how to learn, and that they are equipped with a profound basic knowledge and with latest knowledge about modern software and system development. Since industry demands change constantly, HEIs are challenged in meeting such current and future demands in a timely manner. This paper analyzes the current state of practice in software engineering education. Specifically, we want to compare contemporary education with industrial practice to understand if frameworks, methods and practices for software and system development taught at HEIs reflect industrial practice. For this, we conducted an online survey and collected information about 67 software engineering courses. Our findings show that development approaches taught at HEIs quite closely reflect industrial practice. We also found that the choice of what process to teach is sometimes driven by the wish to make a course successful. Especially when this happens for project courses, it could be beneficial to put more emphasis on building learning sequences with other courses

Hybrid Software Development Approaches in Practice: A European Perspective

Agile and traditional development approaches are used in combination in todays software development. To improve the understanding and to provide better guidance for selecting appropriate development approaches, it is important to analyze such combinations in practice. Results obtained from an online survey strongly confirm that hybrid development approaches are widely used in industry. Our results show that hybrid development approaches: (i) have become reality for nearly all companies; (ii) are applied to specific projects even in the presence of company-wide policies for process usage; (iii) are neither planned nor designed but emerge from the evolution of different work practices; and, (iv) are consistently used regardless of company size or industry secto

What are Hybrid Development Methods Made Of? An Evidence-Based Characterization

Among the multitude of software development processes available, hardly any is used by the book. Regardless of company size or industry sector, a majority of project teams and companies use customized processes that combine different development methods— so-called hybrid development methods. Even though such hybrid development methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. In this paper, we make a first step towards devising such guidelines. Grounded in 1,467 data points from a large-scale online survey among practitioners, we study the current state of practice in process use to answer the question: What are hybrid development methods made of? Our findings reveal that only eight methods and few practices build the core of modern software development. This small set allows for statistically constructing hybrid development methods. Using an 85% agreement level in the participants’ selections, we provide two examples illustrating how hybrid development methods are characterized by the practices they are made of. Our evidence-based analysis approach lays the foundation for devising hybrid development methods

Ordnungsarbeit in einer glokalisierten Welt: Die neue Mischökonomie des Polizierens und der Polizei

Although a plethora of tools are available for Global Software Engineering (GSE) teams, it is being realized increasingly that the most prevalent desktop metaphor underpinning the majority of tools have several inherent limitations. We have proposed that Activity-Based Computing (ABC) can be a promising alternative to build tools for GSE. However, significant effort is required to introduce a new paradigm; there is a need of sound theoretical foundation based on activity theory to address challenges faced by tools in GSE. This paper reports our effort aimed at building theoretical foundations for applying activity theory to GSE. We analyze and explain the fundamental concepts of activity theory, and how they can be applied by using examples of software architecture design and evaluation processes. We describe the kind of data model and architectural support required for applying activity theory in building supporting infrastructure for GSE, and describe a proof of concept prototype.Paolo Tell, Muhammad Ali Baba

In-situ monitoring for CVD processes

Aiming towards process control of industrial high yield/high volume CVD reactors, the potential of optical sensors as a monitoring tool has been explored. The sensors selected are based on both Fourier transform infrared spectroscopy (FTIR) and tunable diode laser spectroscopy (NIR-DLS). The former has the advantage of wide spectral capability, and well established databases. NIR-DLS spectroscopy has potentially high sensitivity, laser spatial resolution, and the benefits of comparatively easier integration capabilities-including optical fibre compatibility. The proposed technical approach for process control is characterised by a 'chemistry based' feedback system with in-situ optical data as input information. The selected optical sensors continuously analyze the gas phase near the surface of the growing layer. The spectroscopic data has been correlated with process performance and layer properties which, in turn establish data basis for process control. The new process control approach is currently being verified on different industrialised CVD coaters. One of the selected applications deals with the deposition of SnO2 layers on glass based on the oxidation of (CH3)2SnCl2, which is used in high volume production for low-E glazing

Dyonic Non-Abelian Black Holes

We study static spherically symmetric dyonic black holes in Einstein-Yang-Mills-Higgs theory. As for the magnetic non-abelian black holes, the domain of existence of the dyonic non-abelian black holes is limited with respect to the horizon radius and the dimensionless coupling constant $\alpha$, which is proportional to the ratio of vector meson mass and Planck mass. At a certain critical value of this coupling constant, $\hat \alpha$, the maximal horizon radius is attained. We derive analytically a relation between $\hat \alpha$ and the charge of the black hole solutions and confirm this relation numerically. Besides the fundamental dyonic non-abelian black holes, we study radially excited dyonic non-abelian black holes and globally regular gravitating dyons.Comment: LaTeX, 22 pages, 16 figures, three figures added, file manipulation error in previous replac

An ambipolar BODIPY derivative for a white exciplex OLED and cholesteric liquid crystal laser toward multifunctional devices

A new interface engineering method is demonstrated for the preparation of an efficient white organic light-emitting diode (WOLED) by embedding an ultrathin layer of the novel ambipolar red emissive compound 4,4-difluoro-2,6-di(4-hexylthiopen-2-yl)-1,3,5,7,8-pentamethyl-4-bora-3a,4a-diaza-s-indacene (bThBODIPY) in the exciplex formation region. The compound shows a hole and electron mobility of 3.3 × 10–4 and 2 × 10–4 cm2 V–1 s–1, respectively, at electric fields higher than 5.3 × 105 V cm–1. The resulting WOLED exhibited a maximum luminance of 6579 cd m–2 with CIE 1931 color coordinates (0.39; 0.35). The bThBODIPY dye is also demonstrated to be an effective laser dye for a cholesteric liquid crystal (ChLC) laser. New construction of the ChLC laser, by which a flat capillary with an optically isotropic dye solution is sandwiched between two dye-free ChLC cells, provides photonic lasing at a wavelength well matched with that of a dye-doped planar ChLC cell

Interference of Clocks: A Quantum Twin Paradox

The phase of matter waves depends on proper time and is therefore susceptible to special-relativistic (kinematic) and gravitational time dilation (redshift). Hence, it is conceivable that atom interferometers measure general-relativistic time-dilation effects. In contrast to this intuition, we show that light-pulse interferometers without internal transitions are not sensitive to gravitational time dilation, whereas they can constitute a quantum version of the special-relativistic twin paradox. We propose an interferometer geometry isolating the effect that can be used for quantum-clock interferometry.Comment: 9 Pages, 2 Figure

Enzymatically activated emulsions stabilised by interfacial nanofibre networks

We report on-demand formation of emulsions stabilised by interfacial nanoscale networks. These are formed through biocatalytic dephosphorylation and self-assembly of Fmoc(9-fluorenylmethoxycarbonyl)-dipeptide amphiphiles in aqueous/organic mixtures. This is achieved by using alkaline phosphatase which transforms surfactant-like phosphorylated precursors into self-assembling aromatic peptide amphiphiles (Fmoc-tyrosine-leucine, Fmoc-YL) that form nanofibrous networks. In biphasic organic/aqueous systems, these networks form preferentially at the interface thus providing a means of emulsion stabilisation. We demonstrate on-demand emulsification by enzyme addition, even after storage of the biphasic mixture for several weeks. Experimental (Fluorescence, FTIR spectroscopy, fluorescence microscopy, electron microscopy, atomic force microscopy) and computational techniques (atomistic molecular dynamics) are used to characterise the interfacial self-assembly process

Generic 3D Representation via Pose Estimation and Matching

Though a large body of computer vision research has investigated developing generic semantic representations, efforts towards developing a similar representation for 3D has been limited. In this paper, we learn a generic 3D representation through solving a set of foundational proxy 3D tasks: object-centric camera pose estimation and wide baseline feature matching. Our method is based upon the premise that by providing supervision over a set of carefully selected foundational tasks, generalization to novel tasks and abstraction capabilities can be achieved. We empirically show that the internal representation of a multi-task ConvNet trained to solve the above core problems generalizes to novel 3D tasks (e.g., scene layout estimation, object pose estimation, surface normal estimation) without the need for fine-tuning and shows traits of abstraction abilities (e.g., cross-modality pose estimation). In the context of the core supervised tasks, we demonstrate our representation achieves state-of-the-art wide baseline feature matching results without requiring apriori rectification (unlike SIFT and the majority of learned features). We also show 6DOF camera pose estimation given a pair local image patches. The accuracy of both supervised tasks come comparable to humans. Finally, we contribute a large-scale dataset composed of object-centric street view scenes along with point correspondences and camera pose information, and conclude with a discussion on the learned representation and open research questions.Comment: Published in ECCV16. See the project website http://3drepresentation.stanford.edu/ and dataset website https://github.com/amir32002/3D_Street_Vie