Strategic organization in projects and firms through software integration

As integrated software solutions reshape project delivery, they alter the bases for collaboration and competition across firms in complex industries. This paper synthesises and extends literatures on strategy in project-based industries and digitally-integrated work to understand how project-based firms interact with digital infrastructures for project delivery. Four identified strategies are to: 1) develop and use capabilities to shape the integrated software solutions that are used in projects; 2) co-specialize, developing complementary assets to work repeatedly with a particular integrator firm; 3) retain flexibility by developing and maintaining capabilities in multiple digital technologies and processes; and 4) manage interfaces, translating work into project formats for coordination while hiding proprietary data and capabilities in internal systems. The paper articulates the strategic importance of digital infrastructures for delivery as well as product architectures. It concludes by discussing managerial implications of the identified strategies and areas for further research.

Real-Time software control of neural stimulation in a closed loop Animat system

A recent area for investigation into the development of adaptable robot control is the use of living neuronal networks to control a mobile robot. The so-called Animat paradigm comprises a neuronal network (the ‘brain’) connected to an external embodiment (in this case a mobile robot), facilitating potentially robust, adaptable robot control and increased understanding of neural processes. Sensory input from the robot is provided to the neuronal network via stimulation on a number of electrodes embedded in a specialist Petri dish (Multi Electrode Array (MEA)); accurate control of this stimulation is vital. We present software tools allowing precise, near real-time control of electrical stimulation on MEAs, with fast switching between electrodes and the application of custom stimulus waveforms. These Linux-based tools are compatible with the widely used MEABench data acquisition system. Benefits include rapid stimulus modulation in response to neuronal activity (closed loop) and batch processing of stimulation protocols.

A data collection case study supporting requirements oriented prediction and management in software developments

Consider the statement "this project should cost X and has risk of Y". Such statements are used daily in industry as the basis for making decisions. The work reported here is part of a study aimed at providing a rational and pragmatic basis for such statements. Of particular interest are predictions made in the requirements and early phases of projects. A preliminary model has been constructed using Bayesian Belief Networks and in support of this, a programme to collect and study data during the execution of various software development projects commenced in May 2002. The data collection programme is undertaken under the constraints of a commercial industrial regime of multiple concurrent small to medium scale software development projects. Guided by pragmatism, the work is predicated on the use of data that can be collected readily by project managers; including expert judgements, effort, elapsed times and metrics collected within each project.

Discriminative pattern mining in software fault detection

We present a method to enhance fault localization for software systems based on a frequent pattern mining algorithm. Our method is based on a large set of test cases for a given set of programs in which faults can be detected. The test executions are recorded as function call trees. Based on test oracles the tests can be classified into successful and failing tests. A frequent pattern mining algorithm is used to identify frequent subtrees in successful and failing test executions. This information is used to rank functions according to their likelihood of containing a fault. The ranking suggests an order in which to examine the functions during fault analysis. We validate our approach experimentally using a subset of Siemens benchmark programs.

HDC poinsettia tracker: flexible graphical tracking software

Growing pot poinsettia and similar crops involves careful crop monitoring and management to ensure that height specifications are met. Graphical tracking represents a target driven approach to decision support with simple interpretation. HDC (Horticultural Development Council) Poinsettia Tracker implements a graphical track based on the Generalised Logistic Curve, similar to that of other tracking packages. Any set of curve parameters can be used to track crop progress. However, graphical tracks must be expected to be site and cultivar specific. By providing a simple Curve fitting function, growers can easily develop their own site and variety specific ideal tracks based on past records with increasing quality as more seasons' data are added. (C) 2009 Elsevier B.V. All rights reserved.

Cascade dicopper architectures of a dibenzodioxatetraazamacrocycle

The dibenzodioxatetraazamacrocycle [26]pbz(2)N(4)O(2) was characterised by single crystal X-ray diffraction and the protonation constants of this compound and the stability constants of its copper(II) and lead(II) complexes were determined by potentiometry in water at 298.2 K in 0.10 mol dm(-3) in KNO3. Mono- and dinuclear complexes were found for both metal ions, the dinuclear complexes being the main species in the 5-7.5 pH range for copper(II) and 7.5-8.5 for lead(II). As expected the values of the stability constants for the copper(II) complexes are lower than those for related macrocycles containing only nitrogen atoms. The presence of mono- and dinuclear copper complexes was also confirmed by electrospray ionization mass spectrometry. These results suggest that the symmetric macrocyclic cavity of [26]pbZ(2)N(4)O(2) has enough space for the coordination of two metal ions. Additionally, NMR spectroscopy showed that the dinuclear complex of lead(II) has high symmetry. The equilibrium constants of the dinuclear copper(II) complexes and dicarboxylate anions (oxalate, malonate and succinate) were also determined in 0.10 mol dm-3 aqueous KNO3 solution. Only species containing one anion, Cu(2)H(h)LA((2+h)), were found, strongly suggesting that the anion bridges the two copper(II) ions. The binding constants of the cascade species formed by [Cu-2[26]pbZ(2)N(4)O(2)(H2O)(4+) with dicarboxylate anions decrease with the increase in length of the alkyl chain of the anion, a fact which was attributed to a higher conformational energy necessary for the rearrangement of the macrocycle to accommodate the larger anions bridging the two copper(II) centres. The variation of the magnetic susceptibility with temperature Of [Cu-2(H-2[26]pbz(2)N(4)O(2))(oxa)(3)]-4H(2)O and [Cu-2([26]pbz(2)N(4)O(2))(suc)Cl-2] were measured and the two complexes showed different behaviour. (c) 2007 Elsevier Ltd. All rights reserved.

Structural diversity in supramolecular architectures of Mn(II) through non-covalent interactions

Two mononuclear complexes of manganese(II), [Mn(OCN)(2)(phen)(2)] 1 and [Mn(NCO)(2)(bpy)(2)] 2 [1,10-phenanthroline (phen); 2,2'-bipyridine (bpy)], have been synthesized and characterized by single crystal X-ray analysis, infra-red spectroscopy and magnetic studies. The coordination structure of complex 2 is already reported. The cyanate anions are pendent in both the complexes. In 1, cyanate anion links manganese(II) through O-atom, whereas in 2 it coordinates through N-atom. The mononuclear fragments of 1 are built up to a supramolecular lamellar 3D architecture by pi-pi interactions only. On the other hand, mononuclear fragments of 2 are assembled to a 2D supramolecular brick-wall architecture by C-H-... pi interactions.

Utilisation of dendritic architectures in molecular recognition and self-assembly processes

This mini-review outlines recent key developments in the use of dendritic architectures in self-assembly processes via utilisation of molecular recognition motifs.

Teachers as researchers and teachers as software developers: how use-case analysis helps build better educational software

A series of government initiatives has raised both the profile of ICT in the curriculum and the expectation that high quality teaching and learning resources will be accessible across electronic networks. In order for e-learning resources such as websites to have the maximum educational impact, teachers need to be involved in their design and development. Use-case analysis provides a means of defining user requirements and other constraints in such a way that software developers can produce e-learning resources which reflect teachers' professional knowledge and support their classroom practice. It has some features in common with the participatory action research used to develop other aspects of classroom practice. Two case-studies are presented: one involves the development of an on-line resource centred on transcripts of original historical documents; the other describes how 'Learning how to Learn', a major, distributed research project funded under the ESRC Teaching and Learning Research Programme is using use-case analysis to develop web resources and services.

Advanced scalable algorithms for advanced architectures

With the latest advances in the area of advanced computer architectures we are seeing already large scale machines at petascale level and we are discussing exascale computing. All these require efficient scalable algorithms in order to bridge the performance gap. In this paper examples of various approaches of designing scalable algorithms for such advanced architectures will be given and the corresponding properties of these algorithms will be outlined and discussed. Examples will outline such scalable algorithms applied to large scale problems in the area Computational Biology, Environmental Modelling etc. The key properties of such advanced and scalable algorithms will be outlined.

A simulation model of self-organising evolvability in software systems

The evolvability of a software artifact is its capacity for producing heritable or reusable variants; the inverse quality is the artifact's inertia or resistance to evolutionary change. Evolvability in software systems may arise from engineering and/or self-organising processes. We describe our 'Conditional Growth' simulation model of software evolution and show how, it can be used to investigate evolvability from a self-organisation perspective. The model is derived from the Bak-Sneppen family of 'self-organised criticality' simulations. It shows good qualitative agreement with Lehman's 'laws of software evolution' and reproduces phenomena that have been observed empirically. The model suggests interesting predictions about the dynamics of evolvability and implies that much of the observed variability in software evolution can be accounted for by comparatively simple self-organising processes.