Requirements Prioritization Based on Benefit and Cost Prediction: An Agenda for Future Research

In early phases of the software cycle, requirements prioritization necessarily relies on the specified requirements and on predictions of benefit and cost of individual requirements. This paper presents results of a systematic review of literature, which investigates how existing methods approach the problem of requirements prioritization based on benefit and cost. From this review, it derives a set of under-researched issues which warrant future efforts and sketches an agenda for future research in this area

Requirements Prioritization Based on Benefit and Cost Prediction: A Method Classification Framework

In early phases of the software development process, requirements prioritization necessarily relies on the specified requirements and on predictions of benefit and cost of individual requirements. This paper induces a conceptual model of requirements prioritization based on benefit and cost. For this purpose, it uses Grounded Theory. We provide a detailed account of the procedures and rationale of (i) how we obtained our results and (ii) how we used them to form the basis for a framework for classifying requirements prioritization methods

Efficient algorithm to study interconnected networks

Interconnected networks have been shown to be much more vulnerable to random and targeted failures than isolated ones, raising several interesting questions regarding the identification and mitigation of their risk. The paradigm to address these questions is the percolation model, where the resilience of the system is quantified by the dependence of the size of the largest cluster on the number of failures. Numerically, the major challenge is the identification of this cluster and the calculation of its size. Here, we propose an efficient algorithm to tackle this problem. We show that the algorithm scales as O(N log N), where N is the number of nodes in the network, a significant improvement compared to O(N^2) for a greedy algorithm, what permits studying much larger networks. Our new strategy can be applied to any network topology and distribution of interdependencies, as well as any sequence of failures.Comment: 5 pages, 6 figure

Mitochondrial heat shock protein 70, a molecular chaperone for proteins encoded by mitochondrial DNA

Mitochondrial heat shock protein 70 (mt-Hsp70) has been shown to play an important role in facilitating import into, as well as folding and assembly of nuclear-encoded proteins in the mitochondrial matrix. Here, we describe a role for mt-Hsp70 in chaperoning proteins encoded by mitochondrial DNA and synthesized within mitochondria. The availability of mt-Hsp70 function influences the pattern of proteins synthesized in mitochondria of yeast both in vivo and in vitro. In particular, we show that mt-Hsp70 acts in maintaining the var1 protein, the only mitochondrially encoded subunit of mitochondrial ribosomes, in an assembly competent state, especially under heat stress conditions. Furthermore, mt-Hsp70 helps to facilitate assembly of mitochondrially encoded subunits of the ATP synthase complex. By interacting with the ATP-ase 9 oligomer, mt-Hsp70 promotes assembly of ATP-ase 6, and thereby protects the latter protein from proteolytic degradation. Thus mt-Hsp70 by acting as a chaperone for proteins encoded by the mitochondrial DNA, has a critical role in the assembly of supra- molecular complexes

Renormalizing Sznajd model on complex networks taking into account the effects of growth mechanisms

We present a renormalization approach to solve the Sznajd opinion formation model on complex networks. For the case of two opinions, we present an expression of the probability of reaching consensus for a given opinion as a function of the initial fraction of agents with that opinion. The calculations reproduce the sharp transition of the model on a fixed network, as well as the recently observed smooth function for the model when simulated on a growing complex networks.Comment: 5 pages, 7 figure

Riemann solvers and undercompressive shocks of convex FPU chains

We consider FPU-type atomic chains with general convex potentials. The naive continuum limit in the hyperbolic space-time scaling is the p-system of mass and momentum conservation. We systematically compare Riemann solutions to the p-system with numerical solutions to discrete Riemann problems in FPU chains, and argue that the latter can be described by modified p-system Riemann solvers. We allow the flux to have a turning point, and observe a third type of elementary wave (conservative shocks) in the atomistic simulations. These waves are heteroclinic travelling waves and correspond to non-classical, undercompressive shocks of the p-system. We analyse such shocks for fluxes with one or more turning points. Depending on the convexity properties of the flux we propose FPU-Riemann solvers. Our numerical simulations confirm that Lax-shocks are replaced by so called dispersive shocks. For convex-concave flux we provide numerical evidence that convex FPU chains follow the p-system in generating conservative shocks that are supersonic. For concave-convex flux, however, the conservative shocks of the p-system are subsonic and do not appear in FPU-Riemann solutions