ÐThe basic premise of software inspections is that they detect and remove defects before they propagate to subsequent development phases where their detection and correction cost escalates. To exploit their full potential, software inspections must call for a close and strict examination of the inspected artifact. For this, reading techniques for defect detection may be helpful since these techniques tell inspection participants what to look for and, more importantly, how to scrutinize a software artifact in a systematic manner. Recent research efforts investigated the benefits of scenario-based reading techniques. A major finding has been that these techniques help inspection teams find more defects than existing state-of-the-practice approaches, such as, ad-hoc or checklist-based reading (CBR). In this paper, we experimentally compare one scenario-based reading technique, namely, perspective-based reading (PBR), for defect detection in code documents with the more traditional CBR approach. The comparison was performed in a series of three studies, as a quasi experiment and two internal replications, with a total of 60 professional software developers at Bosch Telecom GmbH. Meta-analytic techniques were applied to analyze the data. Our results indicate that PBR is more effective than CBR (i.e., it resulted in inspection teams detecting more unique defects than CBR) and that the cost of defect detection using PBR is significantly lower than CBR. Therefore, this study provides evidence demonstrating the efficacy of PBR scenarios for code documents in an industrial setting. Index TermsÐSoftware inspection, perspective-based reading, quasi experiment, replication, meta-analysis. ae 1. This constitutes the costs associated with correcting defects. 2. Both of these figures assume that the defect detection life cycle prior to the introduction of inspections consisted only of testing activities. 3. In this article, we model the inspection process in terms of its main activities. This allows us to be independent from a specific inspection implementation, such as the Fagan [24] or the Gilb [30] one.
An electron-hole plasma in the presence of a high-intensity laser field is considered in the quasienergy picture. Using a two-band model it is shown that the gain spectrum depends on the strength of the laser field in a characteristic way, provided the frequency of transitions between the conduction and the valence band is a t least of the order of the inverse collision time.Es wird ein Elektron-Loch-Plasma in Anwesenheit eines extrem intensiven Laserfeldes im Quasienergie-Bild betrachtet. Fur ein einfaches Zwei-Band-Model1 wird gezeigt, da13 das Gain-Spektr um yon der Laserfeldstarke in charakteristischer Weise abhlngt, vorausgesetzt, die ubergangsr ate zwischen Leitungs-und Valenzband ist rnindestens so grol3 wie die inverse Kollisionszeit.
Recent years have witnessed a convergence of data and methods that allow us to approximate the shape, size, and functional attributes of biological organisms. This is not only limited to traditional model species: given the ability to culture and visualize a specific organism, we can capture both its structural and functional attributes. We present a quantitative model for the colonial diatom Bacillaria paradoxa, an organism that presents a number of unique attributes in terms of form and function. To acquire a digital model of B. paradoxa, we extract a series of quantitative parameters from microscopy videos from both primary and secondary sources. These data are then analyzed using a variety of techniques, including two rival deep learning approaches. We provide an overview of neural networks for non-specialists as well as present a series of analysis on Bacillaria phenotype data. The application of deep learning networks allow for two analytical purposes. Application of the DeepLabv3 pre-trained model extracts phenotypic parameters describing the shape of cells constituting Bacillaria colonies. Application of a semantic model trained on nematode embryogenesis data (OpenDevoCell) provides a means to analyze masked images of potential intracellular features. We also advance the analysis of Bacillaria colony movement dynamics by using templating techniques and biomechanical analysis to better understand the movement of individual cells relative to an entire colony. The broader implications of these results are presented, with an eye towards future applications to both hypothesis-driven studies and theoretical advancements in understanding the dynamic morphology of Bacillaria.
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