Aspect] is a simple and practical aspect-oriented extension to Java With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ's dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.

An overview of AspectJ

We examine why demographic models should be used cautiously in Population Viability Analysis (PVA) with endangered species. We review the structure, data requirements, and outputs of analytical, deterministic single-population, stochastic single-population, metapopulation, and spatially explicit models. We believe predictions from quantitative models for endangered species are unreliable due to poor quality of demographic data used in most applications, difficulties in estimating variance in demographic rates, and lack of information on dispersal (distances, ages, mortality, movement patterns). Unreliable estimates also arise because stochastic models are difficult to validate, environmental trends and periodic fluctuations are rarely considered, the form of density dependence is frequently unknown but greatly affects model outcomes, and alternative model structures can result in very different predicted effects of management regimes. We suggest that PVA (1) evaluate relative rather than absolute rates of extinction, (2) emphasize short-time periods for making projections, (3) start with simple models and choose an approach that data can support, (4) use models cautiously to diagnose causes of decline and examine potential routes to recovery, (5) evaluate cumulative ending functions and alternative reference points rather than extinction rates, (6) examine all feasible scenarios, and (7) mix genetic and demographic currencies sparingly. Links between recovery options and PVA models should be established by conducting field tests of model assumptions and field validation of secondary model predictions.

On the Use of Demographic Models of Population Viability in Endangered Species Management

Step-wise refinement is a powerful paradigm for developing a complex program from a simple program by adding features incrementally. We present the AHEAD (algebraic hierarchical equations for application design) model that shows how step-wise refinement scales to synthesize multiple programs and multiple noncode representations. AHEAD shows that software can have an elegant, hierarchical mathematical structure that is expressible as nested sets of equations. We review a tool set that supports AHEAD. As a demonstration of its viability, we have bootstrapped AHEAD tools from equational specifications, refining Java and nonJava artifacts automatically; a task that was accomplished only by ad hoc means previously.

Scaling step-wise refinement

From the Publisher:
Why do similar patterns and forms appear in nature in settings that seem to bear no relation to one another? The Windblown ripples of desert sand follow a sinuous course that resembles the stripes of a zebra or a marine fish In the trellis-like shells of microscopic sea creatures we see the same geometry as in the bubble walls of foam, Forks of lightning mirror the branches of a river network or a tree
This book explains why these are not coincidences Nature commonly weaves its tapestry without any master plan or blueprint Instead, these designs build themselves by self-organization The interactions between the component parts -- whether they be grains of sand, molecules or living cells -- give rise to spontaneous patterns that are at the same time complex and beautiful Many of these patterns are universal, recurring again and again in the natural order: spirals, spots, stripes, branches, honeycombs Philip Ball conducts a profusely illustrated tour of this gallery, and reveals the secrets of how nature's patterns are made

The Self-Made Tapestry: Pattern Formation in Nature

Feature modeling is an important approach to capture the commonalities and variabilities in system families and product lines. Cardinality-based feature modeling integrates a number of existing extensions of the original feature-modeling notation from Feature-Oriented Domain Analysis. Staged configuration is a process that allows the incremental configuration of cardinality-based feature models. It can be achieved by performing a step-wise specialization of the feature model. In this article, we argue that cardinality-based feature models can be interpreted as a special class of context-free grammars. We make this precise by specifying a translation from a feature model into a context-free grammar. Consequently, we provide a semantic interpretation for cardinality-based feature models by assigning an appropriate semantics to the language recognized by the corresponding grammar. Finally, we give an account on how feature model specialization can be formalized as transformations on the grammar equivalent of feature models. Copyright © 2005 John Wiley & Sons, Ltd.

/pdf/formalizing-cardinality-based-feature-models-and-their-6zf3v3d7z9.pdf

Formalizing cardinality‐based feature models and their specialization

Ecologists have fiercely debated for many decades whether populations are self-regulated by density-dependent biological mechanisms or are controlled by exogenous environmental forces. Here, a stochastic mechanistic model is used to show that the interaction of these two forces can explain observed large fluctuations in Dungeness crab (Cancer magister) numbers. Relatively small environmental perturbations interact with realistic nonlinear (density dependent) biological mechanisms, to produce dynamics that are similar to observations. This finding has implications throughout population biology, suggesting both that the study of deterministic density-dependent models is highly problematic and that stochastic models must include biologically relevant nonlinear mechanisms.

https://science.sciencemag.org/content/sci/276/5317/1431.full.pdf

Stochastic Dynamics and Deterministic Skeletons: Population Behavior of Dungeness Crab

Step-wise refinement is a powerful paradigm for developing a complex program from a simple program by adding features incrementally. We present the AHEAD (Algebraic Hierarchical Equations for Application Design) model that shows how step-wise refinement scales to synthesize multiple programs and multiple non-code representations. AHEAD shows that software can have an elegant, hierarchical mathematical structure that is expressible as nested sets of equations. We review a tool set that supports AHEAD. As a demonstration of its viability, we have bootstrapped AHEAD tools solely from equational specifications, generating Java and non-Java artifacts automatically, a task that was accomplished only by ad hoc means previously.

/pdf/scaling-step-wise-refinement-4gplsnsvhc.pdf

Step-wise refinement (SWR) asserts that complex programs can be derived from simple programs by progressively adding features. The length of a program specification is the number of features that the program has. Critical to the scalability of SWR are multi-dimensional models that separate orthogonal feature sets. Let n be the dimensionality of a model and k be the number of features along a dimension. We show program specifications that could be O(kn) features long have short and easy-to-understand specifications of length O(kn) when multi-dimensional models are used. We present new examples of multidimensional models: a micro example of a product-line (whose programs are 30 lines of code) and isomorphic macro examples (whose programs exceed 30K lines of code). Our work provides strong evidence that SWR scales to synthesis of large systems.

/pdf/refinements-and-multi-dimensional-separation-of-concerns-4i9tk7mtsr.pdf

Refinements and multi-dimensional separation of concerns

Model driven engineering (MDE) of software product lines (SPLs) merges two increasing important paradigms that synthesize programs by transformation. MDE creates programs by transforming models, and SPLs elaborate programs by applying transformations called features. In this paper, we present the design and implementation of a transformational model of a product line of scalar vector graphics and JavaScript applications. We explain how we simplified our implementation by lifting selected features and their compositions from our original product line (whose implementations were complex) to features and their compositions of another product line (whose specifications were simple). We used operators to map higher-level features and their compositions to their lower-level counterparts. Doing so exposed commuting relationships among feature compositions in both product lines that helped validate our model and implementation.

Jacob Neal Sarvela

Papers

Scaling step-wise refinement

Stochastic Dynamics and Deterministic Skeletons: Population Behavior of Dungeness Crab

Scaling step-wise refinement

Refinements and multi-dimensional separation of concerns

Lifting transformational models of product lines: a case study