2030931
Improved Algorithm Complexities for Linear Temporal Logic Model Checking of Pushdown Systems
This paper presents a novel implementation strategy for linear temporal logic (LTL) model checking of pushdown systems (PDS). The model checking problem is formulated intuitively in terms of evaluation of Datalog rules. We use a systematic and fully automated method to generate a specialized algorithm and data structures directly from the rules. The generated implementation employs an incremental approach that considers one fact at a time and uses a combination of linked and indexed data structures for facts. We provide precise time complexity for the model checking problem; it is computed automatically and directly from the rules. We obtain a more precise and simplified complexity analysis, as well as improved algorithm understanding.
8840929
Optimized Live Heap Bound Analysis
This paper describes a general approach for optimized live heap space and live heap space-bound analyses for garbage-collected languages. The approach is based on program analysis and transformations and is fully automatic. In our experience, the space-bound analysis generally produces accurate (tight) upper bounds in the presence of partially known input structures. The optimization drastically improves the analysis efficiency. The analyses have been implemented and experimental results confirm their accuracy and efficiency.
37778003
Automatic Accurate Cost-Bound Analysis for High-Level Languages
This paper describes a language-based approach for automatic and accurate cost-bound analysis. The approach consists of transformations for building cost-bound functions in the presence of partially known input structures, symbolic evaluation of the cost-bound function based on input size parameters, and optimizations to make the overall analysis efficient as well as accurate, all at the source-language level. The calculated cost bounds are expressed in terms of primitive cost parameters. These parameters can be obtained based on the language implementation or can be measured conservatively or approximately, yielding accurate, conservative, or approximate time or space bounds. We have implemented this approach and performed a number of experiments for analyzing Scheme programs. The results helped confirm the accuracy of the analysis.
15838270
Eliminating Dead Code on Recursive Data
This paper describes a general and powerful method for dead code analysis and elimination in the presence of recursive data constructions. We represent partially dead recursive data using liveness patterns based on general regular tree grammars extended with the notion of live and dead, and we formulate the analysis as computing liveness patterns at all program points based on program semantics. This analysis yields a most precise liveness pattern for the data at each program point, which is significantly more precise than results from previous methods. The analysis algorithm takes cubic time in terms of the size of the program in the worst case but is very efficient in practice, as shown by our prototype implementation. The analysis results are used to identify and eliminate dead code. The general framework for representing and analyzing properties of recursive data structures using general regular tree grammars applies to other analyses as well.
5528420
Automatic time-bound analysis for a higher-order language
Analysis of program running time is important for several applications, including reactive systems, interactive environments, compiler optimizations and performance evaluation. Automatic and efficient prediction of accurate time bounds is particularly important, and being able to do so for high-level languages is particularly desirable. This paper presents a general approach for automatic and accurate time-bound analysis for a functional high-level language, that combines methods and techniques studied in theory, languages, and systems. The approach consists of transformations for building time-bound functions in the presence of partially known input structures, symbolic evaluation of the time-bound function based on input parameters, optimizations to make the analysis efficient as well as accurate, and measurements of primitive parameters, all at the source-language level. To handle higher-order functions, special transformations are needed to build lambda expressions for computing running times, to optimize the construction of the time lambda expressions, and to optimize the symbolic evaluation. It took us several tries to obtain the simple and concise transformations for handling lambda expressions. We describe analysis and transformation algorithms and explain how they work. We have implemented this approach and performed a large number of experiments analyzing Scheme programs. The measured worst-case times are closely bounded by the calculated bounds. We describe our prototype system, ALPA, as well as the analysis and measurement results.
9019278
Querying Complex Graphs
This paper presents a powerful language for querying complex graphs and a method for generating efficient implementations that can answer queries with complexity guarantees. The graphs may have edge labels that may have parameters, and easily and naturally capture complex interrelated objects in object-oriented systems and XML data. The language is built on extended regular path expressions with variables and scoping, and can express queries more easily and clearly than previous query languages.The method for implementation first transforms queries into Datalog with limited extensions. It then extends a previous method to generate specialized algorithms and complexity formulas from Datalog with these extensions.
15475945
Performance prediction of component-based applications
One of the major problems in building large-scale enterprise systems is anticipating the performance of the eventual solution before it has been built. The fundamental software engineering problem becomes more difficult when the systems are built on component technology. This paper investigates the feasibility of providing a practical solution to this problem. An empirical approach is proposed to determine the performance characteristics of component-based applications by benchmarking and profiling. Based on observation, a model is constructed to act as a performance predictor for a class of applications based on the specific component technology. The performance model derived from empirical measures is necessary to make the problem tractable and the results relevant. A case study applies the performance model to an application prototype implemented by two component infrastructures: CORBA and J2EE.
2748390
Ensemble structure of evolutionary artificial neural networks
Evolutionary artificial neural networks (EANNs) refer to a special class of artificial neural networks (ANNs) in which evolution is another fundamental form of adaptation in addition to learning. Evolution can be introduced at various levels of ANNs. It can be used to evolve weights, architectures, and learning parameters and rules. The paper is concerned with the evolution of ANN architectures, where an evolutionary algorithm is used to evolve a population of ANNs. The current practice in evolving ANNs is to choose the best ANN in the last population as the final result. The paper proposes a novel approach to form the final result by combining all the individuals in the last generation in order to make best use of all the information contained in the whole population. This approach regards a population of ANNs as an ensemble of ANNs and use a method to combine them. We have used four simple methods in our computational studies. The first is the majority voting method. The second and third are linear combination methods over the whole population. The fourth is a linear combination method over a subset of the whole population. The near optimal subset is obtained by a genetic algorithm search. Our experiments have shown that all four methods have produced better results than those produced by the single best individual.
5651676
Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition
Protein fold recognition is an important step towards understanding protein three-dimensional structures and their functions. A conditional graphical model, i.e. segmentation conditional random fields (SCRFs), is proposed to solve the problem. In contrast to traditional graphical models such as hidden markov model (HMM), SCRFs follow a discriminative approach. It has the flexibility to include overlapping or long-range interaction features over the whole sequence, as well as global optimally solutions for the parameters. On the other hand, the segmentation setting in SCRFs makes its graphical structures intuitively similar to the protein 3-D structures and more importantly, provides a framework to model the long-range interactions directly. 
 
Our model is applied to predict the parallel β-helix fold, an important fold in bacterial infection of plants and binding of antigens. The cross-family validation shows that SCRFs not only can score all known β-helices higher than non β-helices in Protein Data Bank, but also demonstrate more success in locating each rung in the known β-helix proteins than BetaWrap, a state-of-the-art algorithm for predicting β-helix fold, and HMMER, a general motif detection algorithm based on HMM. Applying our prediction model to Uniprot database, we hypothesize previously unknown β-helices.
15500512
Real-time simulation of physically based on-surface flow
Although many papers have been published in the field of fluid simulation, little attention has been paid to on-surface flow involving wetting and stain transportation as well as erosion and deposition phenomena. In this paper, we introduce nonzero divergence in the mass equation of Navier–Stokes equations to simulate water penetration from on-surface flow into substrate material. Also, the volume of fluid method is adopted to track the free surface. With a computation of the actual amount of absorbed water we render the wetting effects with fully dry and fully wet texture images simultaneously. Using our model, the on-surface flow that accompanies water absorption can be simulated realistically in real time with OpenGL preview rendering. Experimental results illustrate that our model can be widely applied to solve various problems related to on-surface flow.
54297489
Iso-Map: Energy-Efficient Contour Mapping in Wireless Sensor Networks
Contour mapping is a crucial part of many wireless sensor network applications. Many efforts have been made to avoid collecting data from all the sensors in the network and producing maps at the sink, which is proven to be inefficient. The existing approaches (often aggregation based), however, suffer from heavy transmission traffic and incur large computational overheads on each sensor node. We propose Iso-Map, an energy-efficient protocol for contour mapping, which builds contour maps based solely on the reports collected from intelligently selected ?isoline nodes? in wireless sensor networks. Iso-Map achieves high-quality contour mapping while significantly reducing the generated traffic from O(n) to O(?n), where n is the total number of sensor nodes in the field. The pernode computation overhead is also restrained as a constant. We conduct comprehensive trace-driven simulations to verify this protocol, and demonstrate that Iso-Map outperforms the previous approaches in the sense that it produces contour maps of high fidelity with significantly reduced energy cost.