Using temporal logic to specify adaptive program semantics
Computer software must dynamically adapt to changing conditions. In order to fully realize the benefit of dynamic adaptation, it must be performed correctly. The correctness of adaptation cannot be properly addressed without precisely specifying the requirements for adaptation. This paper introduces an approach to formally specifying adaptation requirements in temporal logic. We introduce A-LTL, an adaptation-based extension to linear temporal logic, and use this logic to specify three commonly used adaptation semantics. Composition techniques are developed and applied to A-LTL to construct the specification of an adaptive program. We introduce adaptation semantics graphs to visually represent the adaptation semantics, which can also be used to automatically generate specification for adaptive programs.

title: Modular verification of dynamically adaptive systems
abstract: Cyber-physical systems increasingly rely on dynamically adaptive programs to respond to changes in their physical environment; examples include ecosystem monitoring and disaster relief systems. These systems are considered high-assurance since errors during execution could result in injury, loss of life, environmental impact, and/or financial loss. In order to facilitate the development and verification of dynamically adaptive systems, we separate functional concerns from adaptive concerns. Specifically, we model a dynamically adaptive program as a collection of (non-adaptive) steady-state programs and a set of adaptations that realize transitions among steady state programs in response to environmental changes. We use Linear Temporal Logic (LTL) to specify properties of the non-adaptive portions of the system, and we use A-LTL (an adapt-operator extension toLTL) to concisely specify properties that hold during the adaptation process. Model checking offers an attractive approach to automatically analyzing models for adherence to formal properties and thus providing assurance. However, currently, model checkers are unable to verify properties specified using A-LTL. Moreover, as the number of steady-state programs and adaptations increase, the verification costs (in terms of space and time) potentially become unwieldy. To address these issues, we propose a modular model checking approach to verifying that a formal model of an adaptive program satisfies its requirements specified in LTL and A-LTL, respectively.

title: Specifying real-time properties in autonomic systems
abstract: Increasingly, computer software must adapt dynamically to changing conditions. The correctness of adaptation cannot be rigorously addressed without precisely specifying the requirements for adaptation. In many situations, these requirements involve absolute time, in addition to a logical ordering of events. This paper introduces an approach to formally specifying such timing requirements for adaptive software. We introduce TA-LTL, a timed adaptation-based extension to linear temporal logic, and use this logic to specify three timing properties associated with the adaptation process: safety, liveness, and stability. A dynamic adaptation scenario involving interactive audio streaming software is used to illustrate the timed temporal logic.

title: AMOEBA-RT: Run-Time Verification of Adaptive Software
abstract: Increasingly, software must dynamically adapt its behavior in response to changes in the supporting computing, communication infrastructure, and in the surrounding physical environment. Assurance that the adaptive software correctly satisfies its requirements is crucial if the software is to be used in high assurance systems, such as command and control or critical infrastructure protection systems. Adaptive software development for these systems must be grounded upon formalism and rigorous software engineering methodology to gain assurance. In this paper, we briefly describe AMOebA-RT , a run-time monitoring and verification technique that provides assurance that dynamically adaptive software satisfies its requirements.

title: A model-driven approach to enforce crosscutting assertion checking
abstract: Design by Contract provides an effective principle to enable the construction of robust software by describing properties of a module using logical assertions. This paper presents a model-driven approach for weaving assertion checking aspects into a large software system. The approach is based on a technique called two-level aspect weaving. At the top level, crosscutting assertions are weaved into a model by use of a model weaver. The second step of the weaving process occurs when the Model-Driven Program Transformation technique is applied to perform large-scale adaptation of the underlying source code from the contracts specified in the high-level models. The paper briefly presents a case study to illustrate the concept.

title: Concern Based Approach to Generating SCR Requirement Specification: A Case Study
abstract: SCR is a mature and widely used document driven requirement method, which emphasizes creating strict and complete formal requirement documents during software requirement analysis to serve the whole life circle. However, due to the big gap between textual requirement description and formal requirement document, how to obtain formal SCR requirements specification from informal textual description becomes an obstacle of applying SCR to real projects. In this paper, a concern based approach to generating SCR requirement specification from textual requirement document is proposed. The requirement analysis process includes concerns elicitation, specification of concerns and their relationship, identification of concepts, definition and classification of variables, derivation of SCR requirement specification, and validation of requirement specification. The method introduced in this paper has been applied to a classical case – Light Control System by documenting the requirements of hallway section. It is indicated that our approach bridges the gap between textual requirement description and formal SCR requirement document.

title: Advances in Fuzzy Method for Natural Computing
abstract: Both natural computing and fuzzy method exhibit human-like mental processing. Natural computing is the field of research that works with computational techniques inspired in part by natural systems. Fuzzy method is an alternative to traditional notions of set membership and logic, and it occurs in many applications of engineering, science and medicine. This paper presents a survey of recent advances in fuzzy method for natural computing, such as fuzzy artificial neural networks, fuzzy genetic algorithms, fuzzy ant colony optimization, fuzzy artificial immune systems, etc. We utilize uncertainty handling capacity of fuzzy method for modeling ambiguity, and the learning ability of natural computing for efficiently traversing large search spaces.

title: Application of Immune Classifier Based on Increment of Diversity in the Model Species Genomes Identification
abstract: The model species genomes project has played a very important role in the research of human genomes. By comparing and identifying the genomes' information in the different biological evolution stages with the model species genomes, it is favorable to understand deeply the genomes' structure and function of the advanced species, especially the human being, and to reveal the life's essential law. In the paper, the DNA sequences of three model species including C. elegans, S. cerevisiae and A.thaliana are divided into three types: intron, exon, intergenic DNA at first. The bases of each sequence are given number (1, 2, hellip, N) base by base from the beginning. According to three phases of the codons, we can extract three subsequences which numbers are respectively 3n+1, 3n+2 and 3n+3 (n=0, 1, 2, ...,N/3-1). Calculating respectively the probability of four bases in three subsequence we can attain 12 parameters which are regarded as the state parameters of the diversity sources. Each sequence of intron, exon and intergenic DNA is expressed by a 12-dimension eigenvector. All of these sequences' 12-dimension samples are divided into the training sample set and the testing sample set. Then, according to the immune network theory, a immune classifier based on the diversity increment is constructed, which considers the reciprocal of the diversity increment as affinity function and makes the immune network evolve in the direction of identifying the antigens by submitting unceasingly the antigens one by one, which is a record of the training sample set. Finally, the classifier has high performance and its prediction accuracy is up to 85% by test.

title: Multi-User Joint Doppler Spread Estimation in Generalized Distributed Antenna System
abstract: Generalized distributed antenna is one of the most promising architectures likely to be used in next generation mobile communication systems. In this paper, based on the architecture, multi-user co-channel interference in Doppler spread estimation is analyzed and several useful conclusions are obtained. Moreover, in order to combat this interference, a novel ACF-based multi-user joint Doppler spread estimation (M- JDSE) algorithm is proposed, taking advantage of centralized signal processing characteristic in generalized distributed antenna systems. Both theoretical analysis and simulation results demonstrate the significant performance improvement of proposed M-JDSE algorithm in multi-user environments.