Array P Systems and t−Communication

The two areas of grammar systems and P systems, which have provided interesting computational models in the study of formal string language theory have been in the recent past effectively linked in [4] by incorporating into P systems, a communication mode called t−mode of cooperating distributed grammar systems. On the other hand cooperating array grammar systems [5]and array P systems [1] have been developed in the context of two-dimensional picture description. In this paper, motivated by the study of [4], these two systems are studied by linking them through the t−communication mode, thus bringing out the picture description power of these systems

Capturing CFLs with Tree Adjoining Grammars

We define a decidable class of TAGs that is strongly equivalent to CFGs and is cubic-time parsable. This class serves to lexicalize CFGs in the same manner as the LCFGs of Schabes and Waters but with considerably less restriction on the form of the grammars. The class provides a normal form for TAGs that generate local sets in much the same way that regular grammars provide a normal form for CFGs that generate regular sets.Comment: 8 pages, 3 figures. To appear in proceedings of ACL'9

Terminator Detection by Support Vector Machine Utilizing a Stochastic Context-Free Grammar

A 2-stage detector was designed to find rho-independent transcription terminators in the Escherichia coli genome. The detector includes a stochastic context free grammar (SCFG) component and a support vector machine (SVM) component. To find terminators, the SCFG searches the intergenic regions of nucleotide sequence for local matches to a terminator grammar that was designed and trained utilizing examples of known terminators. The grammar selects sequences that are the best candidates for terminators and assigns them a prefix, stem-loop, suffix structure using the Cocke-Younger-Kasaami (CYK) algorithm, modified to incorporate energy effects of base pairing. The parameters from this inferred structure are passed to the SVM classifier, which distinguishes terminators from non-terminators that score high according to the terminator grammar. The SVM was trained with negative examples drawn from intergenic sequences that include both featureless and RNA gene regions (which were assigned prefix, stem-loop, suffix structure by the SCFG), so that it successfully distinguishes terminators from either of these. The classifier was found to be 96.4% successful during testin

Implementation and Optimization of PEG Parsers for Use on FPGAs

DARPA’s Guaranteed Architecture for Physical Security (GAPS) project requires a device to provably enforce security policies. As part of a solution that GE and Dartmouth have proposed for the GAPS project, parsers for Parsing Expression Grammars (PEGs) are required to run on a Field-Programmable Gate Array (FPGA). There exist programs, like Pegmatite, which produce PEG parsers written in VHDL, but these parsers have not yet been run on FPGAs. They have been run in simulators where they have been tested for correctness, but they need to be adapted for execution on FPGAs (Lucas et al., 2021). This thesis explores the process of modifying existing VHDL PEG parsers to run on FPGAs and optimizing their performance. We contribute two techniques to achieve performance improvements: (1) exploiting data parallelism, and (2) parsing the input packet as it arrives instead of waiting for the entire packet to be received. We were not able to execute our solution consistently on FPGAs, so we present an analysis of these techniques through simulations

On the Practice and Application of Context-Free Language Reachability

The Context-Free Language Reachability (CFL-R) formalism relates to some of the most important computational problems facing researchers and industry practitioners. CFL-R is a generalisation of graph reachability and language recognition, such that pairs in a labelled graph are reachable if and only if there is a path between them whose labels, joined together in the order they were encountered, spell a word in a given context-free language. The formalism finds particular use as a vehicle for phrasing and reasoning about program analysis, since complex relationships within the data, logic or structure of computer programs are easily expressed and discovered in CFL-R. Unfortunately, The potential of CFL-R can not be met by state of the art solvers. Current algorithms have scalability and expressibility issues that prevent them from being used on large graph instances or complex grammars. This work outlines our efforts in understanding the practical concerns surrounding CFL-R, and applying this knowledge to improve the performance of CFL-R applications. We examine the major difficulties with solving CFL-R-based analyses at-scale, via a case-study of points-to analysis as a CFL-R problem. Points-to analysis is fundamentally important to many modern research and industry efforts, and is relevant to optimisation, bug-checking and security technologies. Our understanding of the scalability challenge motivates work in developing practical CFL-R techniques. We present improved evaluation algorithms and declarative optimisation techniques for CFL-R, capitalising on the simplicity of CFL-R to creating fully automatic methodologies. The culmination of our work is a general-purpose and high-performance tool called Cauliflower, a solver-generator for CFL-R problems. We describe Cauliflower and evaluate its performance experimentally, showing significant improvement over alternative general techniques