288,971 research outputs found
Data Flow Program Graphs
Data flow languages form a subclass of the languages which are based primarily upon function application (i.e., applicative languages). By data flow language we mean any applicative language based entirely upon the notion of data flowing from one function entity to another or any language that directly supports such flowing. This flow concept gives data flow languages the advantage of allowing program definitions to be represented exclusively by graphs. Graphical representations and their applications are the subject of this article
Reliability models for dataflow computer systems
The demands for concurrent operation within a computer system and the representation of parallelism in programming languages have yielded a new form of program representation known as data flow (DENN 74, DENN 75, TREL 82a). A new model based on data flow principles for parallel computations and parallel computer systems is presented. Necessary conditions for liveness and deadlock freeness in data flow graphs are derived. The data flow graph is used as a model to represent asynchronous concurrent computer architectures including data flow computers
Heap Reference Analysis Using Access Graphs
Despite significant progress in the theory and practice of program analysis,
analysing properties of heap data has not reached the same level of maturity as
the analysis of static and stack data. The spatial and temporal structure of
stack and static data is well understood while that of heap data seems
arbitrary and is unbounded. We devise bounded representations which summarize
properties of the heap data. This summarization is based on the structure of
the program which manipulates the heap. The resulting summary representations
are certain kinds of graphs called access graphs. The boundedness of these
representations and the monotonicity of the operations to manipulate them make
it possible to compute them through data flow analysis.
An important application which benefits from heap reference analysis is
garbage collection, where currently liveness is conservatively approximated by
reachability from program variables. As a consequence, current garbage
collectors leave a lot of garbage uncollected, a fact which has been confirmed
by several empirical studies. We propose the first ever end-to-end static
analysis to distinguish live objects from reachable objects. We use this
information to make dead objects unreachable by modifying the program. This
application is interesting because it requires discovering data flow
information representing complex semantics. In particular, we discover four
properties of heap data: liveness, aliasing, availability, and anticipability.
Together, they cover all combinations of directions of analysis (i.e. forward
and backward) and confluence of information (i.e. union and intersection). Our
analysis can also be used for plugging memory leaks in C/C++ languages.Comment: Accepted for printing by ACM TOPLAS. This version incorporates
referees' comment
Parameterized Construction of Program Representations for Sparse Dataflow Analyses
Data-flow analyses usually associate information with control flow regions.
Informally, if these regions are too small, like a point between two
consecutive statements, we call the analysis dense. On the other hand, if these
regions include many such points, then we call it sparse. This paper presents a
systematic method to build program representations that support sparse
analyses. To pave the way to this framework we clarify the bibliography about
well-known intermediate program representations. We show that our approach, up
to parameter choice, subsumes many of these representations, such as the SSA,
SSI and e-SSA forms. In particular, our algorithms are faster, simpler and more
frugal than the previous techniques used to construct SSI - Static Single
Information - form programs. We produce intermediate representations isomorphic
to Choi et al.'s Sparse Evaluation Graphs (SEG) for the family of data-flow
problems that can be partitioned per variables. However, contrary to SEGs, we
can handle - sparsely - problems that are not in this family
Dual nozzle aerodynamic and cooling analysis study
Geometric, aerodynamic flow field, performance prediction, and heat transfer analyses are considered for two advanced chamber nozzle concepts applicable to Earth-to-orbit engine systems. Topics covered include improvements to the dual throat aerodynamic and performance prediction program; geometric and flow field analyses of the dual expander concept; heat transfer analysis of both concepts, and engineering analysis of data from the NASA/MSFC hot-fire testing of a dual throat thruster model thrust chamber assembly. Preliminary results obtained are presented in graphs
Building program understanding tools using visitor combinators
Program understanding tools manipulate program representations, such as abstract syntax trees, control-flow graphs, or data-flow graphs. This paper deals with the use of visitor combinators to conduct such manipulations. Visitor combinators are an extension of the well-known visitor design pattern. They are small, reusable classes that carry out specific visiting steps. They can be composed in different constellations to build more complex visitors. We evaluate the expressiveness, reusability, ease of development, and applicability of visitor combinators to the construction of program understanding tools. To that end, we conduct a case study in the use of visitor combinators for control-flow analysis and visualization as used in a commercial Cobol program understanding tool
Evidence flow graph methods for validation and verification of expert systems
The results of an investigation into the use of evidence flow graph techniques for performing validation and verification of expert systems are given. A translator to convert horn-clause rule bases into evidence flow graphs, a simulation program, and methods of analysis were developed. These tools were then applied to a simple rule base which contained errors. It was found that the method was capable of identifying a variety of problems, for example that the order of presentation of input data or small changes in critical parameters could affect the output from a set of rules
Performing high-level synthesis via program transformations within a theorem prover
In this paper, we present a new methodology towards performing high-level synthesis. During high-level synthesis an algorithmic description is mapped to a structure of hardware components. In our approach, high-level synthesis is performed via program transformations. All transformations are performed within a higher order logic theorem prover thus guaranteeing correctness. Our approach is not restricted to data flow graphs but supports arbitrary computable functions, i.e. mixed control/data flow graphs. Furthermore, the treatment of algorithmic and interface descriptions is orthogonalised, allowing systematic reuse of designs
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