Data-flow Analysis of Programs with Associative Arrays

Dynamic programming languages, such as PHP, JavaScript, and Python, provide built-in data structures including associative arrays and objects with similar semantics-object properties can be created at run-time and accessed via arbitrary expressions. While a high level of security and safety of applications written in these languages can be of a particular importance (consider a web application storing sensitive data and providing its functionality worldwide), dynamic data structures pose significant challenges for data-flow analysis making traditional static verification methods both unsound and imprecise. In this paper, we propose a sound and precise approach for value and points-to analysis of programs with associative arrays-like data structures, upon which data-flow analyses can be built. We implemented our approach in a web-application domain-in an analyzer of PHP code.Comment: In Proceedings ESSS 2014, arXiv:1405.055

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

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

DIVA, a data flow language

The underlying principles of concurrency and data flow are summarized along with a survey of the current data flow languages. A high level data flow language, DIVA, is developed that provides the basic data types and language constructs of traditional languages as well as some unique features of data flow. The organization and data structures of the compiler and assembler are also discussed

Common Subexpression Elimination in a Lazy Functional Language

Common subexpression elimination is a well-known compiler optimisation that saves time by avoiding the repetition of the same computation. To our knowledge it has not yet been applied to lazy functional programming languages, although there are several advantages. First, the referential transparency of these languages makes the identification of common subexpressions very simple. Second, more common subexpressions can be recognised because they can be of arbitrary type whereas standard common subexpression elimination only shares primitive values. However, because lazy functional languages decouple program structure from data space allocation and control flow, analysing its effects and deciding under which conditions the elimination of a common subexpression is beneficial proves to be quite difficult. We developed and implemented the transformation for the language Haskell by extending the Glasgow Haskell compiler and measured its effectiveness on real-world programs

Generating Data Flow Programs From Nonprocedural Specifications

Data flow is a mode of parallel computation in which parallelism in a program can be exploited at the fine grained as well as macro level. A data flow computer executes a data dependency graph rather than the program counter controlled sequence of instructions executed by conventional machines. Nonprocedural languages appear to be especially appropriate high level languages for data flow computers. Nonprocedural languages have only two statement forms: data description and assertion. The assertions enumerate the relationships among the data. A data dependency graph is also a suitable representation for a nonprocedural language program (or specification). This research is concerned with translating the dependency graph form of a specification to a program graph for a data flow machine. Specifications in the MODEL language are translated into an intermediate form, the data flow template. The template is a language-independent representation of the specification. The template is then translated into a data flow language (Manchester Dataflow) for the Manchester University machine. The translation consists of creating an array graph to represent the specification; generating the data flow program template from the array graph; and translating the template into MaD