Incremental Evaluation of Ordered Attribute Grammars for Asynchronous Subtree Replacements

Incremental algorithms for evaluating attribute grammars (AGs) have been extensively studied in recent years, primarily because of their application in language-based environments. Ordered attribute grammars are a subclass of AGs for which efficient evaluators can be constructed. Previous incremental algorithms for ordered attribute grammars only allowed one modification to the program at a time, requiring attribute evaluation due to one change to quiesce before another one due to a second change can start. This article presents new incremental evaluation algorithms for ordered attribute grammars that can handle asynchronous program modifications in an optimal manner. Support for asynchronous changes is necessary in environments for multiple users, where different programmers may be making changes to different parts of the program simultaneously. The key to the optimality of the algorithm is an ordering of the attribute evaluations so that an attribute affected by more than one change will only be evaluated once if the changes happen concurrently

Incremental Semantic Evaluation for Interactive Systems: Inertia, Pre-emption, and Relations

Although schemes for incremental semantic evaluation have been explored and refined for more than two decades, the demands of user interaction continue to outstrip the capabilities of these schemes. The feedback produced by a semantic evaluator must support the user's programming activities: it must be structured in a way that provides the user with meaningful insight into the program (directly, or via other tools in the environment) and it must be timely. In this paper we extend an incremental attribute evaluation scheme with three techniques to better meet these demands within the context of a modeless editing system with a flexible tool integration paradigm. Efficient evaluation in the presence of syntax errors (which arise often under modeless editing) is supported by giving semantic attributes inertia: a tendency to not change unless necessary. Pre-emptive evaluation helps to reduce the delays associated with a sequence of edits, allowing an evaluator to "keep pace" with the user. Relations provide a general means to capture semantic structure (for the user, other tools, and as attributes within an evaluation) and are treated efficiently using a form of differential propagation. The combination of these three techniques meets the demands of user interaction; leaving out any one does not

Extending Attribute Grammars to Support Programming-in-the-Large

Attribute grammars add specification of static semantic properties to context-free grammars, which in turn describe the syntactic structure of program units. However, context-free grammars cannot express programming-in-the-large features common in modern programming languages, including unordered collections of units, included units and sharing of included units. We present extensions to context-free grammars, and corresponding extensions to attribute grammars, suitable for defining such features. We explain how batch and incremental attribute evaluation algorithms can be adapted to support these extensions, resulting in a uniform approach to intra-unit and inter-unit static semantic analysis and translation of multi-unit programs

IceDust: Incremental and Eventual Computation of Derived Values in Persistent Object Graphs

Derived values are values calculated from base values. They can be expressed in object-oriented languages by means of getters calculating the derived value, and in relational or logic databases by means of (materialized) views. However, switching to a different calculation strategy (for example caching) in object-oriented programming requires invasive code changes, and the databases limit expressiveness by disallowing recursive aggregation. In this paper, we present IceDust, a data modeling language for expressing derived attribute values without committing to a calculation strategy. IceDust provides three strategies for calculating derived values in persistent object graphs: Calculate-on-Read, Calculate-on-Write, and Calculate-Eventually. We have developed a path-based abstract interpretation that provides static dependency analysis to generate code for these strategies. Benchmarks show that different strategies perform better in different scenarios. In addition we have conducted a case study that suggests that derived value calculations of systems used in practice can be expressed in IceDust