A Declarative Framework for Analysis and Optimization

Abstract

DeepWeaver-1 is a tool supporting cross-cutting program analysis and transformation components, called "weaves". Like an aspect, a DeepWeaver weave consists of a query part, and a part which may modify code. DeepWeaver's query language is based on Prolog, and provides access to data-flow and control-flow reachability analyses. DeepWeaver provides a declarative way to access the internal structure of methods, and supports cross-cutting weaves which operate on code blocks from different parts of the codebase simultaneously. Deep-Weaver operates at the level of bytecode, but offers predicates to extract structured control flow constructs. This paper motivates the design, and demonstrates some of its power, using a sequence of examples including performance profiling and domain-specific performance optimisations for database access and remote method invocation. Introduction. Aspect-oriented programming tools, such as AspectJ [12], can be used to implement performance optimizations. However, tools like AspectJ are too weak, both to perform interesting optimizing transformations, and to capture the conditions for their validity. Similar problems arise when using AspectJ for static program analysis, e.g. to check usage rules for library code, or to detect software defects. For many, this is a consequence of deliberate simplicity in the aspect language design. This paper presents a prototype system which is powerful enough to express complex analyses (and transformations)-yet, like an aspect weaver, retains a declarative style by which some simplicity can be retained. The tool is motivated and illustrated using a series of examples, including intramethod performance profiling, and domain-specific optimizations for database access and remote method invocation. Example. We begin with a very simple motivating example, a domain-specific performance optimisation for Java code that uses the JDBC (Java Database Connectivity) library. Consider this Java fragment: ResultSet staff = statement.executeQuery("SELECT * FROM employees"); ResultSet clients = statement.executeQuery("SELECT * FROM customers"); ... complex and messy code that uses clients but not staff ...

JavaDL: automatically incrementalizing Java bug pattern detection

“…Beyond SOUL, Visser [2002] argues in favor of syntactic pattern matching, with Fischer and Visser [2004] opting for concrete syntax over AST matching by arguing that "the simple abstract syntax approach quickly becomes cumbersome as the schemas become largerž. Their AutoBayes system combines syntactic pattern matching with Prolog, compared to which DeepWeaver [Falconer et al 2007] adds program rewriting for implementing aspect weaving. Another related system with syntactic pattern matching is our earlier MetaDL [Dura et al 2019], which analyzes a Datalog dialect, in which it needs to match only one syntactic category.…”

A Precise Framework for Source-Level Control-Flow Analysis

“…Like our system, SOUL uses on-demand evaluation. DeepWeaver [10] supports data flow analysis and program transformation on byte code. Meanwhile, Flix [24] combines Datalog-style fixpoint computations and functional programming for declarative data flow analysis, and can scale IFDS/IDE-style interprocedural data flow analysis to nontrivial software [25].…”

Code querying by UML

“…For example, languages based on graph rewrite rules [18], logic formulas [1]- [3], [7], [14], [20], [26], and constraint programming [13] have been proposed to express structural characteristics. In order to express behavioral characteristics, we find approaches based on reachability queries [8], [24], [25], temporal logic formulas [15], state machines [11], and logic formulas [12], [16] that reason over the results of data flow and control flow analyses. Related to these approaches is also our previous work on SOUL [6].…”