Despite the advances made by modern parsing strategies such as PEG, LL(*), GLR, and GLL, parsing is not a solved problem. Existing approaches suffer from a number of weaknesses, including difficulties supporting side-effecting embedded actions, slow and/or unpredictable performance, and counter-intuitive matching strategies. This paper introduces the ALL(*) parsing strategy that combines the simplicity, efficiency, and predictability of conventional top-down LL(k) parsers with the power of a GLR-like mechanism to make parsing decisions. The critical innovation is to move grammar analysis to parse-time, which lets ALL(*) handle any non-left-recursive context-free grammar. ALL(*) is O(n4) in theory but consistently performs linearly on grammars used in practice, outperforming general strategies such as GLL and GLR by orders of magnitude. ANTLR 4 generates ALL(*) parsers and supports direct left-recursion through grammar rewriting. Widespread ANTLR 4 use (5000 downloads/month in 2013) provides evidence that ALL(*) is effective for a wide variety of applications.

Despite the power of Parser Expression Grammars (PEGs) and GLR, parsing is not a solved problem. Adding nondeterminism (parser speculation) to traditional LL and LR parsers can lead to unexpected parse-time behavior and introduces practical issues with error handling, single-step debugging, and side-effecting embedded grammar actions. This paper introduces the LL(*) parsing strategy and an associated grammar analysis algorithm that constructs LL(*) parsing decisions from ANTLR grammars. At parse-time, decisions gracefully throttle up from conventional fixed k>=1 lookahead to arbitrary lookahead and, finally, fail over to backtracking depending on the complexity of the parsing decision and the input symbols. LL(*) parsing strength reaches into the context-sensitive languages, in some cases beyond what GLR and PEGs can express. By statically removing as much speculation as possible, LL(*) provides the expressivity of PEGs while retaining LL's good error handling and unrestricted grammar actions. Widespread use of ANTLR (over 70,000 downloads/year) shows that it is effective for a wide variety of applications.

Reusing syntax specifications without embedded arbitrary semantic actions is straightforward because the semantic analysis phases of new applications can feed off trees or other intermediate structures constructed by the pre-existing parser. The presence of arbitrary embedded semantic actions, however, makes reuse difficult with existing mechanisms such as grammar inheritance and modules. This short paper proposes a mechanism based upon prototype grammars that automatically pushes changes from prototypes to derived grammars even in the presence of semantic actions. The prototype mechanism alone would be unsuitable for creating a new grammar from multiple preexisting grammars. When combined with grammar composition, however, the prototype mechanism would improve grammar reuse because imported pre-existing grammars could be altered to suit each new application.

Abstract Programmers tend to avoid using language tools, resorting toad hocmethods, because tools can be hard to use, their parsing strategies can be difficult to understand and debug, and their generated parsers can be opaque black‐boxes. In particular, there are two very common difficulties encountered by grammar developers: understanding why a grammar fragment results in a parser non‐determinism and determining why a generated parser incorrectly interprets an input sentence. This paper describes ANTLRWorks, a complete development environment for ANTLR grammars that attempts to resolve these difficulties and, in general, make grammar development more accessible to the average programmer. The main components are a grammar editor with refactoring and navigation features, a grammar interpreter, and a domain‐specific grammar debugger. ANTLRWorks' primary contributions are a parser non‐determinism visualizer based on syntax diagrams and a time‐traveling debugger that pays special attention to parser decision‐making by visualizing lookahead usage and speculative parsing during backtracking. Copyright © 2008 John Wiley & Sons, Ltd.

Search engines regularly crawl the web taking vast snapshots of sitecontent. Because previous crawls are not archived, however, searchresults pertain only to a single, recent instant in time. Search engine users are unable to request pages discussing UK politics in2001, for example. The Internet Archive, an organization dedicated to maintaining such snapshots of the Internet, provides access to many previous web crawls, but lacks a search facility. Users of the ``Way Back Machine'' must provide a specific URL for which they want a listof snapshots organized by date. This short paper describes Chronica, atemporal search engine that indexes Internet Archive crawl data in order to provide search results spanning user-specified time ranges. Chronica can generate graphs showing query result hit counts across a given time span and even side-by-side comparisons of different query results. These graphs can be used to, among other things, track a term's popularity over time for marketing or academic research purposes.

A template engine that strictly enforces model-view separation has been shown to be at least as expressive as a context free grammar allowing the engine to, for example, easily generate any file describable by an XML DTD. When faced with supporting internationalized web applications, however, template engine designers have backed off from enforcing strict separation, allowing unrestricted embedded code segments because it was unclear how localization could otherwise occur. The consequence, unfortunately, is that each reference to a localized data value, such as a date or monetary value, replicates essentially the same snippet of code thousands of times across hundreds of templates for a large site. The potential for cut-and-paste induced bugs and the duplication of code proves a maintenance nightmare. Moreover, page designers are ill-equipped to deal with code fragments. But the difficult question remains: How can localization be done without allowing unrestricted embedded code segments that open the door to model-view entanglement? The answer is simply to automate the localization of data values, thus, avoiding code duplication, making it easier on the developer and designer, and reducing opportunities for the introduction of bugs--all-the-while maintaining the sanctity of strict model-view separation. This paper describes how the StringTemplate template engine strictly enforces model-view separation while handily supporting internationalized web application architectures. Demonstrations of page text localization, locale-specific site designs, and automatic data localization are provided.

The mantra of every experienced web application developer is the same: thou shalt separate business logic from display. Ironically, almost all template engines allow violation of this separation principle, which is the very impetus for HTML template engine development. This situation is due mostly to a lack of formal definition of separation and fear that enforcing separation emasculates a template's power. I show that not only is strict separation a worthy design principle, but that we can enforce separation while providing a potent template engine. I demonstrate my StringTemplate engine, used to build jGuru.com and other commercial sites, at work solving some nontrivial generational tasks.My goal is to formalize the study of template engines, thus, providing a common nomenclature, a means of classifying template generational power, and a way to leverage interesting results from formal language theory. I classify three types of restricted templates analogous to Chomsky's type 1..3 grammar classes and formally define separation including the rules that embody separation.Because this paper provides a clear definition of model-view separation, template engine designers may no longer blindly claim enforcement of separation. Moreover, given theoretical arguments and empirical evidence, programmers no longer have an excuse to entangle model and view.

Abstract Despite the parsing power of LR/LALR algorithms, e.g. YACC, programmers often choose to write recursive‐descent parsers by hand to obtain increased flexibility, better error handling, and ease of debugging. We introduce ANTLR, a public‐domain parser generator that combines the flexibility of hand‐coded parsing with the convenience of a parser generator, which is a component of PCCTS. ANTLR has many features that make it easier to use than other language tools. Most important, ANTLR provides predicates which let the programmer systematically direct the parse via arbitrary expressions using semantic and syntactic context; in practice, the use of predicates eliminates the need to hand‐tweak the ANTLR output, even for difficult parsing problems. ANTLR also integrates the description of lexical and syntactic analysis, accepts LL(k) grammars for k > 1 with extended BNF notation, and can automatically generate abstract syntax trees. ANTLR is widely used, with over 1000 registered industrial and academic users in 37 countries. It has been ported to many popular systems such as the PC, Macintosh, and a variety of UNIX platforms; a commercial C++ front‐end has been developed as a result of one of our industrial collaborations.