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Context: In the first part of his 2012 presentation "Inventing on Principle", Bret Victor gives a demo of a live code editor for Javascript which shows the dynamic history of values of variables in real time. This form of live programming has become known as "probes". Probes provide the programmer with permanent and continuous insight into the dynamic evolution of function or method variables, thus improving feedback and developer experience. Inquiry: Although Victor shows a working prototype of live probes in the context of Javascript, he does not discuss strategies for implementing them. Later work provides an implementation approach, but this requires a programming language to be implemented on top of the GraalVM runtime. In this paper we present **LiveRec**, a generic approach for implementing probes which can be applied in the context of many programming languages, without requiring the modification of compilers or run-time systems. Approach: **LiveRec** is based on reusing existing debug protocols to implement probes. Methods or functions are compiled after every code change and executed inside the debugger. During execution the evolution of all local variables in the current stack frame are recorded and communicated back to the editor or IDE for display to the user. Knowledge: It turns out that mainstream debug protocols are rich enough for implementing live probes. Step-wise execution, code hot swapping, and stack frame inspection provide the right granularity and sufficient information to realize live probes, without modifying compilers or language runtimes. Furthermore, it turns out that the recently proposed Debugger Adapter Protocol (DAP) provides an even more generic approach of implementing live probes, but, in some cases, at the cost of a significant performance penalty. Grounding: We have applied **LiveRec** to implement probes using stack recording natively for Java through the Java Debug Interface (JDI), and through the DAP for Java, Python, C, and Javascript, all requiring just modest amounts of configuration code. We evaluate the run-time performance of all four probes prototypes, decomposed into: compile-after-change, hot swap, single step overhead, and stack recording overhead. Our initial results show that live probes on top of native debug APIs can be performant enough for interactive use. In the case of DAP, however, it highly depends on characteristics of the programming language implementation and its associated debugging infrastructure. Importance: Live programming improves the programmer experience by providing immediate feedback about a program's execution and eliminating disruptive edit-compile-restart sequences. Probes are one way to shorten the programmer feedback loop at the level of functions and methods. Although probes are not new, and have been implemented in (prototype) systems, **LiveRec**'s approach of building live probes on top of existing and generic debug protocols promises a path towards probes for a host of mainstream programming languages, with reasonable effort.

Schema change is an unsolved problem in both live programming and local-first software. We include in schema change any change to the expected shape of data, whether that is expressed explicitly in a database schema or type system, or whether those expectations are implicit in the behavior of the code. Schema changes during live programming can create a mismatch between the code and data in the running environment. Similarly, schema changes in local-first programming can create mismatches between data in different replicas, and between data in a replica and the code colocated with it. In all of these situations the problem of schema change is to migrate or translate existing data in coordination with changes to the code. This paper contributes a set of concrete scenarios involving schema change that are offered as challenge problems to the live programming and local-first communities. We hope that these problems will spur progress by providing concrete objectives and a basis for comparing alternative solutions., Comment: To appear at LIVE Programming Workshop, October 24, 2023, ACM SIGPLAN conference on Systems, Programming, Languages, and Applications (SPLASH) Cascais, Portugal

Context: Computational notebooks are a contemporary style of literate programming, in which users can communicate and transfer knowledge by interleaving executable code, output, and prose in a single rich document. A Domain-Specific Language (DSL) is an artificial software language tailored for a particular application domain. Usually, DSL users are domain experts that may not have a software engineering background. As a consequence, they might not be familiar with Integrated Development Environments (IDEs). Thus, the development of tools that offer different interfaces for interacting with a DSL is relevant. Inquiry: However, resources available to DSL designers are limited. We would like to leverage tools used to interact with general purpose languages in the context of DSLs. Computational notebooks are an example of such tools. Then, our main question is: What is an efficient and effective method of designing and implementing notebook interfaces for DSLs? By addressing this question we might be able to speed up the development of DSL tools, and ease the interaction between end-users and DSLs. Approach: In this paper, we present Bacat\'a, a mechanism for generating notebook interfaces for DSLs in a language parametric fashion. We designed this mechanism in a way in which language engineers can reuse as many language components (e.g., language processors, type checkers, code generators) as possible. Knowledge: Our results show that notebook interfaces generated by Bacat\'a can be automatically generated with little manual configuration. There are few considerations and caveats that should be addressed by language engineers that rely on language design aspects. The creation of a notebook for a DSL with Bacat\'a becomes a matter of writing the code that wires existing language components in the Rascal language workbench with the Jupyter platform. Grounding: We evaluate Bacat\'a by generating functional computational notebook interfaces for three different non-trivial DSLs, namely: a small subset of Halide (a DSL for digital image processing), SweeterJS (an extended version of JavaScript), and QL (a DSL for questionnaires). Additionally, it is relevant to generate notebook implementations rather than implementing them manually. We measured and compared the number of Source Lines of Code (SLOCs) that we reused from existing implementations of those languages. Importance: The adoption of notebooks by novice-programmers and end-users has made them very popular in several domains such as exploratory programming, data science, data journalism, and machine learning. Why are they popular? In (data) science, it is essential to make results reproducible as well as understandable. However, notebooks are only available for GPLs. This paper opens up the notebook metaphor for DSLs to improve the end-user experience when interacting with code and to increase DSLs adoption.

Context: Concurrent objects with asynchronous messaging are an increasingly popular way to structure highly available, high performance, large-scale software systems. To ensure data-consistency and support synchronization between objects such systems often use distributed transactions with Two-Phase Locking (2PL) for concurrency control and Two-Phase commit (2PC) as atomic commitment protocol. Inquiry In highly available, high-throughput systems, such as large banking infrastructure, however, 2PL becomes a bottleneck when objects are highly contended, when an object is queuing a lot of messages because of locking. Approach: In this paper we introduce Path-Sensitive Atomic Commit (PSAC) to address this situation. We start from message handlers (or methods), which are decorated with pre- and post-conditions, describing their guards and effect. Knowledge: This allows the PSAC lock mechanism to check whether the effect of two incoming messages at the same time are independent, and to avoid locking if this is the case. As a result, more messages are directly accepted or rejected, and higher overall throughput is obtained. Grounding: We have implemented PSAC for a state machine-based DSL called Rebel, on top of a runtime based on the Akka actor framework. Our performance evaluation shows that PSAC exhibits the same scalability and latency characteristics as standard 2PL/2PC, and obtains up to 1.8 times median higher throughput in congested scenarios. Importance: We believe PSAC is a step towards enabling organizations to build scalable distributed applications, even if their consistency requirements are not embarrassingly parallel.

Context: Meta programming consists for a large part of matching, analyzing, and transforming syntax trees. Many meta programming systems process abstract syntax trees, but this requires intimate knowledge of the structure of the data type describing the abstract syntax. As a result, meta programming is error-prone, and meta programs are not resilient to evolution of the structure of such ASTs, requiring invasive, fault-prone change to these programs. Inquiry: Concrete syntax patterns alleviate this problem by allowing the meta programmer to match and create syntax trees using the actual syntax of the object language. Systems supporting concrete syntax patterns, however, require a concrete grammar of the object language in their own formalism. Creating such grammars is a costly and error-prone process, especially for realistic languages such as Java and C++. Approach: In this paper we present Concretely, a technique to extend meta programming systems with pluggable concrete syntax patterns, based on external, black box parsers. We illustrate Concretely in the context of Rascal, an open-source meta programming system and language workbench, and show how to reuse existing parsers for Java, JavaScript, and C++. Furthermore, we propose Tympanic, a DSL to declaratively map external AST structures to Rascal's internal data structures. Tympanic allows implementors of Concretely to solve the impedance mismatch between object-oriented class hierarchies in Java and Rascal's algebraic data types. Both the algebraic data type and AST marshalling code is automatically generated. Knowledge: The conceptual architecture of Concretely and Tympanic supports the reuse of pre-existing, external parsers, and their AST representation in meta programming systems that feature concrete syntax patterns for matching and constructing syntax trees. As such this opens up concrete syntax pattern matching for a host of realistic languages for which writing a grammar from scratch is time consuming and error-prone, but for which industry-strength parsers exist in the wild. Grounding: We evaluate Concretely in terms of source lines of code (SLOC), relative to the size of the AST data type and marshalling code. We show that for real programming languages such as C++ and Java, adding support for concrete syntax patterns takes an effort only in the order of dozens of SLOC. Similarly, we evaluate Tympanic in terms of SLOC, showing an order of magnitude of reduction in SLOC compared to manual implementation of the AST data types and marshalling code. Importance: Meta programming has applications in reverse engineering, reengineering, source code analysis, static analysis, software renovation, domain-specific language engineering, and many others. Processing of syntax trees is central to all of these tasks. Concrete syntax patterns improve the practice of constructing meta programs. The combination of Concretely and Tympanic has the potential to make concrete syntax patterns available with very little effort, thereby improving and promoting the application of meta programming in the general software engineering context.

The goal of the DSLDI workshop is to bring together researchers and practitioners interested in sharing ideas on how DSLs should be designed, implemented, supported by tools, and applied in realistic application contexts. We are both interested in discovering how already known domains such as graph processing or machine learning can be best supported by DSLs, but also in exploring new domains that could be targeted by DSLs. More generally, we are interested in building a community that can drive forward the development of modern DSLs. These informal post-proceedings contain the submitted talk abstracts to the 3rd DSLDI workshop (DSLDI'15), and a summary of the panel discussion on Language Composition.

Program transformations in terms of abstract syntax trees compromise referential integrity by introducing variable capture. Variable capture occurs when in the generated program a variable declaration accidentally shadows the intended target of a variable reference. Existing transformation systems either do not guarantee the avoidance of variable capture or impair the implementation of transformations. We present an algorithm called name-fix that automatically eliminates variable capture from a generated program by systematically renaming variables. name-fix is guided by a graph representation of the binding structure of a program, and requires name-resolution algorithms for the source language and the target language of a transformation. name-fix is generic and works for arbitrary transformations in any transformation system that supports origin tracking for names. We verify the correctness of name-fix and identify an interesting class of transformations for which name-fix provides hygiene. We demonstrate the applicability of name-fix for implementing capture-avoiding substitution, inlining, lambda lifting, and compilers for two domain-specific languages., Comment: In Proceedings of European Conference on Object-Oriented Programming (ECOOP) 2014

Algebraic specification has a long tradition in bridging the gap between specification and programming by making specifications executable. Building on extensive experience in designing, implementing and using specification formalisms that are based on algebraic specification and term rewriting (namely Asf and Asf+Sdf), we are now focusing on using the best concepts from algebraic specification and integrating these into a new programming language: Rascal. This language is easy to learn by non-experts but is also scalable to very large meta-programming applications. We explain the algebraic roots of Rascal and its main application areas: software analysis, software transformation, and design and implementation of domain-specific languages. Some example applications in the domain of Model-Driven Engineering (MDE) are described to illustrate this., Comment: In Proceedings AMMSE 2011, arXiv:1106.5962