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Results in Journal ACM SIGPLAN Notices: 11,152

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Larissa Rocha Soares, Jens Meinicke, Sarah Nadi, Christian Kästner, Eduardo Santana De Almeida
ACM SIGPLAN Notices, Volume 53, pp 40-52; https://doi.org/10.1145/3393934.3278127

Abstract:
In highly configurable systems, features may interact unexpectedly and produce faulty behavior. Those faults are not easily identified from the analysis of each feature separately, especially when feature specifications are missing. We propose VarXplorer, a dynamic and iterative approach to detect suspicious interactions. It provides information on how features impact the control and data flow of the program. VarXplorer supports developers with a graph that visualizes this information, mainly showing suppress and require relations between features. To evaluate whether VarXplorer helps improve the performance of identifying suspicious interactions, we perform a controlled study with 24 subjects. We find that with our proposed feature-interaction graphs, participants are able to identify suspicious interactions more than 3 times faster compared to the state-of-the-art tool.
Sebastian Ruland, Lars Luthmann, Johannes Bürdek, Sascha Lity, Thomas Thüm, Malte Lochau, Márcio Ribeiro
ACM SIGPLAN Notices, Volume 53, pp 119-133; https://doi.org/10.1145/3393934.3278130

Abstract:
Recent research on quality assurance (QA) of configurable software systems (e.g., software product lines) proposes different analysis strategies to cope with the inherent complexity caused by the well-known combinatorial-explosion problem. Those strategies aim at improving efficiency of QA techniques like software testing as compared to brute-force configuration-by-configuration analysis. Sampling constitutes one of the most established strategies, defining criteria for selecting a drastically reduced, yet sufficiently diverse subset of software configurations considered during QA. However, finding generally accepted measures for assessing the impact of sample-based analysis on the effectiveness of QA techniques is still an open issue. We address this problem by lifting concepts from single-software mutation testing to configurable software. Our framework incorporates a rich collection of mutation operators for product lines implemented in C to measure mutation scores of samples, including a novel family-based technique for product-line mutation detection. Our experimental results gained from applying our tool implementation to a collection of subject systems confirms the widely-accepted assumption that pairwise sampling constitutes the most reasonable efficiency/effectiveness trade-off for sample-based product-line testing.
Gabriel Radanne, Peter Thiemann
ACM SIGPLAN Notices, Volume 53, pp 202-214; https://doi.org/10.1145/3393934.3278133

Abstract:
Regular expressions are part of every programmer’s toolbox. They are used for a wide variety of language-related tasks and there are many algorithms for manipulating them. In particular, matching algorithms that detect whether a word belongs to the language described by a regular expression are well explored, yet new algorithms appear frequently. However, there is no satisfactory methodology for testing such matchers. We propose a testing methodology which is based on generating positive as well as negative examples of words in the language. To this end, we present a new algorithm to generate the language described by a generalized regular expression with intersection and complement operators. The complement operator allows us to generate both positive and negative example words from a given regular expression. We implement our generator in Haskell and OCaml and show that its performance is more than adequate for testing.
Jácome Cunha, Mihai Dan, Martin Erwig, Danila Fedorin, Alex Grejuc
ACM SIGPLAN Notices, Volume 53, pp 161-167; https://doi.org/10.1145/3393934.3278136

Abstract:
Based on the concept of explanation sheets, we present an approach to make spreadsheets easier to understand and thus easier to use and maintain. We identify the notion of explanation soundness and show that explanation sheets which conform to simple rules of formula coverage provide sound explanations. We also present a practical evaluation of explanation sheets based on samples drawn from widely used spreadsheet corpora and based on a small user study. In addition to supporting spreadsheet understanding and maintenance, our work on explanation sheets has also uncovered several general principles of explanation languages that can help guide the design of explanations for other programming and domain-specific languages.
L. Thomas Van Binsbergen
ACM SIGPLAN Notices, Volume 53, pp 168-174; https://doi.org/10.1145/3393934.3278132

Abstract:
The PLanCompS project proposes a component-based approach to programming-language development in which fundamental constructs (funcons) are reused across language definitions. Homogeneous Generative Meta-Programming (HGMP) enables writing programs that generate code as data, at run-time or compile-time, for manipulation and staged evaluation. Building on existing formalisations of HGMP, this paper introduces funcons for HGMP and demonstrates their usage in component-based semantics.
Michael Nieke, , Christoph Seidl, Thomas Thüm, Ingrid Chieh Yu, Felix Franzke
ACM SIGPLAN Notices, Volume 53, pp 188-201; https://doi.org/10.1145/3393934.3278123

Abstract:
Software Product Lines (SPLs) are a common technique to capture families of software products in terms of commonalities and variabilities. On a conceptual level, functionality of an SPL is modeled in terms of features in Feature Models (FMs). As other software systems, SPLs and their FMs are subject to evolution that may lead to the introduction of anomalies (e.g., non-selectable features). To fix such anomalies, developers need to understand the cause for them. However, for large evolution histories and large SPLs, explanations may become very long and, as a consequence, hard to understand. In this paper, we present a method for anomaly detection and explanation that, by encoding the entire evolution history, identifies the evolution step of anomaly introduction and explains which of the performed evolution operations lead to it. In our evaluation, we show that our method significantly reduces the complexity of generated explanations.
Laurent Christophe, Coen De Roover, Elisa Gonzalez Boix, Wolfgang De Meuter
ACM SIGPLAN Notices, Volume 53, pp 107-118; https://doi.org/10.1145/3393934.3278135

Abstract:
Dynamic analyses are commonly implemented by instrumenting the program under analysis. Examples of such analyses for JavaScript range from checkers of user- defined invariants to concolic testers. For a full-stack JavaScript program, these analyses would benefit from reasoning about the state of the client-side and server-side processes it is comprised of. Lifting a dynamic analysis so that it supports full-stack programs can be challenging. It involves distributed communication to maintain the analysis state across all processes, which has to be deadlock-free. In this paper, we advocate maintaining distributed analysis state in a centralized analysis process instead — which is communicated with from the processes under analysis. The approach is supported by a dynamic analysis platform that provides abstractions for this communication. We evaluate the approach through a case study. We use the platform to build a distributed origin analysis, capable of tracking the expressions from which values originate from across process boundaries, and deploy it on collaborative drawing application. The results show that our approach greatly simplifies the lifting process at the cost of a computational overhead. We deem this overhead acceptable for analyses intended for use at development time.
Sven Peldszus, Daniel Strüber, Jan Jürjens
ACM SIGPLAN Notices, Volume 53, pp 93-106; https://doi.org/10.1145/3393934.3278126

Abstract:
Today's software systems are too complex to ensure security after the fact – security has to be built into systems by design. To this end, model-based techniques such as UMLsec support the design-time specification and analysis of security requirements by providing custom model annotations and checks. Yet, a particularly challenging type of complexity arises from the variability of software product lines. Analyzing the security of all products separately is generally infeasible. In this work, we propose SecPL, a methodology for ensuring security in a software product line. SecPL allows developers to annotate the system design model with product-line variability and security requirements. To keep the exponentially large configuration space tractable during security checks, SecPL provides a family-based security analysis. In our experiments, this analysis outperforms the naive strategy of checking all products individually. Finally, we present the results of a user study that indicates the usability of our overall methodology.
Nicolas Stucki, Aggelos Biboudis, Martin Odersky
ACM SIGPLAN Notices, Volume 53, pp 14-27; https://doi.org/10.1145/3393934.3278139

Abstract:
Program generation is indispensable. We propose a novel unification of two existing metaprogramming techniques: multi-stage programming and hygienic generative macros. The former supports runtime code generation and execution in a type-safe manner while the latter offers compile-time code generation. In this work we draw upon a long line of research on metaprogramming, starting with Lisp, MetaML and MetaOCaml. We provide direct support for quotes, splices and top-level splices, all regulated uniformly by a level-counting Phase Consistency Principle. Our design enables the construction and combination of code values for both expressions and types. Moreover, code generation can happen either at runtime à la MetaML or at compile time, in a macro fashion, à la MacroML. We provide an implementation of our design in Scala and we present two case studies. The first implements the Hidden Markov Model, Shonan Challenge for HPC. The second implements the staged streaming library Strymonas.
Ebrahim Khalaj, Marwan Abi-Antoun
ACM SIGPLAN Notices, Volume 53, pp 53-65; https://doi.org/10.1145/3393934.3278128

Abstract:
Ownership type qualifiers clarify aliasing invariants that cannot be directly expressed in mainstream programming languages. Adding qualifiers to code, however, often involves significant overhead and difficult interaction. We propose an analysis to infer qualifiers in the code based on developer refinements that express strict encapsulation, logical containment and architectural tiers. Refinements include: makeOwnedBy, to make an object strictly encapsulated by another; makePartOf, to make an object logically contained in another; makePeer, to make two objects peers; makeParam, to make an object more accessible than the above choices; or makeShared, to allow an object to be globally aliased. If the code as-written matches the requested refinements, the analysis generates qualifiers that type-check; otherwise, it reports that the refinements do not match the code, so developers must investigate unexpected aliasing, change their understanding of the code and pick different refinements, or change the code and re-run the analysis. We implement the analysis and confirm that refinements generate precise qualifiers that express strict encapsulation, logical containment and architectural tiers.
Yin Liu, Kijin An, Eli Tilevich
ACM SIGPLAN Notices, Volume 53, pp 175-187; https://doi.org/10.1145/3393934.3278137

Abstract:
Real-time systems must meet strict timeliness requirements. These systems also often need to protect their critical program information (CPI) from adversarial interference and intellectual property theft. Trusted execution environments (TEE) execute CPI tasks on a special-purpose processor, thus providing hardware protection. However, adapting a system written to execute in environments without TEE requires partitioning the code into the regular and trusted parts. This process involves complex manual program transformations that are not only laborious and intellectually tiresome, but also hard to validate and verify for the adherence to real-time constraints. To address these problems, this paper presents novel program analyses and transformation techniques, accessible to the developer via a declarative meta-programming model. The developer declaratively specifies the CPI portion of the system. A custom static analysis checks CPI specifications for validity, while probe-based profiling helps identify whether the transformed system would continue to meet the original real-time constraints, with a feedback loop suggesting how to modify the code, so its CPI can be isolated. Finally, an automated refactoring isolates the CPI portion for TEE-based execution, communicated with through generated calls to the TEE API. We have evaluated our approach by successfully enabling the trusted execution of the CPI portions of several microbenchmarks and a drone autopilot. Our approach shows the promise of declarative meta-programming in reducing the programmer effort required to adapt systems for trusted execution under real-time constraints.
William Gallard Hatch, Matthew Flatt
ACM SIGPLAN Notices, Volume 53, pp 28-39; https://doi.org/10.1145/3393934.3278129

Abstract:
Command languages like the Bourne Shell provide a terse syntax for exploratory programming and system interaction. Shell users can begin to write programs that automate their tasks by simply copying their interactions verbatim into a script file. However, command languages usually scale poorly beyond small scripts, and they can be difficult to integrate into larger programs. General-purpose languages scale well, but are verbose and unwieldy for common interactive actions such as process composition. We present Rash, a domain-specific command language embedded in Racket. Rash provides a terse and extensible syntax for interactive system administration and scripting, as well as easy composition of both Racket functions and operating system processes. Rash and normal Racket code can be nested together at the expression level, providing the benefits of a shell language and a general-purpose language together. Thus, Rash provides a gradual scale between shell-style interactions and general-purpose programming.
Karl Smeltzer, Martin Erwig
ACM SIGPLAN Notices, Volume 53, pp 1-13; https://doi.org/10.1145/3393934.3278138

Abstract:
With an ever-growing amount of collected data, the importance of visualization as an analysis component is growing in concert. The creation of good visualizations often doesn't happen in one step but is rather an iterative and exploratory process. However, this process is currently not well supported in most of the available visualization tools and systems. Visualization authors are forced to commit prematurely to particular design aspects of their creations, and when exploring potential variant visualizations, they are forced to adopt ad hoc techniques such as copying code snippets or keeping a collection of separate files. We propose variational visualizations as a model supporting open-ended exploration of the design space of information visualization. Together with that model, we present a prototype implementation in the form of a domain-specific language embedded in Purescript.
Adilla Susungi, Norman A. Rink, Albert Cohen, Jeronimo Castrillon, Claude Tadonki
ACM SIGPLAN Notices, Volume 53, pp 79-92; https://doi.org/10.1145/3393934.3278131

Abstract:
Many modern application domains crucially rely on tensor operations. The optimization of programs that operate on tensors poses difficulties that are not adequately addressed by existing languages and tools. Frameworks such as TensorFlow offer good abstractions for tensor operations, but target a specific domain, i.e. machine learning, and their optimization strategies cannot easily be adjusted to other domains. General-purpose optimization tools such as Pluto and existing meta-languages offer more flexibility in applying optimizations but lack abstractions for tensors. This work closes the gap between domain-specific tensor languages and general-purpose optimization tools by proposing the Tensor optimizations Meta-Language (TeML). TeML offers high-level abstractions for both tensor operations and loop transformations, and enables flexible composition of transformations into effective optimization paths. This compositionality is built into TeML's design, as our formal language specification will reveal. We also show that TeML can express tensor computations as comfortably as TensorFlow and that it can reproduce Pluto's optimization paths. Thus, optimized programs generated by TeML execute at least as fast as the corresponding Pluto programs. In addition, TeML enables optimization paths that often allow outperforming Pluto.
Ahmad Salim Al-Sibahi, Thomas P. Jensen, Aleksandar S. Dimovski, Andrzej Wąsowski
ACM SIGPLAN Notices, Volume 53, pp 147-160; https://doi.org/10.1145/3393934.3278125

Abstract:
High-level transformation languages like Rascal include expressive features for manipulating large abstract syntax trees: first-class traversals, expressive pattern matching, backtracking and generalized iterators. We present the design and implementation of an abstract interpretation tool, Rabit, for verifying inductive type and shape properties for transformations written in such languages. We describe how to perform abstract interpretation based on operational semantics, specifically focusing on the challenges arising when analyzing the expressive traversals and pattern matching. Finally, we evaluate Rabit on a series of transformations (normalization, desugaring, refactoring, code generators, type inference, etc.) showing that we can effectively verify stated properties.
Nic Volanschi, Bernard Serpette, Charles Consel
ACM SIGPLAN Notices, Volume 53, pp 66-78; https://doi.org/10.1145/3393934.3278134

Abstract:
In spite of the fact that many sensors in use today are binary (i.e. produce only values of 0 and 1), and that useful context-aware applications are built exclusively on top of them, there is currently no development approach specifically targeted to binary sensors. Dealing with notions of state and state combinators, central to binary sensors, is tedious and error-prone in current approaches. For instance, developing such applications in a general programming language requires writing code to process events, maintain state and perform state transitions on events, manage timers and/or event histories. In another paper, we introduced a domain specific language (DSL) called Allen, specifically targeted to binary sensors. Allen natively expresses states and state combinations, and detects contexts on line, on incoming streams of binary events. Expressing state combinations in Allen is natural and intuitive due to a key ingredient: semi-causal operators. That paper focused on the concept of the language and its main operators, but did not address its implementation challenges. Indeed, online evaluation of expressions containing semi-causal operators is difficult, because semi-causal sub-expressions may block waiting for future events, thus generating unknown values, besides 0 and 1. These unknown values may or may not propagate to the containing expressions, depending on the current value of the other arguments. This paper presents a compiler and runtime for the Allen language, and shows how they implement its state combining operators, based on reducing complex expressions to a core subset of operators, which are implemented natively. We define several assisted living applications both in Allen and in a general scripting language. We show that the former are much more concise in Allen, achieve more effective code reuse, and ease the checking of some domain properties.
Weixin Zhang, Bruno C. D. S. Oliveira
ACM SIGPLAN Notices, Volume 53, pp 134-146; https://doi.org/10.1145/3393934.3278124

Abstract:
Pattern matching is a pervasive and useful feature in functional programming. There have been many attempts to bring similar notions to Object-Oriented Programming (OOP) in the past. However, a key challenge in OOP is how pattern matching can coexist with the open nature of OOP data structures, while at the same time guaranteeing other desirable properties for pattern matching. This paper discusses several desirable properties for pattern matching in an OOP context and shows how existing approaches are lacking some of these properties. We argue that the traditional semantics of pattern matching, which is based on the order of patterns and adopted by many approaches, is in conflict with the openness of data structures. Therefore we suggest that a more restricted, top-level pattern matching model, where the order of patterns is irrelevant, is worthwhile considering in an OOP context. To compensate for the absence of ordered patterns we propose a complementary mechanism for case analysis with defaults, which can be used when nested and/or multiple case analysis is needed. To illustrate our points we develop Castor: a meta-programming library inScala that adopts both ideas. Castor generates code that uses type-safe extensible visitors, and largely removes boilerplate code typically associated with visitors. We illustrate the applicability of our approach with a case study modularizing the interpreters in the famous book ”Types and Programming Languages”.
Yoav Seginer, Theo Vosse, Gil Harari, Uri Kolodny
ACM SIGPLAN Notices, Volume 53, pp 64-75; https://doi.org/10.1145/3393673.3276949

Abstract:
We present a declarative, object-oriented language in which queries play a central role. Queries are used not only to access data, but also to refer to the application’s object members and as a means of program control. The language is fully declarative, with queries and other pure functions defining the relations between the attributes of different objects. A rule-base-like write operation allows state to be updated. Control is achieved by queries selecting the class variants (mixin classes) which are active in each object. The dynamic activation and deactivation of declarative mixin classes allows decomposition of functionality into small reusable classes. The programming style in the language is functional and reactive, with function applications defining object members. Queries are one type of function, which also serves as the glue which puts these functions together, providing them with their input. Since queries describe declaratively what they return, they leave it to the system to implement the how of getting it. Combining this with an organization around objects makes the language highly suitable for complex interactive applications driven by large amounts of data from multiple sources. Our implementation of the language includes a strong display component. It can be seen as a conceptual extension of HTML and CSS in a way which replaces the need for the JavaScript imperative component in web applications. The work described here is not restricted, however, to front-end development and can be applied elsewhere as well.
Preston Tunnell Wilson, Ben Greenman, Justin Pombrio, Shriram Krishnamurthi
ACM SIGPLAN Notices, Volume 53, pp 1-12; https://doi.org/10.1145/3393673.3276947

Abstract:
There are several different gradual typing semantics, reflecting different trade-offs between performance and type soundness guarantees. Notably absent, however, are any data on which of these semantics developers actually prefer. We begin to rectify this shortcoming by surveying professional developers, computer science students, and Mechanical Turk workers on their preferences between three gradual typing semantics. These semantics reflect important points in the design space, corresponding to the behaviors of Typed Racket, TypeScript, and Reticulated Python. Our most important finding is that our respondents prefer a runtime semantics that fully enforces statically declared types.
Guido Chari, Javier Pimás, Jan Vitek, Olivier Flückiger
ACM SIGPLAN Notices, Volume 53, pp 76-87; https://doi.org/10.1145/3393673.3276948

Abstract:
Operating systems are traditionally implemented in low- level, performance-oriented programming languages. These languages typically rely on minimal runtime support and provide unfettered access to the underlying hardware. Tra- dition has benefits: developers control the resources that the operating system manages and few performance bottle- necks cannot be overcome with clever feats of programming. On the other hand, this makes operating systems harder to understand and maintain. Furthermore, those languages have few built-in barriers against bugs. This paper is an ex- periment in side-stepping operating systems, and pushing functionality into the runtime of high-level programming languages. The question we try to answer is how much sup- port is needed to run an application written in, say, Smalltalk or Python on bare metal, that is, with no underlying oper- ating system. We present a framework named NopSys that allows this, and we validate it with the implementation of CogNos a Smalltalk virtual machine running on bare x86 hardware. Experimental results suggest that this approach is promising.
Manuel Serrano
ACM SIGPLAN Notices, Volume 53, pp 50-63; https://doi.org/10.1145/3393673.3276950

Abstract:
Static compilation, a.k.a., ahead-of-time (AOT) compilation, is an alternative approach to JIT compilation that can combine good speed and lightweight memory footprint, and that can accommodate read-only memory constraints that are imposed by some devices and some operating systems. Unfortunately the highly dynamic nature of JavaScript makes it hard to compile statically and all existing AOT compilers have either gave up on good performance or full language support. We have designed and implemented an AOT compiler that aims at satisfying both. It supports full unrestricted ECMAScript 5.1 plus many ECMAScript 2017 features and the majority of benchmarks are within 50
David Herrera, Hanfeng Chen, Erick Lavoie, Laurie Hendren
ACM SIGPLAN Notices, Volume 53, pp 88-100; https://doi.org/10.1145/3393673.3276968

Abstract:
Recent advances in execution environments for JavaScript and WebAssembly that run on a broad range of devices, from workstations and mobile phones to IoT devices, provide new opportunities for portable and web-based numerical computing. Indeed, numerous numerical libraries and applications are emerging on the web, including Tensorflow.js, JSMapReduce, and the NLG Protein Viewer. This paper evaluates the current performance of numerical computing on the web, including both JavaScript and WebAssembly, over a wide range of devices from workstations to IoT devices. We developed a new benchmarking approach, which allowed us to perform centralized benchmarking, including benchmarking on mobile and IoT devices. Using this approach we performed four performance studies using the Ostrich benchmark suite, a collection of numerical programs representing the numerical dwarf categories identified by Colella. We studied the performance evolution of JavaScript, the relative performance of WebAssembly, the performance of server-side Node.js, and a comprehensive performance showdown for a wide range of devices.
Mark Marron
ACM SIGPLAN Notices, Volume 53, pp 25-36; https://doi.org/10.1145/3393673.3276952

Abstract:
Logging is a fundamental part of the software development and deployment lifecycle but logging support is often provided as an afterthought via limited library APIs or third-party modules. Given the critical nature of logging in modern cloud, mobile, and IoT development workflows, the unique needs of the APIs involved, and the opportunities for optimization using semantic knowledge, we argue logging should be included as a central part of the language and runtime designs. This paper presents a rethinking of the logger for modern cloud-native workflows. Based on a set of design principles for modern logging we build a logging system, that supports near zero-cost for disabled log statements, low cost lazy-copying for enabled log statements, selective persistence of logging output, unified control of logging output across different libraries, and DevOps integration for use with modern cloud-based deployments. To evaluate these concepts we implemented the Log++ logger for Node.js hosted JavaScript applications.
Hanfeng Chen, Joseph Vinish D'silva, Hongji Chen, Bettina Kemme, Laurie Hendren
ACM SIGPLAN Notices, Volume 53, pp 37-49; https://doi.org/10.1145/3393673.3276951

Abstract:
Relational database management systems (RDBMS) are operationally similar to a dynamic language processor. They take SQL queries as input, dynamically generate an optimized execution plan, and then execute it. In recent decades, the emergence of in-memory databases with columnar storage, which use array-like storage structures, has shifted the focus on optimizations from the traditional I/O bottleneck to CPU and memory. However, database research so far has primarily focused on CPU cache optimizations. The similarity in the computational characteristics of such database workloads and array programming language optimizations are largely unexplored. We believe that these database implementations can benefit from merging database optimizations with dynamic array-based programming language approaches. Therefore, in this paper, we propose a novel approach to optimize database query execution using a new array-based intermediate representation, HorseIR, that resides between database queries and compiled code. Furthermore, we provide a translator to generate HorseIR from database execution plans and a compiler that optimizes HorseIR and generates efficient code. We compare HorseIR with the MonetDB RDBMS, by testing standard SQL queries, and show how our approach and compiler optimizations improve the runtime of complex queries.
Martin Bodin, Tomás Diaz, Éric Tanter
ACM SIGPLAN Notices, Volume 53, pp 13-24; https://doi.org/10.1145/3393673.3276946

Abstract:
The R programming language is very popular for developing statistical software and data analysis, thanks to rich libraries, concise and expressive syntax, and support for interactive programming. Yet, the semantics of R is fairly complex, contains many subtle corner cases, and is not formally specified. This makes it difficult to reason about R programs. In this work, we develop a big-step operational semantics for R in the form of an interpreter written in the Coq proof assistant. We ensure the trustworthiness of the formalization by introducing a monadic encoding that allows the Coq interpreter, CoqR, to be in direct visual correspondence with the reference R interpreter, GNU R. Additionally, we provide a testing framework that supports systematic comparison of CoqR and GNU R. In its current state, CoqR covers the nucleus of the R language as well as numerous additional features, making it pass a significant number of realistic test cases from the GNU R and FastR projects. To exercise the formal specification, we prove in Coq the preservation of memory invariants in selected parts of the interpreter. This work is an important first step towards a robust environment for formal verification of R programs.
Steven R. Brandt, Hari Krishnan, ,
ACM SIGPLAN Notices, Volume 53, pp 29-44; https://doi.org/10.1145/3299706.3210572

Abstract:
We propose a scalable, cycle-collecting, decentralized, reference counting garbage collector with partial tracing. The algorithm is based on the Brownbridge system but uses four different types of references to label edges. Memory usage is O (log n) bits per node, where n is the number of nodes in the graph. The algorithm assumes an asynchronous network model with a reliable reordering channel. It collects garbage in O (E a ) time, where E a is the number of edges in the in- duced subgraph. The algorithm uses termination detection to manage the distributed computation, a unique identifier to break the symmetry among multiple collectors, and a transaction-based approach when multiple collectors conflict. Unlike existing algorithms, ours is not centralized, does not require barriers, does not require migration of nodes, does not require back-pointers on every edge, and is stable against concurrent mutation.
Richard A. Eisenberg, ,
ACM SIGPLAN Notices, Volume 53, pp 94-105; https://doi.org/10.1145/3299711.3242753

Abstract:
For many years, GHC has implemented an extension to Haskell that allows type variables to be bound in type signatures and patterns, and to scope over terms. This extension was never properly specified. We rectify that oversight here. With the formal specification in hand, the otherwise-labyrinthine path toward a design for binding type variables in patterns becomes blindingly clear. We thus extend ScopedTypeVariables to bind type variables explicitly, obviating the Proxy workaround to the dustbin of history.
Joachim Breitner
ACM SIGPLAN Notices, Volume 53, pp 14-25; https://doi.org/10.1145/3299711.3242748

Abstract:
Occasionally, developers need to ensure that the compiler treats their code in a specific way that is only visible by inspecting intermediate or final compilation artifacts. This is particularly common with carefully crafted compositional libraries, where certain usage patterns are expected to trigger an intricate sequence of compiler optimizations – stream fusion is a well-known example. The developer of such a library has to manually inspect build artifacts and check for the expected properties. Because this is too tedious to do often, it will likely go unnoticed if the property is broken by a change to the library code, its dependencies or the compiler. The lack of automation has led to released versions of such libraries breaking their documented promises. This indicates that there is an unrecognized need for a new testing paradigm, inspection testing , where the programmer declaratively describes non-functional properties of an compilation artifact and the compiler checks these properties. We define inspection testing abstractly, implement it in the context of the Haskell Compiler GHC and show that it increases the quality of such libraries.
Alejandro Serrano, Victor Cacciari Miraldo
ACM SIGPLAN Notices, Volume 53, pp 41-54; https://doi.org/10.1145/3299711.3242745

Abstract:
Datatype-generic programming is a widely used technique to define functions that work regularly over a class of datatypes. Examples include deriving serialization of data, equality or even functoriality. The state-of-the-art of generic programming still lacks handling GADTs, multiple type variables, and some other features. This paper exploits modern GHC extensions, including TypeInType, to handle arbitrary number of type variables, constraints, and existentials. We also provide an Agda model of our construction that does not require Russel’s paradox, proving the construction is consistent.
Agustín Mista, Alejandro Russo, John Hughes
ACM SIGPLAN Notices, Volume 53, pp 1-13; https://doi.org/10.1145/3299711.3242747

Abstract:
In QuickCheck (or, more generally, random testing), it is challenging to control random data generators' distributions---specially when it comes to user-defined algebraic data types (ADT). In this paper, we adapt results from an area of mathematics known as branching processes, and show how they help to analytically predict (at compile-time) the expected number of generated constructors, even in the presence of mutually recursive or composite ADTs. Using our probabilistic formulas, we design heuristics capable of automatically adjusting probabilities in order to synthesize generators which distributions are aligned with users' demands. We provide a Haskell implementation of our mechanism in a tool called DRaGeN and perform case studies with real-world applications. When generating random values, our synthesized QuickCheck generators show improvements in code coverage when compared with those automatically derived by state-of-the-art tools.
Daniel Byrne, Nilufer Onder, Zhenlin Wang
ACM SIGPLAN Notices, Volume 53, pp 84-95; https://doi.org/10.1145/3299706.3210571

Abstract:
Web applications employ key-value stores to cache the data that is most commonly accessed. The cache improves an web application's performance by serving its requests from memory, avoiding fetching them from the backend database. Since the memory space is limited, maximizing the memory utilization is a key to delivering the best performance possible. This has lead to the use of multi-tenant systems, allowing applications to share cache space. In addition, application data access patterns change over time, so the system should be adaptive in its memory allocation. In this work, we address both multi-tenancy (where a single cache is used for multiple applications) and dynamic workloads (changing access patterns) using a model that relates the cache size to the application miss ratio, known as a miss ratio curve. Intuitively, the larger the cache, the less likely the system will need to fetch the data from the database. Our efficient, online construction of the miss ratio curve allows us to determine a near optimal memory allocation given the available system memory, while adapting to changing data access patterns. We show that our model outperforms an existing state-of-the-art sharing model, Memshare, in terms of overall cache hit ratio and does so at a lower time cost. We show that for a typical system, overall hit ratio is consistently 1 percentage point greater and 99.9th percentile latency is reduced by as much as 2.9% under standard web application workloads containing millions of requests.
Stuart Byma, James R. Larus
ACM SIGPLAN Notices, Volume 53, pp 1-13; https://doi.org/10.1145/3299706.3210564

Abstract:
Modern software systems heavily use the memory heap. As systems grow more complex and compute with increasing amounts of data, it can be difficult for developers to understand how their programs actually use the bytes that they allocate on the heap and whether improvements are possible. To answer this question of heap usage efficiency, we have built a new, detailed heap profiler called Memoro. Memoro uses a combination of static instrumentation, subroutine interception, and runtime data collection to build a clear picture of exactly when and where a program performs heap allocation, and crucially how it actually uses that memory. Memoro also introduces a new visualization application that can distill collected data into scores and visual cues that allow developers to quickly pinpoint and eliminate inefficient heap usage in their software. Our evaluation and experience with several applications demonstrates that Memoro can reduce heap usage and produce runtime improvements of 10%.
Kazutaka Matsuda, Meng Wang
ACM SIGPLAN Notices, Volume 53, pp 158-171; https://doi.org/10.1145/3299711.3242758

Abstract:
This paper describes a new embedding technique of invertible programming languages, through the case of the FliPpr language. Embedded languages have the advantage of inheriting host languages' features and supports; and one of the influential methods of embedding is the tagless-final style, which enables a high level of programmability and extensibility. However, it is not straightforward to apply the method to the family of invertible/reversible/bidirectional languages, due to the different ways functions in such domains are represented. We consider FliPpr, an invertible pretty-printing system, as a representative of such languages, and show that Atkey et al.'s unembedding technique can be used to address the problem. Together with a reformulation of FliPpr, our embedding achieves a high level of interoperability with the host language Haskell, which is not found in any other invertible languages. We implement the idea and demonstrate the benefits of the approach with examples.
Divesh Otwani, Richard A. Eisenberg
ACM SIGPLAN Notices, Volume 53, pp 106-118; https://doi.org/10.1145/3299711.3242754

Abstract:
Many fancy types (e.g., generalized algebraic data types, type families) require a type checker plugin. These fancy types have a type index (e.g., type level natural numbers) with an equality relation that is difficult or impossible to represent using GHC's built-in type equality. The most practical way to represent these equality relations is through a plugin that asserts equality constraints. However, such plugins are difficult to write and reason about. In this paper, we (1) present a formal theory of reasoning about the correctness of type checker plugins for type indices, and, (2) apply this theory in creating Thoralf, a generic and extensible plugin for type indices that translates GHC constraint problems to queries to an external SMT solver. By "generic and extensible", we mean the restrictions on extending Thoralf are slight, and, if some type index could be encoded as an SMT sort, then a programmer could extend Thoralf by providing this encoding function.
Dong Han, Tao He
ACM SIGPLAN Notices, Volume 53, pp 172-178; https://doi.org/10.1145/3299711.3242759

Abstract:
We present a high performance multicore I/O manager based on libuv for Glasgow Haskell Compiler (GHC). The new I/O manager is packaged as an ordinary Haskell package rather than baked into GHC's runtime system(GHC RTS), yet takes advantage of GHC RTS's comprehensive concurrent support, such as lightweight threads and safe/unsafe FFI options. The new I/O manager's performance is comparable with existing implementation, with greater stability under high load. It also can be easily extended to support all of libuv's callback-based APIs, allowing us to write a complete high performance I/O toolkit without spending time on dealing with OS differences or low-level I/O system calls.
Manuel Bärenz, Ivan Perez
ACM SIGPLAN Notices, Volume 53, pp 145-157; https://doi.org/10.1145/3299711.3242757

Abstract:
Processing data at different rates is generally a hard problem in reactive programming. Buffering problems, lags, and concurrency issues often occur. Many of these problems are clock errors , where data at different rates is combined incorrectly. Techniques to avoid clock errors, such as type-level clocks and deterministic scheduling, exist in the field of synchronous programming, but are not implemented in general-purpose languages like Haskell. Rhine is a clock-safe library for synchronous and asynchronous Functional Reactive Programming (FRP). It separates the aspects of clocking, scheduling and resampling from each other, and ensures clock-safety at the type level. Concurrent communication is encapsulated safely. Diverse reactive subsystems can be combined in a coherent, declarative data-flow framework, while correct interoperability of data at different rates is guaranteed by type-level clocks. This provides a general-purpose framework that simplifies multi-rate FRP systems and can be used for game development, media applications, GUIs and embedded systems, through a flexible API with many reusable components.
Michihiro Horie, Hiroshi Horii, Kazunori Ogata,
ACM SIGPLAN Notices, Volume 53, pp 109-119; https://doi.org/10.1145/3299706.3210570

Abstract:
Work-stealing is promising for scheduling and balancing parallel workloads. It has a wide range of applicability on middleware, libraries, and runtime systems of programming languages. OpenJDK uses work-stealing for copying garbage collection (GC) to balance copying tasks among GC threads. Each thread has its own queue to store tasks. When a thread has no task in its queue, it acts as a thief and attempts to steal a task from another thread's queue. However, this work-stealing algorithm requires expensive memory fences for pushing, popping, and stealing tasks, especially on weak memory models such as POWER and ARM. To address this problem, we propose a work-stealing algorithm that uses double queues. Each GC thread has a public queue that is accessible from other GC threads and a private queue that is only accessible by itself. Pushing and popping tasks in the private queue are free from expensive memory fences. The most significant point in our algorithm is providing a mechanism to maintain the load balance on the basis of the use of double queues. We developed a prototype implementation for parallel GC in OpenJDK8 for ppc64le. We evaluated our algorithm by using SPECjbb2015, SPECjvm2008, TPC-DS, and Apache DayTrader.
Gurneet Kaur, Keval Vora, ,
ACM SIGPLAN Notices, Volume 53, pp 71-83; https://doi.org/10.1145/3299706.3210568

Abstract:
While single machine MapReduce systems can squeeze out maximum performance from available multi-cores, they are often limited by the size of main memory and can thus only process small datasets. Our experience shows that the state-of-the-art single-machine in-memory MapReduce system Metis frequently experiences out-of-memory crashes. Even though today's computers are equipped with efficient secondary storage devices, the frameworks do not utilize these devices mainly because disk access latencies are much higher than those for main memory. Therefore, the single-machine setup of the Hadoop system performs much slower when it is presented with the datasets which are larger than the main memory. Moreover, such frameworks also require tuning a lot of parameters which puts an added burden on the programmer. In this paper we present OMR, an Out-of-core MapReduce system that not only successfully handles datasets that are far larger than the size of main memory, it also guarantees linear scaling with the growing data sizes. OMR actively minimizes the amount of data to be read/written to/from disk via on-the-fly aggregation and it uses block sequential disk read/write operations whenever disk accesses become necessary to avoid running out of memory. We theoretically prove OMR's linear scalability and empirically demonstrate it by processing datasets that are up to 5x larger than main memory. Our experiments show that in comparison to the standalone single-machine setup of the Hadoop system, OMR delivers far higher performance. Also in contrast to Metis, OMR avoids out-of-memory crashes for large datasets as well as delivers higher performance when datasets are small enough to fit in main memory.
Charles Tripp, David Hyde, Benjamin Grossman-Ponemon
ACM SIGPLAN Notices, Volume 53, pp 14-28; https://doi.org/10.1145/3299706.3210569

Abstract:
We present FRC, a high-performance concurrent parallel reference counter for unmanaged languages. It is well known that high-performance garbage collectors help developers write memory-safe, highly concurrent systems and data structures. While C++, C, and other unmanaged languages are used in high-performance applications, adding concurrent memory management to these languages has proven to be difficult. Unmanaged languages like C++ use pointers instead of references, and have uncooperative mutators which do not pause easily at a safe point. Thus, scanning mutator stack root references is challenging. FRC only defers decrements and does not require mutator threads to pause during collection. By deferring only decrements, FRC avoids much of the synchronization overhead of a fully-deferred implementation. Root references are scanned without interrupting the mutator by publishing these references to a thread-local array. FRC's performance can exceed that of the C++ standard library's shared pointer by orders of magnitude. FRC's thread-safety guarantees and low synchronization overhead enable significant throughput gains for concurrently-readable shared data structures. We describe the components of FRC, including our static tree router data structure: a novel barrier which improves the scalability of parallel collection workers. FRC's performance is evaluated on several concurrent data structures. We release FRC and our tests as open-source code and expect FRC will be useful for many concurrent C++ software systems.
Rodrigo C. M. Santos, Guilherme F. Lima, Francisco Sant'anna, Roberto Ierusalimschy, Edward H. Haeusler
ACM SIGPLAN Notices, Volume 53, pp 1-18; https://doi.org/10.1145/3299710.3211334

Abstract:
Céu is a synchronous programming language for embedded soft real-time systems. It focuses on control-flow safety features, such as safe shared-memory concurrency and safe abortion of lines of execution, while enforcing memory bounded, deterministic, and terminating reactions to the environment. In this work, we present a small-step structural operational semantics for Céu and a proof that reactions have the properties enumerated above: that for a given arbitrary timeline of input events, multiple executions of the same program always react in bounded time and arrive at the same final finite memory state.
ACM SIGPLAN Notices, Volume 53, pp 81-93; https://doi.org/10.1145/3299711.3242752

Abstract:
Type classes are one of Haskell's most popular features and extend its type system with ad-hoc polymorphism. Since their conception, there were useful features that could not be offered because of the desire to offer two correctness properties: coherence and global uniqueness of instances. Coherence essentially guarantees that program semantics are independent from type-checker internals. Global uniqueness of instances is relied upon by libraries for enforcing, for example, that a single order relation is used for all manipulations of an ordered binary tree. The features that could not be offered include explicit dictionary application and local instances, which would be highly useful in practice. In this paper, we propose a new design for offering explicit dictionary application, without compromising coherence and global uniqueness. We introduce a novel criterion based on GHC's type argument roles to decide when a dictionary application is safe with respect to global uniqueness of instances. We preserve coherence by detecting potential sources of incoherence, and prove it formally. Moreover, our solution makes it possible to use local dictionaries. In addition to developing our ideas formally, we have implemented a working prototype in GHC.
Pavan Mehrotra, Sabar Dasgupta, Samantha Robertson, Paul Nuyujukian
ACM SIGPLAN Notices, Volume 53, pp 109-112; https://doi.org/10.1145/3299710.3211344

Abstract:
Systems neuroscience studies involving in-vivo models often require realtime data processing. In these studies, many events must be monitored and processed quickly, including behavior of the subject (e.g., movement of a limb) or features of neural data (e.g., a neuron transmitting an action potential). Unfortunately, most realtime platforms are proprietary, require specific architectures, or are limited to low-level programming languages. Here we present a hardware-independent, open-source realtime computation platform that supports high-level programming. The resulting platform, LiCoRICE, can process on order 10e10 bits/sec of network data at 1 ms ticks with 18.2 µs jitter. It connects to various inputs and outputs (e.g., DIO, Ethernet, database logging, and analog line in/out) and minimizes reliance on custom device drivers by leveraging peripheral support via the Linux kernel. Its modular architecture supports model-based design for rapid prototyping with C and Python/Cython and can perform numerical operations via BLAS/LAPACK-optimized NumPy that is statically compiled via Numba’s pycc. LiCoRICE is not only suitable for systems neuroscience research, but also for applications requiring closed-loop realtime data processing from robotics and control systems to interactive applications and quantitative financial trading.
Michael Stokes, Ryan Baird, Zhaoxiang Jin, David Whalley, Soner Onder
ACM SIGPLAN Notices, Volume 53, pp 65-75; https://doi.org/10.1145/3299710.3211340

Abstract:
Level-one data cache (L1 DC) accesses impact energy usage as they frequently occur and use significantly more energy than register file accesses. A memory access instruction consists of an address generation operation calculating the location where the data item resides in memory and the data access operation that loads/stores a value from/to that location. We propose to decouple these two operations into separate machine instructions to reduce energy usage. By associating the data translation lookaside buffer (DTLB) access and level-one data cache (L1 DC) tag check with an address generation instruction, only a single data array in a set-associative L1 DC needs to be accessed during a load instruction when the result of the tag check is known at that point. In addition, many DTLB accesses and L1 DC tag checks are avoided by memoizing the DTLB way and L1 DC way with the register that holds the memory address to be dereferenced. Finally, we are able to often coalesce an ALU operation with a load or store data access using our technique to reduce the number of instructions executed.
Lei Han, Zhaoyan Shen, , Tao Li
ACM SIGPLAN Notices, Volume 53, pp 44-54; https://doi.org/10.1145/3299710.3211338

Abstract:
Flash-based SSD RAID arrays are increasingly being deployed in data centers. Compared with HDD arrays, SSD arrays drastically enhance storage density and I/O performance, and reduce power and rack space. Nevertheless, SSDs suffer aging issues. Though prior studies have been conducted to address this disadvantage, effective techniques of RAID/SSD controllers are urgently needed to extend the lifetime of SSD arrays. In this paper, we for the first time apply approximate storage via the interplay of RAID and SSD controllers to optimize the lifespan of SSD arrays. Our basic idea is to reuse faulty blocks (those contain pages with uncorrectable errors) to store approximate data (which can tolerate more errors). By relaxing the integrity of flash blocks, we observed that the endurance of NAND flash memory can be significantly boosted, thereby providing huge potentials to significantly extend the lifetime of SSDs. Based on this observation, we propose the use of an efficient space management scheme for data allocation and FTL strategies by coordinating the interplay of RAID and SSD controllers to optimize the lifetime of SSD arrays. We implemented a prototype, called FreeRAID, based on an SSD array simulator. Our experiments show that we can significantly increase the lifetime by up to 2.17× compared with conventional SSD-based RAID arrays.
Andre Xian Ming Chang, Aliasger Zaidy, Lukasz Burzawa, Eugenio Culurciello
ACM SIGPLAN Notices, Volume 53, pp 89-93; https://doi.org/10.1145/3299710.3211333

Abstract:
Deep Neural Networks (DNNs) are the algorithm of choice for image processing applications. DNNs present highly parallel workloads that lead to the emergence of custom hardware accelerators. Deep Learning (DL) models specialized in different tasks require a programmable custom hardware and a compiler/mapper to efficiently translate different DNNs into an efficient dataflow in the accelerator. The goal of this paper is to present a compiler for running DNNs on Snowflake, which is a programmable hardware accelerator that targets DNNs. The compiler correctly generates instructions for various DL models: AlexNet, VGG, ResNet and LightCNN9. Snowflake, with a varying number of processing units, was implemented on FPGA to measure the compiler and Snowflake performance properties upon scaling up. The system achieves 70 frames/s and 4.5 GB/s of off-chip memory bandwidth for AlexNet without linear layers on Xilinx’s Zynq-SoC XC7Z045 FPGA.
Niki Vazou, Joachim Breitner, Rose Kunkel, David Van Horn, Graham Hutton
ACM SIGPLAN Notices, Volume 53, pp 132-144; https://doi.org/10.1145/3299711.3242756

Abstract:
Equational reasoning is one of the key features of pure functional languages such as Haskell. To date, however, such reasoning always took place externally to Haskell, either manually on paper, or mechanised in a theorem prover. This article shows how equational reasoning can be performed directly and seamlessly within Haskell itself, and be checked using Liquid Haskell. In particular, language learners --- to whom external theorem provers are out of reach --- can benefit from having their proofs mechanically checked. Concretely, we show how the equational proofs and derivations from Graham's textbook can be recast as proofs in Haskell (spoiler: they look essentially the same).
, Paulo Ferreira, Ruslan Synytsky, Tetiana Fydorenchyk, Jia Rao, , Song Wu
ACM SIGPLAN Notices, Volume 53, pp 59-70; https://doi.org/10.1145/3299706.3210567

Abstract:
The cloud is an increasingly popular platform to deploy applications as it lets cloud users to provide resources to their applications as needed. Furthermore, cloud providers are now starting to offer a "pay-as-you-use" model in which users are only charged for the resources that are really used instead of paying for a statically sized instance. This new model allows cloud users to save money, and cloud providers to better utilize their hardware. However, applications running on top of runtime environments such as the Java Virtual Machine (JVM) cannot benefit from this new model because they cannot dynamically adapt the amount of used resources at runtime. In particular, if an application needs more memory than what was initially predicted at launch time, the JVM will not allow the application to grow its memory beyond the maximum value defined at launch time. In addition, the JVM will hold memory that is no longer being used by the application. This lack of dynamic vertical scalability completely prevents the benefits of the "pay-as-you-use" model, and forces users to over-provision resources, and to lose money on unused resources. We propose a new JVM heap sizing strategy that allows the JVM to dynamically scale its memory utilization according to the application's needs. First, we provide a configurable limit on how much the application can grow its memory. This limit is dynamic and can be changed at runtime, as opposed to the current static limit that can only be set at launch time. Second, we adapt current Garbage Collection policies that control how much the heap can grow and shrink to better fit what is currently being used by the application. The proposed solution is implemented in the OpenJDK 9 HotSpot JVM, the new release of OpenJDK. Changes were also introduced inside the Parallel Scavenge collector and the Garbage First collector (the new by-default collector in HotSpot). Evaluation experiments using real workloads and data show that, with negligible throughput and memory overhead, dynamic vertical memory scalability can be achieved. This allows users to save significant amounts of money by not paying for unused resources, and cloud providers to better utilize their physical machines.
Matthías Páll Gissurarson
ACM SIGPLAN Notices, Volume 53, pp 179-185; https://doi.org/10.1145/3299711.3242760

Abstract:
Type systems allow programmers to communicate a partial specification of their program to the compiler using types, which can then be used to check that the implementation matches the specification. But can the types be used to aid programmers during development? In this experience report I describe the design and implementation of my lightweight and practical extension to the typed-holes of GHC that improves user experience by adding a list of valid hole fits and refinement hole fits to the error message of typed-holes. By leveraging the type checker, these fits are selected from identifiers in scope such that if the hole is substituted with a valid hole fit, the resulting expression is guaranteed to type check.
Gaurav Chadha
ACM SIGPLAN Notices, Volume 53, pp 104-108; https://doi.org/10.1145/3299710.3211343

Abstract:
JavaScript has seen meteoric growth in popularity as it has in- creasingly become the language of choice for developers, both for front-end web development and server code development through various JavaScript frameworks and Node.js. Part of the reason for its wide use is that it is a prototype based language with dynamic types, making it easy to learn and program in. This flexibility and ease of programming comes at the cost of performance. There are two sources of significant slowdown. First, since the number and type of properties of prototypes is dynamic, accessing a property involves a slow dictionary lookup, as opposed to it being present at a fixed offset from the base address. Second, the dynamism in type of values necessitates wrapping and unwrapping of values into objects with a variety of checks including for type of the value. To mitigate these performance problems, this paper proposes JSCore, a core specialized for JavaScript execution, that vastly reduces the performance degradation due to the above two causes. It uses a hardware lookup table to accelerate property access, and extends the data path to store data types with the data, nearly eliminating the second source of slowdown. Combining the two, JSCore accelerates real world JavaScript applications by 23%.
Guido Martínez, Mauro Jaskelioff, Guido De Luca
ACM SIGPLAN Notices, Volume 53, pp 68-80; https://doi.org/10.1145/3299711.3242751

Abstract:
Mathematical concepts such as monads, functors, monoids, and semigroups are expressed in Haskell as typeclasses. Therefore, in order to exploit relations such as “every monad is a functor”, and “every monoid is a semigroup”, we need to be able to also express relations between typeclasses. Currently, the only way to do so is using superclasses . However, superclasses can be problematic due to their closed nature. Adding a superclass implies modifying the subclass’ definition, which is either impossible if one does not own such code, or painful as it requires cascading changes and the introduction of boilerplate throughout the codebase. In this article, we introduce class morphisms , a way to relate classes in an open fashion, without changing class definitions. We show how class morphisms improve the expressivity, conciseness, and maintainability of code. Further, we show how to implement them while maintaining canonicity and coherence, two key properties of the Haskell type system. Extending a typechecker with class morphisms amounts to adding an elaboration phase and is an unintrusive change. We back this claim with a prototype extension of GHC.
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