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Squeak by Example
Abstract and Figures
Squeak by Example, intended for both students and developers, will guide you gently through the Squeak language and environment by means of a series of examples and exercises. This book is made available under the Creative Commons Attribution-ShareAlike 3.0 license.
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... To evolve a system to a desired state, a stream of deltas in a specific order must be applied to it. Figure 1 shows how a stream of changes {∆ 1 , ∆ 2 } is applied to version 1 of a reflective system to obtain, in order, version 2 and version 3. Pharo [2] and Squeak [1] are object-oriented systems evolving traditionally by self-modification. These systems store their state and all their objects in an image. ...
Bootstrapping is a technique commonly known by its usage in language definition by the introduction of a compiler written in the same language it compiles. This process is important to understand and modify the definition of a given language using the same language, taking benefit of the abstractions and expression power it provides. A bootstrap, then, supports the evolution of a language. However, the infrastructure of reflective systems like Smalltalk includes, in addition to a compiler, an environment with several self-references. A reflective system bootstrap should consider all its infrastructural components. In this paper, we propose a definition of bootstrap for object-oriented reflective systems, we describe the architecture and components it should contain and we analyze the challenges it has to overcome. Finally, we present a reference bootstrap process for a reflective system and Hazelnut, its implementation for bootstrapping the Pharo Smalltalk-inspired system.
... CLS and Test performance. To investigate the relationship between the CLS-score and per- formance using a simple interactive computer system, a simulated ticket vending machine (TVM) of the BVG (Berlin Public Transportation) was built in Squeak/Smalltalk (see Black et al (2007) for an introduction) and presented on a 19" touch screen monitor. The symbols and terms used in the GUI of the simulation were not used as items in the CLS. Figure 2 shows a screenshot of the simulation. ...
An important prerequisite for successful usage of computer systems and other interactive technology is a basic understanding of the symbols and interaction patterns used in them. This aspect of the broader construct "computer literacy" is used as indicator in the computer literacy scale, which proved to be an economical, reliable and valid instrument for the assessment of computer literacy in older adults.
OpenSmalltalk‐VM is a virtual machine (VM) for languages in the Smalltalk family (eg, Squeak and Pharo), which is itself written in a subset of Smalltalk that can easily be translated to C. VM development is done in Smalltalk, an activity we call “simulation.” The production VM is then derived by translating the core VM code to C. As a result, two execution models coexist: simulation, where the Smalltalk code is executed on top of a Smalltalk VM, and production, where the same code is compiled to an executable through a C compiler. The whole VM execution can be simulated: the heap is represented as a huge byte array, the VM code is executed as Smalltalk, and the native code generated by the just‐in‐time (JIT) compiler is executed by a processor simulator. All the Smalltalk development tools, such as the debugger, are then available while simulating. In addition, in simulation, it is also possible to use debugging features such as single stepping in the machine code generated by the JIT compiler. The Smalltalk development tools combined with the simulation debugging features provide developers with a productive environment in which to extend and debug the VM. In this article, we detail the VM simulation infrastructure and report our experiences developing and debugging VM features within it such as the garbage collector and the JIT compiler.
Virtual machines, besides the interpreter and just-in-time compiler optimization facilities, also include a set of primitive operations that the client language can use. Some of these are essential and cannot be performed in any other way. Others are optional: they can be expressed in the client language but are often implemented in the virtual machine to improve performance when the just-in-time compiler is unable to do so (start-up performance, speculative optimizations not implemented or not mature enough, etc.).
In a hybrid runtime, where code is executed by an interpreter and a just-in-time compiler, the implementor can choose to implement optional primitives in the client language, in the virtual machine implementation language (typically C or C++), or on top of the just-in-time compiler backend. This raises the question of the maintenance and performance trade-offs of the different alternatives. As a case study, we implemented the String comparison optional primitive in each case. This paper describes the different implementations, discusses the maintenance cost of each of them and evaluates for different string sizes the execution time in Cog, a Smalltalk virtual machine.
Code profiling enables a user to know where in an application or function the execution time is spent. The Pharo ecosystem offers several code profilers. However, most of the publicly available profilers (MessageTally, Spy, GadgetProfiler) largely ignore the activity carried out by the virtual machine, thus incurring inaccuracy in the gathered information and missing important information, such as the Just-in-time compiler activity.
This paper describes the motivations and the latest improvements carried out in VMProfiler, a code execution profiler hooked into the virtual machine, that performs its analysis by monitoring the virtual machine execution. These improvements address some limitations related to assessing the activity of native functions (resulting from a Just-in-time compiler operation): as of now, VMProfiler provides more detailed profiling reports, showing for native code functions in which bytecode range the execution time is spent.
Class extensions are frequently used in programming languages such as Ruby and Smalltalk to add or change methods of a class that is defined in the same application or in a different one. They suffer from modularity issues if globally visible: Other applications using the same classes are then affected by the modifications. This paper presents a hierarchical approach for dynamically scoping class extensions in dynamically-typed, class-based programming languages supporting class nesting. Our mechanism allows programmers to define the scope of class extensions and to reuse class extensions in other programs. Class extensions can be scoped according to a nested class hierarchy or based on whether programmers regard a potentially affected class as a black box or not. Class extensions are organized in layers, where multiple layers targeting the same class can be active at the same time.
Controlling object graphs and giving specific semantics to references (such as read-only, ownership, scoped sharing) have been the focus of a large body of research in the context of static type systems. Controlling references to single objects and to graphs of objects is essential to build more secure systems, but is notoriously hard to achieve in the absence of static type systems. In this article we embrace this challenge by proposing a solution to the following question: What is an underlying mechanism that can support the definition of properties (such as revocable, read-only, lent) at the reference level in the absence of a static type system? We present handles: first-class references that propagate behavioral change dynamically to the object subgraph during program execution. In this article we describe handles and show how handles support the implementation of read-only references and revocable references. Handles have been fully implemented by modifying an existing virtual machine and we report their costs.
As object-oriented languages are extended with novel mod-ularization mechanisms, better underlying models are re-quired to implement these high-level features. This paper describes CELL, a language model that builds on delegation-based chains of object fragments. Composition of groups of cells is used: 1) to represent objects, 2) to realize various forms of method lookup, and 3) to keep track of method ref-erences. A running prototype of CELL is provided and used to realize the basic kernel of a Smalltalk system. The pa-per shows, using several examples, how higher-level features such as traits can be supported by the lower-level model.
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