A translator writing system for microcomputer high-level languages and assemblers

In order to implement high level languages whenever possible, a translator writing system of advanced design was developed. It is intended for routine production use by many programmers working on different projects. As well as a fairly conventional parser generator, it includes a system for the rapid generation of table driven code generators. The parser generator was developed from a prototype version. The translator writing system includes various tools for the management of the source text of a compiler under construction. In addition, it supplies various default source code sections so that its output is always compilable and executable. The system thereby encourages iterative enhancement as a development methodology by ensuring an executable program from the earliest stages of a compiler development project. The translator writing system includes PASCAL/48 compiler, three assemblers, and two compilers for a subset of HAL/S

Design automation of a machine-independent code generator

As both computer languages and architectures continue to proliferate, there is a continuing need for new compilers. Researchers have attempted to ease the work of producing compilers by developing methods to automate compiler writing. While much work has been done (and considerable success achieved) in writing parsers which can handle a variety of source languages (using mainly table-driven analysis methods), less progress has been made in formalizing the code generation end of the compiler. Nevertheless, some of the more recent publications in code generation stress portability or retargetability of the resulting compiler. A number of code generator synthesisers have been developed, some of which produce code that can be compared in quality with that produced by a conventional code generator. However, because of the complexity of generalizing the mapping from source language to target machine, and the need for efficiency of various kinds, code generator synthesisers are large, complicated programs. Consequently, the person who develops a code generator using one of these tools invariably needs to be a code generation specialist himself. Many compilers follow a pattern of having a front end which generates intermediate code, and a back end which converts intermediate code to machine code. The intermediate code is effectively machine independent, or can be designed that way. With these points in mind, we have set out to write a system of programs which -- 1. will allow the generation of such a back end in a reasonably short time, for a general intermediate code, and for a general machine code, and -- 2. can be used by anyone who has a sound knowledge of the target machine's architecture and associated assembler language, but is not necessarily a specialist compiler writer. The system consists of a series of friendly, interactive programs by means of which the user sets up tables defining the architecture and assembly level instructions for the target machine, and the code templates onto which intermediate codes produced by a parser have been mapped. A general notation has been developed to represent machine instructions using the same format as the target assembler. Thus the code generator writer is able to write code sequences to perform the effects of the intermediate codes, using assembly mnemonics familiar to him. The resultant table-driven code generator simply replaces a sequence of intermediate codes by their respective code templates, relocating them in memory and filling in addresses known only at code-generation time. This thesis describes the use and implementation details of this generalized code generation system. As an example, the implementation of a code generator for a CLANG [23] parser on an 8080 processor is described. The discussion also includes guide-lines on how to implement a loader and associated run-time routines for use in executing the object code. The results of a number of bench-marks have shown, as expected, that code produced by a code generator developed in this manner is larger and slower than that from a special purpose optimizing code generator, but is still several times faster than interpreting the intermediate code. The major benefit to be gained from using this system lies in the shorter development time by a less skilled person.KMBT_223Adobe Acrobat 9.53 Paper Capture Plug-i

Relevance, benefits, and problems of software modelling and model driven techniques—A survey in the Italian industry

Context Claimed benefits of software modelling and model driven techniques are improvements in productivity, portability, maintainability and interoperability. However, little effort has been devoted at collecting evidence to evaluate their actual relevance, benefits and usage complications. Goal The main goals of this paper are: (1) assess the diffusion and relevance of software modelling and MD techniques in the Italian industry, (2) understand the expected and achieved benefits, and (3) identify which problems limit/prevent their diffusion. Method We conducted an exploratory personal opinion survey with a sample of 155 Italian software professionals by means of a Web-based questionnaire on-line from February to April 2011. Results Software modelling and MD techniques are very relevant in the Italian industry. The adoption of simple modelling brings common benefits (better design support, documentation improvement, better maintenance, and higher software quality), while MD techniques make it easier to achieve: improved standardization, higher productivity, and platform independence. We identified problems, some hindering adoption (too much effort required and limited usefulness) others preventing it (lack of competencies and supporting tools). Conclusions The relevance represents an important objective motivation for researchers in this area. The relationship between techniques and attainable benefits represents an instrument for practitioners planning the adoption of such techniques. In addition the findings may provide hints for companies and universitie

A Framework for Evaluating Model-Driven Self-adaptive Software Systems

In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition, self-adaptive application, context oriented software developmen

A Syntactic Neural Model for General-Purpose Code Generation

We consider the problem of parsing natural language descriptions into source code written in a general-purpose programming language like Python. Existing data-driven methods treat this problem as a language generation task without considering the underlying syntax of the target programming language. Informed by previous work in semantic parsing, in this paper we propose a novel neural architecture powered by a grammar model to explicitly capture the target syntax as prior knowledge. Experiments find this an effective way to scale up to generation of complex programs from natural language descriptions, achieving state-of-the-art results that well outperform previous code generation and semantic parsing approaches.Comment: To appear in ACL 201

Liveness-Driven Random Program Generation

Randomly generated programs are popular for testing compilers and program analysis tools, with hundreds of bugs in real-world C compilers found by random testing. However, existing random program generators may generate large amounts of dead code (computations whose result is never used). This leaves relatively little code to exercise a target compiler's more complex optimizations. To address this shortcoming, we introduce liveness-driven random program generation. In this approach the random program is constructed bottom-up, guided by a simultaneous structural data-flow analysis to ensure that the generator never generates dead code. The algorithm is implemented as a plugin for the Frama-C framework. We evaluate it in comparison to Csmith, the standard random C program generator. Our tool generates programs that compile to more machine code with a more complex instruction mix.Comment: Pre-proceedings paper presented at the 27th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur, Belgium, 10-12 October 2017 (arXiv:1708.07854