Use Of Code Generation Research Articles

Evaluating Programming Resources: The Impact of Code Generators in Software Development

The increasing demand for rapid software development has led to the growing use of code generators, which significantly accelerate the programming process. This study investigates the impact of code generators on programming resource needs by comparing the time required by programmers of varying skill levels to develop applications using three code generators PHPMaker, PHPRunner, and CakePH versus manual coding with Laravel. Results indicate that code generators allow programmers, regardless of experience, to produce applications more quickly than manual methods. Interestingly, even novice programmers using code generators outperform senior programmers coding manually. This research contributes to the field by providing a clearer understanding of the efficiency gains offered by code generators and suggesting their potential to optimize programming resources in software development. However, the study also highlights the need for future research to evaluate additional factors, such as application complexity and quality, to further refine resource estimation models like SLIM and COCOMO when integrating code generators into the software development process. Keywords: Code Generator, programming resource, software development

Python at Petascale With PyFR or: How I Learned to Stop Worrying and Love the Snake

In this work, we make the case for Python as a first-class language for high-performance computing (HPC) applications. Our rationale is based on three trends: an increasing desire for applications to be user friendly; the shift toward such applications becoming primarily consumers of third-party application programming interfaces; and growing use of code generation for performance sensitive kernels. In each instance, we argue why Python is better placed to ride these trends than traditional languages such as C or Fortran. Further, we will also address two additional concerns regarding the suitability of Python: long start-up times and limited support for multithreading. An as exemplar of Python in HPC, we consider the high-order computational fluid dynamics code PyFR. The novel architecture of PyFR is described including examples showcasing its domain-specific language.

From Model Specification to Simulation of Biologically Constrained Networks of Spiking Neurons

A declarative extensible markup language (SpineML) for describing the dynamics, network and experiments of large-scale spiking neural network simulations is described which builds upon the NineML standard. It utilises a level of abstraction which targets point neuron representation but addresses the limitations of existing tools by allowing arbitrary dynamics to be expressed. The use of XML promotes model sharing, is human readable and allows collaborative working. The syntax uses a high-level self explanatory format which allows straight forward code generation or translation of a model description to a native simulator format. This paper demonstrates the use of code generation in order to translate, simulate and reproduce the results of a benchmark model across a range of simulators. The flexibility of the SpineML syntax is highlighted by reproducing a pre-existing, biologically constrained model of a neural microcircuit (the striatum). The SpineML code is open source and is available at http://bimpa.group.shef.ac.uk/SpineML.

Next-Generation Applications on Cellular Networks: Trends, Challenges, and Solutions

Applications over cellular networks now range from operator–consumer applications (e.g., mobile television, voice-over-ip, video conferencing), peer-to-peer applications (e.g., instant messaging), machine-to-machine applications (e.g., data telemetry and automotive applications), mobile web services (e.g., music and video streaming), and social networking applications. The current approach for developing mobile applications appears to focus on utilizing template-based application-development kits provided by platform developers (e.g., Google's Android, Apple's iOS, or Nokia's Symbian) to capture application designs and install them on the runtime platforms through use of code generators tied to particular versions of the platform. It is still unclear as to how an application developer (or network operator) conceptualizes the features of a mobile application in a platform-independent way, identifies its utility and explores its impact on the user, or further refines the choice of technology, platform, and mobility/interactivity requirements. This paper attempts to offer some guidelines, based on recent research in the industry and academia in these areas, toward the design and development of successful mobile applications that can utilize the capabilities of the next generation of cellular networks. We provide an overview of the growing trends of the rich multimedia and real-time mobile applications, including the diversity of application types, their impact on the enterprise and consumer, their traffic volumes, and their load and communication patterns. In addition to the overall trend analysis, we also study the design choices that are to be made, and how they are realized, and also describe how the platforms (client and server) may be implemented. Additionally, we focus on mobile video applications according to their communication characteristics and their distinct demands on the cellular network. We also present an analysis of device and network application programming interfaces (API) that form the basic building blocks for efficient and secure mobile application development of the future.

Constrained Model Predictive Control on a Programmable Automation System Exploiting Code Generation: Practical Considerations

AbstractThis paper examines the use of code generators for Model Predictive Control (MPC) on a Programmable Automation Controller (PAC). Recently, a strong interest has been observed in code generators able to produce dedicated code for solving optimization problems on embedded devices. This interest has consecutively raised questions about usability, flexibility and user-friendliness of these code generators in more standard industrial hardware or lab equipment. To this end, the current paper investigates as a benchmark example the constrained model predictive control of a real-life Two Input – Single Output hair dryer system that is controlled with a CompactRIO controller (National Instruments). The aim is to provide practical information throughout the description of the entire development process (i.e., from model identification over code generation to MPC implementation and validation). Hence, advantages as well as possible limitations and pitfalls are explored.

Memoization in Type-Directed Partial Evaluation

We use a code generator--type-directed partial evaluation--to verify conversions between isomorphic types, or more precisely to verify that a composite function is the identity function at some complicated type. A typed functional language such as ML provides a natural support to express the functions and type-directed partial evaluation provides a convenient setting to obtain the normal form of their composition. However, off-the-shelf type-directed partial evaluation turns out to yield gigantic normal forms.<br /> <br />We identify that this gigantism is due to redundancies, and that these redundancies originate in the handling of sums, which uses delimited continuations. We successfully eliminate these redundancies by extending type-directed partial evaluation with memoization capabilities. The result only works for pure functional programs, but it provides an unexpected use of code generation and it yields orders-of-magnitude improvements both in time and in space for type isomorphisms.

Determinants of software maintenance profiles: an empirical investigation

Software maintenance is a task that is difficult to manage effectively. In part, this is because software managers have very little knowledge about the types of maintenance work that are likely to occur. If managers could forecast changes to software systems, they could more effectively plan, allocate workforce and manage change requests. But, the ability to forecast software modifications depends on whether there are predictable patterns in maintenance work. We posit that there are patterns in maintenance work and that certain characteristics of software modules are associated with these patterns. We examine modification profiles for 621 software modules in five different business systems of a commercial merchandiser. We find that only a small number of modules in these systems is likely to be modified frequently, and that certain maintenance patterns emerge. Modules frequently enhanced are in systems whose functionality is considered strategic. Modules frequently repaired have high software complexity, are large in size, and are relatively older. However, modules that have been code generated are less likely to be repaired. Older and larger modules are restructured and upgraded more frequently. Our results suggest that these characteristics of software modules are associated with predictable maintenance profiles. Such profile information can be used by software managers to predict and plan for maintenance more effectively. In addition, our results suggest the use of code generators as a means of reducing repair maintenance. © 1997 John Wiley & Sons, Ltd.