Ferosh Jacob

CnP: Towards an environment for the proactive management of copy-and-paste programming

Programmers copy and paste code for many reasons. Regardless of the specific reasons, similar code fragments (clones) are introduced into software systems. Like other software artifacts, clones may require attention and effort from programmers so that they can be understood, and correctly adapted and evolved. More specifically, when understanding and maintaining clones, programmers need to know where the clones are. Programmers also need to compare and contrast code clones in order to figure out how they correspond and differ. Finally, they also need to edit or remove clones. In addition to what clone detection-based tools can offer, more automated support is needed to better assist programmers in these activities. In this paper, we introduce a toolkit CnP that is aimed to support and manage clones proactively as they are created and evolved. We describe the initial features and the design decisions taken in CnP. We also discuss possible future design extensions.

CUDACL: A tool for CUDA and OpenCL programmers

Graphical Processing Unit (GPU) programming languages are used extensively for general-purpose computations. However, GPU programming languages are at a level of abstraction suitable only for use by expert parallel programmers. This paper presents a new approach through which ‘C’ or Java programmers can access these languages without having to focus on the technical or language-specific details. A prototype of the approach, named CUDACL, is introduced through which a programmer can specify one or more parallel blocks in a file and execute in a GPU. CUDACL also helps the programmer to make CUDA or OpenCL kernel calls inside an existing program. Two scenarios have been successfully implemented to assess the usability and potential of the tool. The tool was created based on a detailed analysis of the CUDA and OpenCL programs. Our evaluation of CUDACL compared to other similar approaches shows the efficiency and effectiveness of CUDACL.

Code template inference using language models

This paper investigates the use of a natural language processing technique that automatically detects project-specific code templates (i.e., frequently used code blocks), which can be made available to software developers within an integrated development environment. During software development, programmers often and in some cases unknowingly rewrite the same code block that represents some functionality. These frequently used code blocks can inform the existence and possible use of code templates. Many existing code editors support code templates, but programmers are expected to manually define these templates and subsequently add them as templates in the editor. Furthermore, the support of editors to provide templates based on the editing context is still limited. The use of n-gram language models within the context of software development is described and evaluated to overcome these restrictions. The technique can search for project-specific code templates and present these templates to the programmer based on the current editing context.

Actively comparing clones inside the code editor

Tool support for code clones can improve software quality and maintainability. While significant research has been done in locating clones in existing source code, there has been less of a research focus on proactively tracking and supporting copy-paste-modify operations, even though copying and pasting is a major source of clone formation and the resulting clones are then often modified. We designed and implemented a programming editor, based on the Eclipse integrated development environment, named CSeR (Code Segment Reuse), which keeps a record of copy-and-paste-induced clones and then tracks and visualizes the changes made to a clone with distinct colors. The core of CSeR is an algorithm that actively compares two clones for detailed differences as a programmer edits either one of them. This edit-based comparison algorithm is unique to CSeR and produces more immediate, accurate, and natural results than other differencing tools.

Exploring the design space of proactive tool support for copy-and-paste programming

Programmers copy and paste code for various reasons, leaving similar code fragments (clones) in the software systems. As a result, they must spend effort and attention in tracking, understanding, and correctly adapting and evolving clones. Ideally, an integrated environment should be used to fully and seamlessly assist programmers in all these activities. Unlike clone-detection-based tools, such environments should support and manage clones proactively as clones are created and evolved. In this paper, an initial design space for such environments is sketched based on our experience with a prototype named CnP. The features and design decisions taken in CnP as well as remaining design problems are identified. To assess the potential of the developed features and identify new design input, code clones in several real-world systems are examined, and their implications on the design (and redesign) of proactive clone tools are discussed.

Representing clones in a localized manner

Code clones (i.e., duplicate sections of code) can be scattered throughout the source files of a program. Manually evaluating group of such clones requires observing each clone in its origina location (i.e., opening each file and finding the source location o each clone), which can be a time-consuming process. As a alternative, this paper introduces a technique that localizes th representation of code clones to provide a summary of th properties of two or more clones in one location. In our approach the results of a clone detection tool are analyzed in an automate manner to determine the properties (i.e., similarities an differences) of the clones. These properties are visualized directl within the source editor. The localized representation is realize as part of the features of an Eclipse plug-in called CeDAR.

A platform-independent tool for modeling parallel programs

Programming languages that can utilize the underlying parallel architecture in shared memory, distributed memory or Graphics Processing Units (GPUs) are used extensively for solving scientific problems. However, from our observation of studying multiple parallel programs from various domains, such programming languages have a substantial amount of sequential code mixed with the parallel code. When rewriting the parallel code for another platform, the same sequential code is often reused without much modification. Although this is a common occurrence, existing tools and programming environments do not offer much support for this process. In this paper, we introduce a tool named PPmodel, which was designed and implemented to assist programmers in separating the core computation from the details of a specific parallel architecture. Using PPmodel, a programmer can identify and retarget the parallel section of a program to execute in a different platform. With PPmodel, a programmer is better enabled to focus on the parallel section of interest, while ignoring other parallel and sequential sections in a program. The tool is explained by example execution of the parallel section of an OpenMP program for the circuit satisfiability problem in a cluster using the Message Passing Interface (MPI).

Domain-specific languages for composing signature discovery workflows

Domain-agnostic signature discovery entails study across multiple scientific disciplines. The cross-disciplinary nature and breadth of this work requires that existing executable applications be integrated with new capabilities into workflows, representing a wide range of user tasks. An algorithm may be written in multiple programming languages for various hardware platforms, and so workflow composition requires integrating executables from any number of remote hosts. This raises an engineering issue on how to generate web service wrappers for these heterogeneous executables and to compose them into a scientific workflow environment (e.g., Taverna). In this position paper, we summarize our work on two simple Domain-Specific Languages (DSLs) that automate these processes. Our Service Description Language (SDL) describes key elements of a signature discovery service and automatically generates its implementation code. The Workflow Description Language (WDL) describes the pipeline of services and generates deployable artifacts for the Taverna workflow management system. We demonstrate our approach with a real-world workflow composed of services wrapping remote executables.

Domain-Specific Languages for Developing and Deploying Signature Discovery Workflows

Domain-agnostic signature discovery supports scientific investigation across domains through algorithm reuse. A new software tool defines two simple domain-specific languages that automate processes that support the reuse of existing algorithms in different workflow scenarios. The tool is demonstrated with a signature discovery workflow composed of services that wrap original scripts running high-performance computing tasks.

PPModel: a modeling tool for source code maintenance and optimization of parallel programs

As the computation power in desktops advances, parallel programming has emerged as one of the essential skills needed by next generation software engineers. However, programs written in popular parallel programming paradigms have a substantial amount of sequential code mixed with the parallel code. Several such versions supporting different platforms are necessary to find the optimum version of the program for the available resources and problem size. As revealed by our study on benchmark programs, sequential code is often duplicated in these versions. This can affect code comprehensibility and re-usability of the software. In this paper, we discuss a framework named PPModel, which is designed and implemented to free programmers from these scenarios. Using PPModel, a programmer can separate parallel blocks in a program, map these blocks to various platforms, and re-execute the entire program. We provide a graphical modeling tool (PPModel) intended for Eclipse users and a Domain-Specific Language (tPPModel) for non-Eclipse users to facilitate the separation, the mapping, and the re-execution. This is illustrated with a case study from a benchmark program, which involves re-targeting a parallel block to CUDA and another parallel block to OpenMP. The modified program gave almost 5× performance gain compared to the sequential counterpart, and 1.5× gain compared to the existing OpenMP version.