Multiprogramming Language Research Articles

An exploratory study on just-in-time multi-programming-language bug prediction

Context:An increasing number of software systems are written in multiple programming languages (PLs), which are called multi-programming-language (MPL) systems. MPL bugs (MPLBs) refers to the bugs whose resolution involves multiple PLs. Despite high complexity of MPLB resolution, there lacks MPLB prediction methods. Objective:This work aims to construct just-in-time (JIT) MPLB prediction models with selected prediction metrics, analyze the significance of the metrics, and then evaluate the performance of cross-project JIT MPLB prediction. Methods:We develop JIT MPLB prediction models with the selected metrics using machine learning algorithms and evaluate the models in within-project and cross-project contexts with our constructed dataset based on 18 Apache MPL projects. Results:Random Forest is appropriate for JIT MPLB prediction. Changed LOC of all files, added LOC of all files, and the total number of lines of all files of the project currently are the most crucial metrics in JIT MPLB prediction. The prediction models can be simplified using a few top-ranked metrics. Training on the dataset from multiple projects can yield significantly higherAUC than training on the dataset from a single project for cross-project JIT MPLB prediction. Conclusions:JIT MPLB prediction models can be constructed with the selected set of metrics, which can be reduced to build simplified JIT MPLB prediction models, and cross-project JIT MPLB prediction is feasible.

Recurrent Semantic Learning-Driven Fast Binary Vulnerability Detection in Healthcare Cyber Physical Systems

Healthcare cyber physical systems (HCPS) always pursuing high availability allow software providers to adopt multiple kinds of development languages to reuse third-party program codes, while leading to the wide propagation of hidden software vulnerabilities. However, it is impossible to accurately trace execution paths and locate the key elements during the software execution process, which makes semantic features of vulnerabilities in the binary code can not bed extracted. This is the key support in automated vulnerability detection practices. To address these problems, a novel fast vulnerability detection mechanism based on recurrent semantic learning is proposed, which does not require high-level permissions to access the compiling process and traverse all execution paths. Firstly, a programframe is constructed to integrate software run-time logic and executing environment, detecting vulnerabilities from multi-programming language binary codes. Secondly, to achieve the powerful software execution context-awareness ability, a cascaded-LSTM recurrent neural network is designated to extract semantic features from binary files with vulnerabilities. Besides, we establish an experimental toolkit named an intelligent vulnerability detector (IntVD) to demonstrate the effectiveness of the proposed methods. Extensive and practical experiments validate that the vulnerability recognition accuracy on the HCPS software including VLC and LibTIFF can reach more than 95%.

Web-based dashboard of data integration for green highway performance management

Highway concessionaires in Malaysia spend considerable assets for managing different forms of data during highway projects' life cycles. In this context, and based on the use of modern technologies, an enormous volume of highway data is generated daily. These data can be utilized to extract and evaluate indicators to analyze highway green performance. Feedback from indicators allows to grasp the sustainable practices and implement corrective actions. Dashboards have become popular in recent years as uniquely powerful tools for communicating important information. This research adopted the approach of a centralized data provider to develop a web-based visualization dashboard, as a technique to reinforce decisions in the highway sector. The dashboard will be employed to gain information about highway green performance to enhance decisions. In this dashboard, data integration of Malaysia Green Highway Index and Carbon Footprint Calculator has been used in illustrating the visualization. The development utilized a web-based multi-programming language. The quantitative and qualitative measures were used to validate the dashboard. Findings demonstrated an increase in accuracy of data monitoring and quicker decision-making using the Dashboard. The outcome of this research will add value to the green highway development and map the highway towards a better and sustainable quality of life nationally and internationally. Furthermore, this research will pave the way for future researchers to integrate other efficient tools and parameters that contribute towards sustainable development.

Knowledge Distillation-Based Multilingual Code Retrieval

Semantic code retrieval is the task of retrieving relevant codes based on natural language queries. Although it is related to other information retrieval tasks, it needs to bridge the gaps between the language used in the code (which is usually syntax-specific and logic-specific) and the natural language which is more suitable for describing ambiguous concepts and ideas. Existing approaches study code retrieval in a natural language for a specific programming language, however it is unwieldy and often requires a large amount of corpus for each language when dealing with multilingual scenarios.Using knowledge distillation of six existing monolingual Teacher Models to train one Student Model—MPLCS (Multi-Programming Language Code Search), this paper proposed a method to support multi-programing language code search tasks. MPLCS has the ability to incorporate multiple languages into one model with low corpus requirements. MPLCS can study the commonality between different programming languages and improve the recall accuracy for small dataset code languages. As for Ruby used in this paper, MPLCS improved its MRR score by 20 to 25%. In addition, MPLCS can compensate the low recall accuracy of monolingual models when perform language retrieval work on other programming languages. And in some cases, MPLCS’ recall accuracy can even outperform the recall accuracy of monolingual models when they perform language retrieval work on themselves.

Multi-programming language software systems modularization

A software system evolves over time to meet the user’s new requirements as well as to adapt to the environment. This causes it deviates from its original and documented structure. Hence, after a while, due to its low understandability, making new changes will not be easy. Modularization is utilized to extract the software system structure from the source code to understand it. Recently, there has been a significant increase in writing large-scale applications in collaboration with several programming languages; for example, Mozilla Firefox 3.7 is written in more than twenty programming languages. Understanding such applications for maintaining them is a challenging problem. Existing modularization methods to understand an application are only applicable to programs which are written in a programming language. This paper introduces the concept of multi-programming language modularization. It then presents a technique for modularization of applications which are written in multiple programming languages. The results on Mozilla Firefox demonstrate that the proposed approach can extract a modularization close to human experts, a capability which may help in understanding an application.

Unified software repositories for Wendelstein 7-X: Workflow elements for fusion software development

Software development for a large project like Wendelstein 7-X (W7-X) requires an appropriate development process to provide a reliable environment supporting the coordinated work of scientific and engineering stakeholders. The first step to achieve this goal was the installation of a central source code management system (SCM). Besides being a code base it provides functions allowing the specification of a release procedure by introducing levels of acceptance specified by appropriate quality criteria. The SCM system serves as a starting point for automatic generation of standard code documentation and for performing automatic testing procedures on standardized integration platforms. In order to provide a universal documentation platform for the multi programming language environment at W7-X the DocSys system has been developed which allows to employ any (language specific) document generator producing html-pages for presentation via internet. An automatic integration testing environment is still being prepared and not yet in standard use.

A pictorial approach to the animation of process-oriented formal specifications

This paper considers how the meaning of process-oriented formal specifications might be made more apparent through the use of pictorial animation. The approach taken is based on techniques embodied in the software animation system PEEP. The PEEP system gives pictorial representations of the changing states of software as it is executed. It was designed for concurrent applications expressed in a modular multiprogramming language, such as Ada or Pascal Plus. Corresponding formal languages suitable for the specification of concurrent systems include CSP, CCS, SDL and LOTOS. The LOTOS language is used for illustration purposes in this paper, but the techniques discussed are equally applicable to the other languages.

Process administration in a high level language

AbstractThe traditional approach to the implementation of process administration in multiprogrammed systems is to make it part of the run‐time system or ‘kernel’. This implies first, that the implementation is written in assembler language, and secondly that the process administration will be very inflexible. This article outlines a high level language PoMP, a Pascal extension. Following the trend set by Concurrent Pascal and Modula towards integrating ever increasing parts of the ‘kernel’ in the individual application program, PoMP provides language constructs for implementing process administration. It is shown that the multiprogramming language constructs of a number of languages may be ‘imitated’ in PoMP.

PLE: A high-level multiprogramming language for psychology

This paper describes a software system called PLE that is designed to turn a Data General Corporation computer system into a sophisticated infinite-channel tachistoscope. We describe hardware and software characteristics of the PLE system and evaluate its performance in comparison to a typical tachistoscope. Additionally, we describe two example experiments that have been implemented in the PLE system.

Design and implementation of modula

AbstractThis paper gives an account of some design decisions made during the development of the programming language Modula. It explains the essential characteristics of its implementation on the PDP‐11 computer, in particular its run‐time administration of processes and the mechanism of signalling. The paper ends with some comments on the suitability of the PDP‐11 for this high‐level multiprogramming language.