Automated Software Development Research Articles

PyScribe–Learning to describe python code

AbstractCode comment generation, which attempts to summarize the functionality of source code in textual descriptions, plays an important role in automatic software development research. Currently, several structural neural networks have been exploited to preserve the syntax structure of source code based on abstract syntax trees (ASTs). However, they can not well capture both the long‐distance and local relations between nodes while retaining the overall structural information of AST. To mitigate this problem, we present a prototype tool titled PyScribe, which extends the Transformer model to a new encoder‐decoder‐based framework. Particularly, the triplet position is designed and integrated into the node‐level and edge‐level structural features of AST for producing Python code comments automatically. This paper, to the best of our knowledge, makes the first effort to model the edges of AST as an explicit component for improved code representation. By specifying triplet positions for each node and edge, the overall structural information can be well preserved in the learning process. Moreover, the captured node and edge features go through a two‐stage decoding process to yield higher qualified comments. To evaluate the effectiveness of PyScribe, we resort to a large dataset of code‐comment pairs by mining Jupyter Notebooks from GitHub, for which we have made it publicly available to support further studies. The experimental results reveal that PyScribe is indeed effective, outperforming the state‐ofthe‐art by achieving an average BLEU score (i.e., av‐BLEU) of 0.28.

Разработка онтологий для автоматизации вычислительных процессов при проектировании трубопроводных систем энергетики

Designing pipeline energy systems (heat, water, oil, gas supply, etc.) is a complex task that requires the use of specialized software to solve it. It is proposed to use ontologies to structure knowledge that is used in the processes of software development automation and organization of the computing process and user interface content. The proposed methodological approach includes the following components: the composition of ontologies, tools for implementing ontologies, and the methods for constructing ontologies (metaontologies, ontologies of specific classes, ontologies of design tasks, software ontologies). It is shown that the use of ontologies allows one to obtain the following results: a single platform for research and development of new methods, algorithms, mathematical models of pipeline systems and their elements; the ability to automate access to data for different types of systems and tasks; and automated software system construction. An example of ontology system application in software development is presented. The architecture of a software system for solving problems of designing pipeline systems of various types and purposes is given.

An Interview with Chunyang Chen - 2023 SIGSOFT Awardee

Chunyang Chen received the 2023 SIGSOFT Early Career Researcher Award for outstanding contributions to the study of intelligent software development automation including automated mobile application development, software testing, migration, and accessibility. He received a Ph.D. in computer science from School of Computer Science and Engineering, Nanyang Technological University (Singapore). He is now a senior lecturer in the Faculty of Information Technology of the Monash University (Australia).

Three Principles of Intellectualization of Automated Systems

Three Principles of Intellectualization of Automated Systems

CONTINUOUS SOFTWARE DELIVERY FOR WEB PROJECTS BASED ON MICROSERVICES

Continuous Integration, Code delivery, and Deployment is a software development automation methodology representingone of the key components of DevOps (an acronym for development & operations). The research object of the present work is a system of continuous delivery and deployment of software projects (SP). In the article the scheme of software infrastructure architecture with continuous integration and code delivery based on SOLID principles is analyzed. A special methodology has been developed to ensure the secure transmission of transport data with encryption and digital signature of documents, which is focused on the projects of the system users. A software project for continuous delivery and deployment of application versions with an auto-configuration system is presented. Project development stages are described in detail. The initial system output is provided.

An automated software development for analysis of the morphological-tensile property relationship in egg shell bio-based particulate composites using machine learning algorithms

This work explored the importance of quantitative observation through imaging methods of optical and electron microscopies on the mechanical properties of particulate polymeric composites. Egg shell powder (ESP) reinforced polypropylene carbonate (PPC) polymeric composites with different filler weight percentage (wt.%) from 1 to 5 wt.% were considered. A cost-effective Image Analysis Software (IAS) was developed to extract black particles from the original optical images. During this process, the optimal image can be reproduced based on its originality by controlling the threshold values from 0.1 to 0.6 in real time situation. Using one-dimensional (1D) Gaussian distribution analysis, the authentication of the particle distribution data was studied and linked to the tensile strength of the composites. The mean value of the particle area collected from the left and right side of the scattered curves has a significant effect on the tensile strength of the composites. The proposed model was validated by comparing the predicted statistical results with the measured tensile strength for different wt.% of ESP composites. From the results obtained, a close agreement of 99% accuracy was observed between the experimental results and the proposed model for the tensile strength of the composites. The innovative study provides more practical and quantitative knowledge on improved particulate polymeric composites, in addition to the detection of failure processes through optical/electron microscopic examination of images. Evidently, the proposed cost effective, accurate and less stressful model can be employed by several composite-based industries to correlate the tensile strengths of particulate polymeric composites with their morphological properties.

Introduction of an Assistance System to Support Domain Experts in Programming Low-Code to Leverage Industry 5.0

The rapid technological leaps of Industry 4.0 increase the pressure and demands on humans working in automation, which is one of the main motivators of Industry 5.0. In particular, automation software development for mechatronic systems becomes increasingly challenging, as both domain knowledge and programming skills are required for high-quality, maintainable software. Especially for small companies from automation and robotics without dedicated software engineering departments, domain-specific low-code platforms become indispensable that enable domain experts to develop code intuitively using visual programming languages, e.g., for tasks such as retrofitting mobile machines. However, for extensive functionalities, visual programs may become overwhelming due to the scaling-up problem. In addition, the ever-shortening time-to-market increases the time pressure on programmers. Thus, an assistance system concept is introduced that can be implemented by low-code platform suppliers based on combining data mining and static code analysis. Domain experts are supported in developing low-code by targeted recommendations, metric-based complexity measurement, and reducing complexity by encapsulating functionalities. The concept is implemented for the industrial low-code platform HAWE eDesign to program hydraulic components in mobile machines, and its benefits are confirmed in a user study and an industrial expert workshop.

Towards cost-benefit evaluation for continuous software engineering activities

Context:Software companies must become better at delivering software to remain relevant in the market. Continuous integration and delivery practices promise to streamline software deliveries to end-users by implementing an automated software development and delivery pipeline. However, implementing or retrofitting an organization with such a pipeline is a substantial investment, while the reporting on benefits and their relevance in specific contexts/domains are vague.Aim:In this study, we explore continuous software engineering practices from an investment-benefit perspective. We identify what benefits can be attained by adopting continuous practices, what the associated investments and risks are, and analyze what parameters determine their relevance.Method:We perform a multiple case study to understand state-of-practice, organizational aims, and challenges in adopting continuous software engineering practices. We compare state-of-practice with state-of-the-art to validate the best practices and identify relevant gaps for further investigation.Results:We found that companies start the CI/CD adoption by automating and streamlining the internal development process with clear and immediate benefits. However, upgrading customers to continuous deliveries is a major obstacle due to existing agreements and customer push-back. Renegotiating existing agreements comes with a risk of losing customers and disrupting the whole organization.Conclusions:We conclude that the benefits of CI/CD are overstated in literature without considering the contextual and domain complexities rendering some benefits infeasible. We identify the need to understand the customer and organizational perspectives further and understand the contextual requirements towards the CI/CD.

Clone-Writer: An effective editor for developing code by using code clones

<h2>Abstract</h2> "Code completion" is an important feature of code editors. Such editors usually provide recommendations in terms of next likely code token(s) of fixed length on the basis of code written so far. Code clones (similar code fragments), which play an important role in rapid development, are traditionally neglected as part of code completion. To facilitate code clone reuse, we propose an automated software development tool, called Clone-Writer. The tool helps develop code swiftly by recommending code clones on the basis of code written so far. Moreover, developers can perform code clone search based on a search query written either as source code terms, or as natural language. The tool also contains different visualization features supporting code completion. We have evaluated our tool by considering the classification framework of visualization methods along with user goals and information needs.

Placing Trust in Automated Software Development Processes

Automation of certain aspects of software development and maintenance help us achieve our software-productivity goals, but we need to consider the trust we can place in that automation.

Novel development tool for IEC 61499 based on domain-specific languages

This paper presents an example of a systematic approach based on domain-specific languages to implement Function Blocks Modelling Environment (FBME): an integrated development environment (IDE) for the international standard IEC 61499. The new open development environment for the standard of growing importance in the Industry 4.0 realm would contribute to the broader adoption of open standard-based development practices and facilitate efficient automation software development.

Code Generation Using Machine Learning: A Systematic Review

Recently, machine learning (ML) methods have been used to create powerful language models for a broad range of natural language processing tasks. An important subset of this field is that of generating code of programming languages for automatic software development. This review provides a broad and detailed overview of studies for code generation using ML. We selected 37 publications indexed in arXiv and IEEE Xplore databases that train ML models on programming language data to generate code. The three paradigms of code generation we identified in these studies are description-to-code, code-to-description, and code-to-code. The most popular applications that work in these paradigms were found to be code generation from natural language descriptions, documentation generation, and automatic program repair, respectively. The most frequently used ML models in these studies include recurrent neural networks, transformers, and convolutional neural networks. Other neural network architectures, as well as non-neural techniques, were also observed. In this review, we have summarized the applications, models, datasets, results, limitations, and future work of 37 publications. Additionally, we include discussions on topics general to the literature reviewed. This includes comparing different model types, comparing tokenizers, the volume and quality of data used, and methods for evaluating synthesized code. Furthermore, we provide three suggestions for future work for code generation using ML.

TREND database: Retinal images of healthy young subjects visualized by a portable digital non-mydriatic fundus camera.

Topological characterization of the Retinal microvascular nEtwork visualized by portable fuNDus camera (TREND) is a database comprising of 72 color digital retinal images collected from the students of the Faculty of Medicine at the University of Montenegro, in the period from February 18th to March 11th 2020. The database also includes binarized images of manually segmented microvascular networks associated with each raw image. The participant demographic characteristics, health status, and social habits information such as age, sex, body mass index, smoking history, alcohol use, as well as previous medical history was collected. As proof of the concept, a smaller set of 10 color digital fundus images from healthy older participants is also included. Comparison of the microvascular parameters of these two sets of images demonstrate that digital fundus images recorded with a hand-held portable camera are able to capture the changes in patterns of microvascular network associated with aging. The raw images from the TREND database provide a standard that defines normal retinal anatomy and microvascular network geometry in young healthy people in Montenegro as it is seen with the digital hand-held portable non-mydriatic MiiS HORUS Scope DEC 200.This knowledge could facilitate the application of this technology at the primary level of health care for large scale telematic screening for complications of chronic diseases, such as hypertensive and diabetic retinopathy. In addition, it could aid in the development of new methods for early detection of age-related changes in the retina, systemic chronic diseases, as well as eye-specific diseases. The associated manually segmented images of the microvascular networks provide the standard that can be used for development of automatic software for image quality assessment, segmentation of microvascular network, and for computer-aided detection of pathological changes in retina. The TREND database is freely available at https://doi.org/10.5281/zenodo.4521043.

RESEARCH OF DATA TYPE CLASSIFICATION METHODS WHEN DEVELOPING COMPUTER ENGINEERING SOFTWARE

The paper deals with the problems of increasing the efficiency of software development, in particular, the issue of reducing the time for developing programs and using automated synthesis of programs, which will avoid the revision of the original product. The software should be tested along with other system components in all combinations that may occur. Testing is time-consuming because hidden bugs are revealed through unexpected interactions between software components. With structural analysis, data flow diagrams are not the end result, they are a developer tool. First, diagrams are built, and then mechanisms are developed to ensure the required system behavior. A graphical approach to solving the problem of automation of software development is being developed, based on the involvement of visual forms of program presentation. For any program object, you can select a finite number of states in which it is at each moment of time. The program progress is associated with the transition of an object from one state to another. The graph replaces the textual form of the description of the program algorithm, while the visual representation of the algorithm is realized. The specification of data structures, as well as the setting of intermodular interfaces according to data, is separated from the description of the structure of the algorithm and controls. Basic modules and data types are used. Basic modules are local calculable functions, on the basis of which all other technology objects are generated. Data types describe the syntactic and semantic aspects of constructing data used in base functions. Algorithms for finding routes on directed graphs are considered. When defining routes from the root vertex to the final ones, the properties of the algebra of three-valued logic were used. Based on the considered approach, as well as taking into account its shortcomings, a method for classifying data types was proposed, based on the implementation of a partial enumeration of the routes of the graph of program links and a method for designing software based on it, taking into account minimizing the time and cost of the project.&#x0D; Keywords: software, computer engineering, information systems, components, partial enumeration of graph routes, development costs.

Automatic Generation of Object-Oriented Code from the ReLEL Requirements Model

The final executable code should no longer be considered as a central element in a software development process but rather a naturally important component that results from a model transformation. The objective of the MDA (Model Driven Architecture) approach is to lift the lock of software development automation from the CIM (Computation Independent Model) requirements until the code of an application is obtained. Therefore, we have proposed in the framework of MDA an approach that consists of automatically generating object-oriented code from the CIM model represented by ReLEL (Restructuring extended Lexical Elaborate Language). ReLEL is a natural language-oriented model that represents both the client requirements and the conceptual level of a system. However, the MDA framework does not recommend the type of UML model that corresponds to each business activity. Consequently, automating the software development process from the CIM model specified by ReLEL becomes a complex task. Our strategy in this paper includes the instantiation of the ReLEL model in the Praxeme methodology, which models each of the company's concerns, grouped in a homogeneous whole, using the UML (Unified Modeling Language) and which considers the articulation of these aspects by adopting the MDA principle. To do this, we propose to automate the articulation that covers the intentional, semantic, logical, and software aspects of Praxeme. To validate our approach, we measure the coupling and cohesion of the UML class diagram obtained from the Java code generated from this article using the slicing technique. The results show that the coupling is weak, and the cohesion is strong. It can be deduced that the method proposed in this paper can produce a more reliable and efficient system.

Use of Artificial Intelligence in Software Development Life Cycle

Current automated software development life cycle was mainly allotting with the automated generation code. That kind of method mostly include in the software combination from model’s design, predetermined polices or the fixed rules. In this paper we discuss about the propose an approach that should went above the SDL automated that should be presenting direct method which is able to make decision and take decision to generate code and software. The ontology do an important part of developer by fulfill the development of software affair freely. [2]Thus behavior catch a database of ontological permit highest level judgement to explain design and incorporate the logic of system depend on the configuration system which is physical system . This kind of method implement in graphical tools. This paper discuss the autonomated ontological form of methodology create the code of according to artificial intelligence

Development of a cyber design modeling declarative Language for cyber physical production systems

This paper considers the issues of software development automation for cyber-physical production systems within the framework of the Smart Manufacturing (SM) and Industry 4.0 concepts. The development of cyber-physical production systems (CPPS) for each enterprise is an individual task that takes into account the specifics of the production process, the requirements for data visualization at each level from Supervisory Control And Data Acquisition (SCADA) to Enterprise Resource Planning System (ERP) in a single information space using different technologies for processing and storing data. To ensure all the requirements that are specified by the customer in the technical requirement (TR), the authors propose to automate the process of developing a cyber-physical production systems Human-Machine Interface (HMI) prototype at an early stage of drafting the terms of reference together with the customer, which will make it possible to take into account all the requirements for visualizations information. Based on the experience gained in the development of cyber-physical production systems, the authors have developed a declarative cyber-design modeling language based on parameters mathematical description of the and Graphical User Interface (GUI) elements events, which allows to simplify the process of HMI cyber-physical production systems development at an early stage by generating fragments of program code for object-oriented programming languages.

An Experimental Study of Software Engineering Model for an Large Industry Automation Design

This paper will explain that how the traditional software development models can be used to automate the tasks in large scale industries. Using the SDLC approach, the development of the system can be automated which will save a lot of time and efforts which can be utilised for other crucial tasks. This paper will also brief the life cycle of automation. The advantages and challenges of the implementation of the automation software development will also be explained.

Software Development Automation: An Approach to Automate the Processes of SDLC

Software Development Automation: An Approach to Automate the Processes of SDLC

Algorithm of adaptation of electronic document management system based on machine learning technology

The topical problem in the development of electronic document management systems (EDMS) is their adaptation and personalization to the individual characteristics of the user. This article discusses the issue of development of an adaptation algorithm using machine learning methods for solving the problem of structural-parametric synthesis of EDMS. In the framework of the presented algorithm, the approaches to the formalization of workflow processes, ways to adapt the interface to the user parameters using artificial neural networks and a comprehensive assessment of the system’s adaptability are considered. The scientific novelty of the approach consists in the algorithmic and software development for automation of the data collection, analysis and interface adaptation through the use and integration of neural networks in the information system. The application of machine learning methods for the formation and adaptation of EDMS interface allows you to automate the process of personalizing it to the user’s individual characteristics, increase the system’s flexibility and provide the best user experience at the first interaction with EDMS based on the intelligent analysis of data about other users. The main scientific results obtained in the article include: formalized criteria for adapting EDMS; algorithm for designing and adapting EDMS; and development of software for adapting EDMS, including a trained neural network and API.