PACGBI: A Pipeline for Automated Code Generation from Backlog Items

Pipeline for Automated Code Generation from Backlog Items (PACGBI)

Wind energy has the advantages of wide distribution, renewable, and non-polluting, so it is receiving more and more attention from more and more countries. As more and more wind power systems are integrated into the grid, it has an impact on the stability of the grid. To keep the power system stable, there is an urgent need for a grid simulator that can simulate various behaviors of the grid and test the reliability of the wind turbine before grid integration. Inverters, especially multilevel inverters, as the core part of the grid simulator, have been widely studied by scholars in recent years. However, compared to conventional inverters, multilevel inverters are characterized by high code development effort, great difficulty, and a long development period. In this paper, we adopt an automatic DSP code generation method with MATLAB hardware support package and give a complete system design method and development flow based on MATLAB and TMSF28335 automatic code generation. Finally, we take the closed-loop three-level MMC inverter as an example, propose an equalization algorithm suitable for automatic code generation for the capacitor-voltage balancing part, and verify the feasibility of the DSP automatic code generation in a multilevel inverter development. The feasibility of DSP automatic code generation in the development of a multilevel inverter is verified. The experimental results show that the proposed equalization algorithm with variable reference coefficient and DSP automatic code generation method can be used in the development of a multilevel inverter, which can improve development efficiency and reduce development costs.

The increasing reliance on automatic code generation integrated with Generative AI technology has raised new challenges for cybersecurity defense against code injection, insecure code templates, and adversarial manipulation of an AI model. These risks make developing advanced frameworks imperative to ensure secure, reliable, and privacy-preserving code generation processes. The paper presents a novel Hybrid Artificial Neural Network (ANN)-Interpretive Structural Modeling (ISM) Framework to alleviate the cybersecurity risks associated with the automatic code generation using Generative AI. The proposed framework integrates the predictive capability of ANN and structured analysis of ISM for the identification, evaluation, and treatment of common vulnerabilities and risks in automatic code generation. We first conduct a multivocal literature review (MLR) to identify cybersecurity risks and generative AI practices for addressing these risks in automatic code generation. Then we conduct a questionnaire survey to identify and validate the identified risks and practices. An expert panel review was then assigned for the process of ANN-ISM. The ANN model can predict potential security risks by learning from historical data and code generation patterns. ISM is used to (1) structure and visualize (2) relations between identified risks and mitigation approaches and (3) offer a combined, multi-layered risk management methodology. We then perform an in-depth examination of the framework with a case study of an AI-based code generation company. We further determine its practicality and usefulness in real-world settings. The case study results show that the framework efficiently handles the primary cybersecurity challenges, such as injection attacks, code quality, backdoors, and lack of input validation. The analysis characterizes the maturity of several mitigation practices and areas for improvement for security integration with automatic code generation functionality. Advanced risk mitigation is enabled in the framework across multiple process areas, where techniques such as static code analysis, automated penetration testing, and adversarial training hold much promise. The Hybrid ANN-ISM Mechanism is a stable and flexible solution for cybersecurity risk reduction in automatic code generation environments. The coupling of ANN and ISM, in terms of predictive analysis and structured risk management, respectively, contributes effectively towards the security of AI-based code generation tools. More research is required to improve the scalability, privacy preserving, and dynamic integration of the framework with cybersecurity threat intelligence.

"Software development is an important area in software engineering, which is why a wide range of techniques, methods, and approaches has emerged to facilitate software development automation. This paper presents an analysis and evaluation of tools for automated software development and automatic code generation in order to determine whether they meet a set of quality metrics. Diverse quality metrics were considered such as effectiveness, productivity, safety, and satisfaction in order to carry out a qualitative and quantitative evaluation. The tools evaluated are CASE tools, frameworks, and Integrated Development Environments (IDEs). The evaluation was conducted to measure not only the tools’ ability to be employed, but also their support for automated software development and automatic source code generation. The aim of this work is to provide a methodology and a brief review of the most important works to identify the main features of these works and present a comparative evaluation in qualitative and quantitative terms of quality metrics. This would provide software developers with the information they need to decide the tools that can be useful for them."

In this paper, we present a series of experiments made with the aim of determining the scheduling mechanism for which the overhead is minimal. And that in the way to adopt it in the algorithm of automatic generation of the scheduled code that we developed.

In this paper incorporating manual and automatic code generation is discussed. A solution for automatic metadata-driven code generation is presented illustrated with multi tier Enterprise Resource Planning System. We intend to make our solution available to public in order to encourage investigation of code generation and schema-driven tools for .NET Framework.

The gap between design and implementation always exists because changes happen frequently throughout software development process, along with rapid release cycles, and accompanied by time constraints and limited resources. The focus of our work is to reduce this gap for service-oriented projects. We proposed an approach which considers both technical strategies and agile methods, trying to streamline the progression from design to implementation at a relatively early phase, and then throughout the whole development lifecycle. Automatic code generation has the potential to reduce above problems to a certain extent. This paper describes our efforts to enable rapid and continuous delivery while leveraging parallelism in development via automatic code generation — specifically making domain models instantly executable. We describe a code generator that has been built to enable parallel development of services. It uses UML class diagram to model the problem domain, then rapidly realize the domain model as a set of NoSQL database collections, automate the generation of common database access functions, and automate the wrapping of these database functions within a set of RESTful APIs. We also consider several common deployment scenarios (e.g. requirements for media-handling, security, scalability) to ensure the flexibility and reusability of the target source code for subsequent development iterations. Several empirical project instances have been built using this code generation technique. Combine with agile methods, we attempt to shorten development schedule in both design and implementation stages, and to eliminate the risks caused by evolutionary development. The result shows a great saving of effort on development and less issues in implementation stage.

Embedded real-time systems employ a variety of operating system platforms. Consequently, for automatic code generation, considerable redevelopment is needed when the platform changes. This results in major challenges with respect to the automatic code generation process of the architecture analysis and design language (AADL). In this paper, we propose a method of template-based automatic code generation to address this issue. Templates are used as carriers of automatic code generation rules from AADL to the object platform. These templates can be easily modified for different platforms. Automatic code generation for different platforms can be accomplished by formulating the corresponding generation rules and transformation templates. We design a set of code generation templates from AADL to the object platform and develop an automatic code generation tool. Finally, we take a typical Data Processing Unit (DPU) system as a case study to test the tool. It is demonstrated that the auto-generated codes can be compiled and executed successfully on the object platform.

<div class="htmlview paragraph">Model-based software development and automatic code generation have become increasingly established in recent years. The automotive industry has widely adopted and successfully deployed these methods in many different series production programs worldwide. This brought various benefits, such as a reduction in development times, improved quality due to more precise specifications, and early verification and validation by means of simulation.</div> <div class="htmlview paragraph">At the same time, more and more safety-related and safety-critical systems have been - and will be -introduced into modern vehicles. Common examples are active front steering, adaptive cruise-control, and integrated chassis control.</div> <div class="htmlview paragraph">This leads to the question, if and how model-based design and automatic production code generation can be applied to the development of safety-critical systems.</div>

Automatic code generation based on Coloured Petri Net (CPN) models is challenging because CPNs allow for the construction of abstract models that intermix control flow and data processing, making translation into conventional programming constructs difficult.We introduce Process-Partitioned CPNs (PP-CPNs) which is a subclass of CPNs equipped with an explicit separation of process control flow, message passing, and access to shared and local data. We show how PP-CPNs caters for a four phase structure-based automatic code generation process directed by the control flow of processes. The viability of our approach is demonstrated by applying it to automatically generate an Erlang implementation of the Dynamic MANET On-demand (DYMO) routing protocol specified by the Internet Engineering Task Force (IETF).

The complexity of embedded systems design is continuously augmented, due to the increasing quantity of components and distinct functionalities incorporated into a single system. To deal with this situation, abstraction level of projects is incessantly raised. In addition, techniques to accelerate the code production process have appeared. In this context, the automatic code generation is an interesting technique for the embedded systems project. This work presents an automatic VHDL code generation method based on the OpenMP parallel programming specification. In order to synthesize C code for loops into hardware, the authors applied the directives of OpenMP, which specifies portable implementations of shared memory parallel programs. A case study focused on the use of embedded systems for the DCT algorithm is presented in this paper to demonstrate the feasibility of the proposed approach.

Automatic code generation is a standard method in software engineering since it improves the code consistency and reduces the overall development time. In this context, this paper presents a design flow for automatic VHDL code generation of mppSoC (massively parallel processing System-on-Chip) configuration. Indeed, depending on the application requirements, a framework of Netbeans Platform Software Tool named MppSoCGEN was developed in order to accelerate the design process of complex mppSoC. Starting from an architecture parameters design, VHDL code will be automatically generated using parsing method. Configuration rules are proposed to have a correct and valid VHDL syntax configuration. Finally, an automatic generation of Processor Elements and network topologies models of mppSoC architecture will be done for Stratix II device family. Our framework improves its flexibility on Netbeans 5.5 version and centrino duo Core 2GHz with 22 Kbytes and 3 seconds average runtime. Experimental results for reduction algorithm validate our MppSoCGEN design flow and demonstrate the efficiency of generated architectures.

Design models are widely spread as core artifacts in software engineering. Yet, a key problem is how to fulfill correctly these blueprint specifications when code components are developed. The best possible scenario occurs when a source modeling language can be perfectly linked to a target language of election. Namely, a well defined mapping bridges the gap between the source and the target language. Otherwise, manual encoding of the system design is cumbersome and error prone. In this setting, we introduce a SQL-PL1 code generator for OCL expressions that, in contrast to other proposals, is able to map OCL iterate and iterator expressions thanks to our use of stored procedures. More in detail, our source language is the Object Constraint Language (OCL), which nowadays is an ISO standard used to express constraints and queries in a textual notation on UML models. Our target language is the procedural language (PL) extension to the Structured Query Language (SQL). SQL is a special-purpose programming language designed for managing data in relational database management systems (RDBMS). The purpose of PL for SQL is to combine database language and procedural programming language. Although SQL is also an ISO standard, different RDBMS implement certain syntactic variations to the standard SQL notation. Thus, we had to adapt the implementation of our mapping to each of them. As implementation targets we selected MariaDB, PostgreSQL, and MS SQL Server. MariaDB and PostgreSQL were selected because they are open source and widely used by developers. MS SQL server was selected to be able to compare evaluation time from open source to commercial RDBMS. A variety of applications arises for a mapping from OCL to SQL expressions. Among others, there are three prominent types. These are i) evaluation of OCL expressions (analysis queries and metrics) on large model's instances, ii) identification of constraints during data modeling that have to be checked as integrity constraints on actual data; iii) automatic code generation from models. Indeed, our implementation was used as a key component of a toolkit that automatically generated ready-to-deploy web applications for secure data management from design models. Our component mapped and evaluated OCL constraints specified within authorization policies. Our code generator is defined recursively over the structure of OCL expressions and it is implemented in the SQL-PL4OCL tool that is publicly available at [1]. The seminal work of the mapping presented here can be found in [2], [3]. The key idea that enables the mapping from OCL iterator expressions to iterative stored procedures remains the same, but the work detailed in [4] introduces a novel mapping from OCL expressions to SQL-PL stored procedures. In the novel mapping we have taken design decisions which have facilitated the recursive definition of the code generator and simplified its definition. These decisions have also helped to significantly decrease the time required for the evaluation of the code generated. Regarding semantics, the new mapping is able to deal properly with the three-valued evaluation semantics of OCL. In addition, our original work and implementation was intended only for the procedural extension of MySQL, while our new definition eased the implementation of the mapping into other relational database management systems. In turn, we can now evaluate the resulting code using different RDBMS, which permits us to widen our discussion regarding efficiency in terms of evaluation-time of the code produced by SQL-PL4OCL tool.

Automatic code generation for production automotive powertrain applications introduces many challenges for the tool vendor. Resource efficiency, reliability, and product process development issues need to be addressed. Automatic code generation used for rapid prototyping systems usually will not satisfy the requirements necessary for production oriented code generation. Some of the requirements critical to automatic code generation are not immediately obvious to a tool vendor who is not active in the user's industry. The purpose of this paper is to address some of the most common requirements for production automotive powertrain code generation.

Computer Aided Control System Design (CACSD) tools are finding greater usage in the development of embedded control systems. Automatic code generation for CACSD models is of increasing interest. However, in order to introduce automatic code generation into high volume production applications, it is necessary to have a high degree of confidence in the automatic code generation tool reliability, robustness and efficiency. Validation of automatic code generation is complex and expensive. Theoretical approaches offer promise but do not necessarily scale well and address increasing complexity. Therefore, a more practical approach has been developed that addresses the complex and diverse nature of the problem. This paper discusses the practical approaches employed to help establish a high degree of confidence that automatic code generation can be successfully deployed in high volume production applications.