AIWARE

AI-powered software development tooling is changing the way that developers interact with tools and write code. However, the ability for AI to truly transform software development may depend on developers' levels of trust in these tools, which has ...

Large language models and other foundation models (FMs) boost productivity by automating code generation, supporting bug fixes, and generating documentation. We propose that FMs can further support Open Source Software (OSS) projects by assisting ...

The development of digital twins (DTs) for physical systems increasingly leverages artificial intelligence (AI), particularly for combining data from different sources or for creating computationally efficient, reduced-dimension models. Indeed, even in ...

Transformer-based language models are highly effective for code completion, with much research dedicated to enhancing the content of these completions. Despite their effectiveness, these models come with high operational costs and can be intrusive, ...

Software developers use natural language to interact not only with other humans, but increasingly also with chatbots. These interactions have different properties and flow differently based on what goal the developer wants to achieve and who they ...

The integration of Large Language Models (LLMs) and chatbots introduces new challenges and opportunities for decision-making in software testing. Decision-making relies on a variety of information, including code, requirements specifications, and other ...

Integrating Artificial Intelligence (AI) into software systems has significantly enhanced their capabilities while escalating energy demands. Ensemble learning, combining predictions from multiple models to form a single prediction, intensifies this ...

Large language models (LLMs) have revolutionized software development practices, yet concerns about their safety have arisen, particularly regarding hidden backdoors, aka trojans. Backdoor attacks involve the insertion of triggers into training data, ...

This paper presents a comprehensive comparative analysis of Large Language Models (LLMs) for generation of code documentation. Code documentation is an essential part of the software writing process. The paper evaluates models such as GPT-3.5, GPT-4, ...

The advent of advanced AI underscores the urgent need for comprehensive safety evaluations, necessitating collaboration across communities (i.e., AI, software engineering, and governance). However, divergent practices and terminologies across these ...

Generative Artificial Intelligence (GenAI) is being adopted for a number of Software Engineering activities, mostly centering around coding, such as code generation, code comprehension, code reviews, test generation, and bug fixing. Other phases in the ...

Modern code review is a process in which an incremental code contribution made by a code author is reviewed by one or more peers before it is committed to the version control system. An important element of modern code review is verifying that code ...

Modern software systems, developed using object-oriented programming languages (OOPL), often rely on relational databases (RDB) for persistent storage, leading to the object-relational impedance mismatch problem (IMP). Although Object-Relational Mapping (...

Recent work in automated program repair (APR) proposes the use of reasoning and patch validation feedback to reduce the semantic gap between the LLMs and the code under analysis. The idea has been shown to perform well for general APR, but its ...

Large language models (LLMs) have showcased remarkable skills, rivaling or even exceeding human intelligence in certain areas. Their proficiency in translation is notable, as they may replicate the nuanced, preparatory steps of human translators for high-...

LLM-based assistants, such as GitHub Copilot and ChatGPT, have the potential to generate code that fulfills a programming task described in a natural language description, referred to as a prompt. The widespread accessibility of these assistants enables ...

With software development increasingly reliant on innovative technologies, there is a growing interest in exploring the potential of generative AI tools to streamline processes and enhance productivity. In this scenario, this paper investigates the ...

Programming has been a key tool for artists and other creatives for decades, and the creative use of programming presents unique challenges, opportunities and perspectives for researchers considering how AI can be used to support coding more generally. ...

Ever since we began programming in the 1950s, there have been two diametrically opposed tendencies within computer science and software engineering: on the left side of the Glorious Throne of Alan Turing, the tendency to perfect the Art of Computer ...

Scientific software development demands robust solutions to meet the complexities of modern scientific systems. In response, we propose a paradigm-shifting Neuro-Symbolic Approach to Certified Scientific Software Synthesis. This innovative framework ...

This paper conducted a novel study to explore the capabilities of ChatGPT, a state-of-the-art LLM, in static analysis tasks such as static bug detection and false positive warning removal. In our evaluation, we focused on two types of typical and ...

Evaluating conversational assistants, such as GitHub Copilot Chat, poses a significant challenge for tool builders in the domain of Software Engineering. These assistants rely on language models and chat-based user experiences, rendering their evaluation ...

The inaugural ACM International Conference on AI-powered Software introduced the AIware Challenge, prompting researchers to explore AI-driven tools for optimizing conference programs through constrained optimization. We investigate the use of Large ...

This study presents a novel Artificial Intelligence (AI)-based approach to automate conference session scheduling that integrates Natural Language Processing (NLP) techniques. By analyzing contextual information from conference activities, this framework ...

Program creation is the process of allocating presentation slots for each paper accepted to a conference with parallel sessions. This process, generally done manually, involves intricate decision-making to align with multiple constraints and optimize ...

Frontier Large language models in 2024 are capable of performing numerous tasks, including SE ones, and are widely used to create impressive demos. However, productizing these models remains notoriously challenging. JetBrains AI Assistant is one such ...

The correctness of a program is always as good as the specification that is verified. However, writing down formal specifications is non-trivial for mainstream developers. This limits the usage of rigorous testing and verification techniques to improve ...

Digital twins, often called “virtual replicas” of their underlying systems, enable advanced system analyses during their design, development, and operation. This talk will cover how we utilized digital twins that we built with artificial intelligence ...

Data science tasks involve a complex interplay of datasets, code and code outputs for answering questions, deriving insights, or building models from data. Tasks and chosen methods may require specialized data domain or scientific domain knowledge. ...

Over a period of just about 5 years, the use of AI-based tools for software engineering has gone from being a very promising research investigation to indispensable features in modern developer environments. This talk will present AI-powered improvements ...