Software development has been changing rapidly. This development process can be influenced through changing developer friendly approaches. We can save time consumption and accelerate the development process if we can automatically guide programmer during software development. There are some approaches that recommended relevant code snippets and APIitems to the developer. Some approaches apply general code, searching techniques and some approaches use an online based repository mining strategies. But it gets quite difficult to help programmers when they need particular type conversion problems. More specifically when they want to adapt existing interfaces according to their expectation. One of the familiar triumph to guide developers in such situation is adapting collections and arrays through automated adaptation of object ensembles. But how does it help to a novice developer in real time software development that is not explicitly specified? In this paper, we have developed a system that works as a plugin-tool integrated with a particular Data Mining Integrated environment (DMIE) to recommend relevant interface while they seek for a type conversion situation. We have a mined repository of respective adapter classes and related APIs from where developer, search their query and get their result using the relevant transformer classes. The system that recommends developers titled automated objective ensembles (AOE plugin).From the investigation as we have ever made, we can see that our approach much better than some of the existing approaches.
Self-adaptivity allows software systems to autonomously adjust their behavior during run-time to reduce the cost complexities caused by manual maintenance. In this paper, a framework for building an external adaptation engine for self-adaptive software systems is proposed. In order to improve the quality of self-adaptive software systems, this research addresses two challenges in self-adaptive software systems. The first challenge is to provide better performance of the adaptation engine by managing the complexity of the adaptation space efficiently and the second challenge is handling run-tim…
Automated Program Repair (APR) is defined as the process of fixing a bug/defect in the source code, by an automated tool. APR tools have recently experienced promising results by leveraging state-of-the-art Neural Language Processing (NLP) techniques. APR tools such as TFix and CodeXGLUE combine text-to-text transformers with software-specific techniques are outperforming alternatives, these days. However, in most APR studies the train and test sets are chosen from the same set of projects. In reality, however, APR models are meant to be generalizable to new and different projects. Therefore, …
Software requirements traceability is a critical component of the software engineering process, enabling activities such as requirements validation, compliance verification, and safety assurance. However, the cost and effort of manually creating a complete set of trace links across natural language artifacts such as requirements, design, and test-cases can be prohibitively expensive. Researchers have therefore proposed automated link-generation solutions primarily based on information-retrieval (IR) techniques; however, these solutions have failed to deliver the accuracy needed for full adopti…
Self-adaptation approaches usually rely on closed-loop controllers that avoid human intervention from adaptation. While such fully automated approaches have proven successful in many application domains, there are situations where human involvement in the adaptation process is beneficial or even necessary. For such "human-in-the-loop" adaptive systems, two major challenges, namely transparency and controllability, have to be addressed to include the human in the self-adaptation loop. Transparency means that relevant context information about the adaptive systems and its context is represented …
Automated TEE Adaptation with LLMs: Identifying, Transforming, and Porting Sensitive Functions in Programs
School of Computing and Information Systems, Singapore Management University（新加坡管理大学计算与信息学学院）；School of Computing Science, University of Alberta（阿尔伯塔大学计算科学学院）；School of Computing and Information Technology, University of Wollongong（伍伦贡大学计算与信息技术学院）
As we develop more assistive and automated game design systems, the question of how these systems should be integrated into game development workflows, and how much adaptation may be required, becomes increasingly important. In this paper we explore the impact of software engineering decisions on the ability of an automated game design system to understand a game's codebase, generate new game code, and evaluate its work. We argue that a new approach to software engineering may be required in order for game developers to fully benefit from automated game designers.
Enhancing Cell Counting through MLOps: A Structured Approach for Automated Cell Analysis
Deep Learning Italia, Milan, Italy（Deep Learning Italia, 米兰，意大利）；Artificial Intelligence Venture Builder, London, UK（人工智能创业 builder，伦敦，英国）；Università di Bologna, Bologna, Italy（博洛尼亚大学，博洛尼亚，意大利）；Università di Bergamo, Bergamo, Italy（贝加莫大学，贝加莫，意大利）；Department of Innovative Technologies in Medicine and Dentistry, Università degli Studi G. d’Annunzio Chieti – Pescara, Chieti, Italy（创新医学与牙科技术系，切蒂-佩斯卡雷大学，切蒂，意大利）；Università degli Studi di Bari Aldo Moro, Bari, Italy（巴里阿尔多·莫罗大学，巴里，意大利）
