Self-planning Code Generation with Large Language Models

Although large language models have demonstrated impressive ability in code generation, they are still struggling to address the complicated intent provided by humans. It is widely acknowledged that humans typically employ planning to decompose complex problems and schedule the solution steps prior to implementation. Thus we introduce planning into code generation to help the model understand complex intent and reduce the difficulty of problem solving. This paper proposes a self-planning code generation method with large language model, which consists of two phases, namely planning phase and implementation phase. Specifically, in the planning phase, the language model plans out the solution steps from the intent combined with in-context learning. Then it enters the implementation phase, where the model generates code step by step, guided by the solution steps. The effectiveness of self-planning code generation has been rigorously evaluated on multiple code generation datasets and the results have demonstrated a marked superiority over naive direct generation approaches with language model. The improvement in performance is substantial, highlighting the significance of self-planning in code generation tasks

Understanding behaviour patterns of multi-agents in digital business ecosystems: an organisational semiotics inspired framework

Digital business ecosystem (DBE) is a collaborative network of organisations, processes and technologies that collectively create value. Thus, value creation in DBEs is jointly undertaken by multiple human and digital agents. To aid appropriate apportionment of work and design of information systems, it is essential to understand behaviour of both human and digital agents. However limited attention has been paid to agents’ behaviour in the extant DBEs literature. Moreover, multi-agent research has also largely focused on technical issues while limited research exists on agents’ behaviour. As such, in this paper, we develop a framework to understand behaviour patterns of multi-agent in DBEs. This framework builds its foundation on the theoretical lens of Organisational Semiotics, a sociotechnical theory towards contribution to DBE research

Agent-Oriented Software Methodology*

Abstract: In this paper, a methodology for agent-oriented software analysis and design is proposed, which starts from a system’s organizational structure and its work mode. The main tasks of analysis are to build the models for a system’s organization structure and its work mode.to capture how roles construct the system, which problems the system is desired to solve, and which relationships are among those problems. The main tasks of design are to model agents who will play the roles and to model interactions to show how agents realize the existing work mode and solve problems. To ensure the consistency between the analysis and the design, this paper also discusses the logic relationships between varied models built at different phases, which makes it possible to check the consistency automatically.

An Online Education Approach Using Web Operation Record and Replay Techniques

Online education plays a more and more important role in the era of Internet and cloud computing, but two problems remain unsolved including MOOCs. First, most of existing online education platforms only provide teaching materials in format of ppt, pdf, video, and they seldom support education based on graphical Web applications. Second, some online education platforms may provide self-governed chatting tools or whiteboards, but they are not combined with teaching materials closely. As a result, they cannot satisfy the need for the real-time interactions based on complex teaching materials. To solve the problems above, we put forward an online education approach using Web operation record and replay techniques, and implement online synchronized education and real-time interactions between teachers and students. Moreover, we develop a supporting tool OSEP for the approach. In the case study, we describe three education scenarios, which verify that the approach supports not only personal learning by tutorials and wizards, but also online in-class real-time collaborative learning. ? 2014 IEEE.EICPCI-S(ISTP)

A Self-Adaptive Mechanism for Software Configuration Based on Case-based Reasoning and Policy

Self-adaptive software expects the system to adapt its behaviors to environment changes. One main challenge is how to improve self-adaptation efficiency. In this paper case-based reasoning method is used to support the self-configuration case reuse which results in the configuration efficiency improvement. If there is no case to reuse directly, the policy-based technique is utilized to achieve the self-configuring plan. Moreover, the new generated configuration plan will be stored to the case repository for later reuse. This self-adaptive mechanism is more flexible and efficient which also is applicable to the self-optimizing, self-healing and selfprotecting etc. It has proved to be available and very helpful in software system self-configuration. ? 2010 IEEE.EI

Interorgan communication in neurogenic heterotopic ossification: the role of brain-derived extracellular vesicles

Abstract Brain-derived extracellular vesicles participate in interorgan communication after traumatic brain injury by transporting pathogens to initiate secondary injury. Inflammasome-related proteins encapsulated in brain-derived extracellular vesicles can cross the blood‒brain barrier to reach distal tissues. These proteins initiate inflammatory dysfunction, such as neurogenic heterotopic ossification. This recurrent condition is highly debilitating to patients because of its relatively unknown pathogenesis and the lack of effective prophylactic intervention strategies. Accordingly, a rat model of neurogenic heterotopic ossification induced by combined traumatic brain injury and achillotenotomy was developed to address these two issues. Histological examination of the injured tendon revealed the coexistence of ectopic calcification and fibroblast pyroptosis. The relationships among brain-derived extracellular vesicles, fibroblast pyroptosis and ectopic calcification were further investigated in vitro and in vivo. Intravenous injection of the pyroptosis inhibitor Ac-YVAD-cmk reversed the development of neurogenic heterotopic ossification in vivo. The present work highlights the role of brain-derived extracellular vesicles in the pathogenesis of neurogenic heterotopic ossification and offers a potential strategy for preventing neurogenic heterotopic ossification after traumatic brain injury. Brain-derived extracellular vesicles (BEVs) are released after traumatic brain injury. These BEVs contain pathogens and participate in interorgan communication to initiate secondary injury in distal tissues. After achillotenotomy, the phagocytosis of BEVs by fibroblasts induces pyroptosis, which is a highly inflammatory form of lytic programmed cell death, in the injured tendon. Fibroblast pyroptosis leads to an increase in calcium and phosphorus concentrations and creates a microenvironment that promotes osteogenesis. Intravenous injection of the pyroptosis inhibitor Ac-YVAD-cmk suppressed fibroblast pyroptosis and effectively prevented the onset of heterotopic ossification after neuronal injury. The use of a pyroptosis inhibitor represents a potential strategy for the treatment of neurogenic heterotopic ossification