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In this paper, we delve into the advancement of domain-specific LargeLanguage Models (LLMs) with a focus on their application in softwaredevelopment. We introduce DevAssistLlama, a model developed through instructiontuning, to assist developers in processing software-related natural languagequeries. This model, a variant of instruction tuned LLM, is particularly adeptat handling intricate technical documentation, enhancing developer capabilityin software specific tasks. The creation of DevAssistLlama involvedconstructing an extensive instruction dataset from various software systems,enabling effective handling of Named Entity Recognition (NER), RelationExtraction (RE), and Link Prediction (LP). Our results demonstrateDevAssistLlama's superior capabilities in these tasks, in comparison with othermodels including ChatGPT. This research not only highlights the potential ofspecialized LLMs in software development also the pioneer LLM for this domain.

Redefining Developer Assistance: Through Large Language Models in Software Ecosystem