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Register a new userRetrieval Augmented Code Generation and Summarization
استرجاع توليد التعليمات البرمجية المعزز
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يكتب مطورو البرمجيات الكثير من التعليمات البرمجية المصدر والوثائق أثناء تطوير البرمجيات. جوهريا، غالبا ما يتذكر المطورون أجزاء من شفرة المصدر أو ملخصات التعليمات البرمجية التي كتبوها في الماضي أثناء تنفيذ البرامج أو توثيقها. لتقليل رمز المطور أو سلوك الجيل الموجز، نقترح إطارا معدليا استرجاعا، ريدكودر، الذي يسترد الكود أو الملخصات ذات الصلة من قاعدة بيانات استرجاع ويوفر لهم كملحق لجيل التعليمات أو نماذج التلخيص. ريدكودر لديه زوجين من التفرد. أولا، إنه يمتد تقنية استرجاع حديثة كثيفة الاستخدام للبحث عن التعليمات البرمجية أو الملخصات ذات الصلة. ثانيا، يمكن أن تعمل مع قواعد بيانات استرجاع تشمل Unimodal (رمز فقط أو وصف اللغة الطبيعية) أو مثيلات BIMODAL (أزواج الكود الوصف). نقوم بإجراء تجارب وتحليل مكثف على مجموعة بيانات قياسية لتوليد التعليمات البرمجية والتلخيص في جاوة وبيرثون، والنتائج الواعدة تؤيد فعالية الإطار المعزز المقترح لاسترجاعنا.
Software developers write a lot of source code and documentation during software development. Intrinsically, developers often recall parts of source code or code summaries that they had written in the past while implementing software or documenting them. To mimic developers' code or summary generation behavior, we propose a retrieval augmented framework, REDCODER, that retrieves relevant code or summaries from a retrieval database and provides them as a supplement to code generation or summarization models. REDCODER has a couple of uniqueness. First, it extends the state-of-the-art dense retrieval technique to search for relevant code or summaries. Second, it can work with retrieval databases that include unimodal (only code or natural language description) or bimodal instances (code-description pairs). We conduct experiments and extensive analysis on two benchmark datasets of code generation and summarization in Java and Python, and the promising results endorse the effectiveness of our proposed retrieval augmented framework.
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