Novel Natural Language Summarization of Program Code via Leveraging Multiple Input Representations

The lack of description of a given program code acts as a big hurdle to those developers new to the code base for its understanding. To tackle this problem, previous work on code summarization, the task of automatically generating code description given a piece of code reported that an auxiliary learning model trained to produce API (Application Programming Interface) embeddings showed promising results when applied to a downstream, code summarization model. However, different codes having different summaries can have the same set of API sequences. If we train a model to generate summaries given an API sequence, the model will not be able to learn effectively. Nevertheless, we note that the API sequence can still be useful and has not been actively utilized. This work proposes a novel multi-task approach that simultaneously trains two similar tasks: 1) summarizing a given code (code to summary), and 2) summarizing a given API sequence (API sequence to summary). We propose a novel code-level encoder based on BERT capable of expressing the semantics of code, and obtain representations for every line of code. Our work is the first code summarization work that utilizes a natural language-based contextual pre-trained language model in its encoder. We evaluate our approach using two common datasets (Java and Python) that have been widely used in previous studies. Our experimental results show that our multi-task approach improves over the baselines and achieves the new state-of-the-art.

Agricultural Policies For Tomatoes In Syria by Using Policy Analysis Matrix ( PAM)

Policy Analysis Matrix (PAM) is a modern method to analyze the polices, it is important to check the net effects of interferences government polices in all commodities affluence steps. This helps in measuring the efficiency of these polices, for achieving the main objectives, and to evaluate their effects on the producers, consumers, and the whole economy. Policy Analysis Matrix (PAM) depends on the farm budget, that based on returns and costs, these cost divided to tradable inputs and domestic resources. The analysis studied two kind of tomatoes farming system, open summer tomatoes in Dara’a Directorate, and tomatoes under plastic houses in Tortuous Directorate.

Production Functions of Vegetables grown under Plastic Houses in High Lands in Jordan

The research aimed to recognize the optimal level of Inputs used for vegetables grown under plastic houses in highlands. These vegetables included cucumber in first and second sowing, green beans, and sweet pepper. To realize this objective, production function analysis was used for representative sample of farmers in the area.