Abstract: A semiconductor structure is disclosed including a semiconductor substrate having two or more fins. The semiconductor structure includes a recessed gate structure having opposing sidewalls located over one of the fins. The semiconductor structure includes a gate spacer disposed on the opposing sidewalls of the recessed gate structure. The semiconductor structure includes a source/drain region disposed between adjacent gate spacers. The semiconductor structure includes a first conductive material disposed on the source/drain region and an interlevel dielectric layer disposed on a top surface of the semiconductor structure defining an opening therein to an exposed top surface of the first conductive material. A width of an upper portion of the opening is greater than the width of the lower portion of the opening. The lower portion of opening is aligned with the first conductive material. The semiconductor structure includes a second conductive material disposed in the opening.

Abstract: A method, system and computer program product for determining API pricing. Consumption parameters are identified using a supervised learning model. The API consumption parameters refer to any parameters that can be used to describe an API (functionality or otherwise) and can be used to compare other comparable APIs in similar domains provided by other providers. Furthermore, reference pricing is determined using machine learning using the identified API consumption parameters. Additionally, the API price is determined dynamically using the identified API consumption parameters and the determined reference pricing. An API pricing score is then derived for the API price using the supervised learning model. The API price is selected as the suggested price for the API in response to the API pricing score exceeding a threshold value. In this manner, an API price is established that reflects the true value of the API assessed by the API consumer.