Programming in Natural Language: Building Algorithms from Human Descriptions

Our work is where the Software Engineering meets the
Human Computer Interaction and the End User Programming
to aim for a major breakthrough by making machines programmable
in ordinary and unrestricted language. In this paper,
we provide a solution on how new algorithms can be recognized
and learned from human descriptions. Our focus is to improve
the interaction between humans and machines and enable the end
user to instruct programmable devices, without having to learn a
programming language. In a test-driven development, we created
a platform that allows users to manipulate spreadsheet data by
using natural language. Therefore, the system (i) enables end
users to give instructions step-by-step, to avoid the complexity
in full descriptions and give directly feedback of success (ii)
creates an abstract meta model for user input during the linguistic
analysis and (iii) independently interprets the meta model to
code sequences that contain loops, conditionals, and statements.
The context then places the recognized program component
in the history. In this way, an algorithm is generated in an
interactive process. One of the result can be the code sequence
... mehr
for algorithm, like well-known selection sort. We present a
series of ontology structures for matching instructions to declare
variables, loop, make decisions, etc. Furthermore, our system
asks clarification questions when the human user is ambiguous.
During the evaluation, 11 undergraduate students were asked to
solve tasks by using natural language, and describe algorithms
in three classes of complexity. Overall, the system was able to
transform 60% of the user statements into code. Far from perfect,
this research might lead to fundamental changes in computer
use. Rather than merely consuming software, end users of the
ever-increasing variety of digital devices could develop their own
programs, potentially leading to novel, highly personalized, and
plentiful solutions.