Quantifying the Impact on Software Complexity of Composable Inductive Programming using Zoea
This addresses the issue of high software complexity for developers and organizations, suggesting that programming languages themselves are a major contributor, though the study is incremental as it builds on existing anecdotal evidence with quantitative metrics.
The paper tackled the problem of quantifying software complexity by comparing programs written in the Zoea language (using composable inductive programming) with equivalent programs in conventional languages, finding that Zoea programs have approximately 50% lower complexity while being similar in size.
Composable inductive programming as implemented in the Zoea programming language is a simple declarative approach to software development. At the language level it is evident that Zoea is significantly simpler than all mainstream languages. However, until now we have only had anecdotal evidence that software produced with Zoea is also simpler than equivalent software produced with conventional languages. This paper presents the results of a quantitative comparison of the software complexity of equivalent code implemented in Zoea and also in a conventional programming language. The study uses a varied set of programming tasks from a popular programming language chrestomathy. Results are presented for relative program complexity using two established metrics and also for relative program size. It was found that Zoea programs are approximately 50% the complexity of equivalent programs in a conventional language and on average equal in size. The results suggest that current programming languages (as opposed to software requirements) are the largest contributor to software complexity and that significant complexity could be avoided through an inductive programming approach.