2021/07/04 by Edward McDaid, McDaid, Edward, Sarah McDaid +1
Computer Science · Engineering · #Artificial Intelligence (cs.AI) #Composability #Computer science #D.1.2 #D.2.3 #D.2.8 #D.3.2 #D.3.3 #D.3.4 #Engineering #F.3.1 #FOS: Computer and information sciences #Formal Methods in Verification #I.2.2 #I.2.5 #Logic, programming, and type systems #Programming Languages (cs.PL) #Programming language #Range (aeronautics) #Scope (computer science) #Software #Software Engineering Research #Test (biology) #Theoretical computer science #cs.AI #cs.PL
paper · pdf · doi:10.48550/arxiv.2107.01621
published in arXiv (Cornell University) (Cornell University) · 8 pages, 9 figures
arxiv created 2021/07/04 · openalex publication_date 2021/07/04 · arxiv updated 2021/07/06 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
It is believed that mechanisms including intermediate values enable composable inductive programming (CIP) to be used to produce software of any size. We present the results of a study that investigated the relationships between program size, the number of intermediate values and the number of test cases used to specify programs using CIP. In the study 96,000 programs of various sizes were randomly generated, decomposed into fragments and transformed into test cases. The test cases were then used to regenerate new versions of the original programs using Zoea. The results show linear relationships between the number of intermediate values and regenerated program size, and between the number of test cases and regenerated program size within the size range studied. In addition, as program size increases there is increasing scope for trading off the number of test cases against the number of intermediate values and vice versa.