- author = "Leandro {Oliveira de Souza} and Eduardo {Santana de Almeida} and Paulo Anselmo {da Mota Silveira Neto} and Earl T. Barr and Justyna Petke",
- title = "Software Product Line Engineering via Software Transplantation",
- journal = "ACM Transactions on Software Engineering and Methodologies",
- year = "2024",
- month = sep,
- note = "Just Accepted",
- keywords = "genetic algorithms, genetic programming, Genetic Improvement, Software Product Lines, SPL, Software Transplantation",
- ISSN = "1049-331X",
-
URL = "
http://www.cs.ucl.ac.uk/staff/J.Petke/papers/Souza_2024_TOSEM.pdf",
-
DOI = "
doi:10.1145/3695987",
-
code_url = "
https://autotransplantation-spl.github.io/foundry.github.io/",
- size = "27 pages",
-
abstract = "Software Product Lines (SPLs) improve time-to-market,
enhance software quality, and reduce maintenance costs.
Current SPL re-engineering practices are largely manual
and require domain knowledge. Thus, adopting and, to a
lesser extent, maintaining SPLs are expensive tasks,
preventing many companies from enjoying their benefits.
To address these challenges, we introduce Foundry, an
approach using software transplantation to reduce the
manual effort of SPL adoption and maintenance. Foundry
enables integrating features across different
codebases, even code bases that are unaware that they
are contributing features to a software product line.
Each product produced by Foundry is pure code, without
variability annotation, unlike feature flags, which
eases variability management and reduces code bloat.
We realise Foundry in prodScalpel, a tool that transplants multiple organs (i.e., a set of interesting features) from donor systems into an emergent product line for codebases written in C. Given tests and light weight annotations identifying features and implantation points, prodScalpel automates feature extraction and integration. To evaluate its effectiveness, our evaluation compares feature transplantation using prodScalpel to the current state of practice: on our dataset, prodScalpel use speeds up feature migration by an average of 4.8 times when compared to current practice",
- notes = "Replaces \cite{souza2023software}",
