[SEG-staff] Research Talks Announcement

Dear all, as already mentioned, we will have the following research talks in our next SPL lecture. Tuesday, December 10, 14:15 - 16:00, Engehalde 8, Room 002. Both are highly recommended! Best, Timo *Speaker* Alexander Schultheiß (University of Paderborn and University of Bern) *Title* Decades of GNU Patch and Git Cherry-Pick: Can We Do Better? *Abstract* Patching is a fundamental software maintenance and evolution task enabling the (semi-)automated propagation of changes across different software versions. Established and widely used general-purpose patchers, such as GNU-patch and git cherry-pick, work on textual artifact representations (i.e., files) and typically rely on line numbers and contexts (i.e., surrounding unchanged text) to apply changes. This strategy often fails if source and target of a patch differ: Some required changes may be rejected, others may be applied to the wrong location; provoking cumbersome manual effort. In this paper, we study the effectiveness of commonly-used patchers, and propose a novel technique that pushes the boundaries of patch automation. First, we curate and analyze a large dataset of more than 400,000 patch scenarios (i.e., cherry picks) from 5,000 GitHub projects. Next, we examine the effectiveness of established patchers on the gathered patch scenarios, observing that patchers often fail to apply changes correctly. Third, we develop a novel general- purpose patch technique, mpatch, that utilizes a source-to-target matching to determine suitable change locations. By comparing mpatch to other patchers, we find that it can correctly apply 44% more patches automatically than other general-purpose patchers, while it also requires fewer manual fixes in cases that cannot be automated completely. Thus, mpatch considerably reduces the burden of manually fixing failed patches in practice, specifically in projects with frequent patch applications. -- *Speaker* Paul Bittner (University of Ulm and TU Braunschweig) *Title* On the Expressive Power of Languages for Static Variability *Abstract* Variability permeates software development to satisfy ever-changing requirements and mass-customization needs. A prime example is the Linux kernel, which employs the C preprocessor to specify a set of related but distinct kernel variants. To study, analyze, and verify variational software, several formal languages have been proposed. For example, the choice calculus has been successfully applied for type checking and symbolic execution of configurable software, while other formalisms have been used for variational model checking, change impact analysis, among other use cases. Yet, these languages have not been formally compared, hence, little is known about their relationships. Crucially, it is unclear to what extent one language subsumes another, how research results from one language can be applied to other languages, and which language is suitable for which purpose or domain. In this paper, we propose a formal framework to compare the expressive power of languages for static (i.e. compile-time) variability. By establishing a common semantic domain to capture the essence of explicit variability, we can formulate the basic, yet to date neglected, properties of soundness, completeness, and expressiveness for variability languages. We then prove the (un)soundness and (in)completeness of a range of existing languages, and relate their ability to express the same variational systems. We implement our framework as an extensible open source Agda library in which proofs act as correct compilers between languages or differencing algorithms. We find that most variability languages are complete, sound, and equally expressive, rendering existing and future research more broadly applicable by bridging the gaps between parallel research efforts.