While unstructured merge tools rely only on textual analysis to detect and resolve conflicts, semistructured merge tools go further by partially exploiting the syntactic structure and semantics of the involved artifacts. Previous studies compare these merge approaches with respect to the number of reported conflicts, showing, for most projects and merge situations, reduction in favor of semistructured merge. However, these studies do not investigate whether this reduction actually leads to integration effort reduction (productivity) without negative impact on the correctness of the merging process (quality). To analyze that, and better understand how merge tools could be improved, in this paper we reproduce more than 30,000 merges from 50 open source projects, identifying conflicts incorrectly reported by one approach but not by the other (false positives), and conflicts correctly reported by one approach but missed by the other (false negatives). Our results and complementary analysis indicate that, in the studied sample, the number of false positives is significantly reduced when using semistructured merge. We also find evidence that its false positives are easier to analyze and resolve than those reported by unstructured merge. However, we find no evidence that semistructured merge leads to fewer false negatives, and we argue that they are harder to detect and resolve than unstructured merge false negatives. Driven by these findings, we implement an improved semistructured merge tool that further combines both approaches to reduce the false positives and false negatives of semistructured merge. We find evidence that the improved tool, when compared to unstructured merge in our sample, reduces the number of reported conflicts by half, has no additional false positives, has at least 8% fewer false negatives, and is not prohibitively slower. CCS Concepts: • General and reference → Empirical studies; • Software and its engineering → Software configuration management and version control systems;

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International audienceSoftware product lines (SPL) provide support for productivity gains through systematic reuse. Among the various quality attributes supporting these goals, modularity, stability and expressiveness of feature specifications, their composition and configuration knowledge emerge as strategic values in modern software development paradigms. This paper presents a metric-based evaluation aiming at assessing how well the chosen qualities are supported by scenario-based SPL requirements approaches. The selected approaches for this study span from type of notation (textual or graphical based), style to support variability (annotation or composition based), and specification expressiveness. They are compared using the metrics developed in a set of releases from an exemplar case study. Our major findings indicate that composition-based approaches have greater potential to support modularity and stability, and that quantification mechanisms simplify and increase expressiveness of configuration knowledge and composition specifications

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