Section: New Results

Cycles and dependencies

Participants : Stéphane Ducasse [Correspondant] , Nicolas Anquetil, Muhammad Bhatti.

OZONE: Layer Identification in the presence of Cyclic Dependencies A layered software architecture helps understanding the role of software entities (e.g., packages or classes) in a system and hence, the impact of changes on these entities. However, the computation of an optimal layered organization in the presence of cyclic dependencies is difficult. We develop an approach that (i) provides a strategy supporting the automated detection of cyclic dependencies, (ii) proposes heuristics to break cyclic dependencies, and (iii) computes an organization of software entities in multiple layers even in presence of cyclic dependencies. Our approach performs better than the other existing approaches in terms of accuracy and interactivity, it supports human inputs and constraints. We compare this approach to existing solutions and apply it on two large software systems to identify package layers. The results are manually validated by software engineers of the two systems [12] .

Efficient Retrieval and Ranking of Undesired Package Cycles in Large Software Systems Many design guidelines state that a software system architecture should avoid cycles between its packages. Yet such cycles appear again and again in many programs. We believe that the existing approaches for cycle detection are too coarse to assist developers to remove cycles from their programs. We design an efficient algorithm that performs a fine-grained analysis of cycles among application packages. In addition, we define multiple metrics to rank cycles by their level of undesirability, prioritizing cycles that are the more undesired by developers. We compare these multiple ranking metrics on four large and mature software systems in Java and Smalltalk [14] .

Resolving cyclic dependencies between packages with Enriched Dependency Structural Matrix Dependency Structural Matrix (DSM) is an approach originally developed for process optimization. It has been successfully applied to identify software dependencies among packages and subsystems. A number of algorithms have been proposed to compute the matrix so that it highlights patterns and problematic dependencies between subsystems. However, existing DSM implementations often miss important information to fully support reengineering effort. For example, they do not clearly qualify and quantify problematic relationships, information that is crucial to support remediation tasks. We propose Enriched Dependency Structural Matrix (eDSM), which provides small multiple views and micro-macro readings by adding fine-grained information in each cell of the matrix. Each cell is enriched with contextual information about (i) the type of dependencies (inheritance, class reference, etc.), (ii) the proportion of referencing entities, (iii) the proportion of referenced entities. We distinguish independent cycles and stress potentially simple fixes for cycles using coloring information. This work is language independent and has been implemented on top of the Moose software analysis platform.We improved the cell content information view based on user feedback and performed multiple validations: two different case studies on Moose and Seaside software; one user study for validating eDSM as a usable approach for developers. Solutions to problems identified with eDSM have been performed and retrofitted in analyzed software [13] .