Differencing and merging of architectural views

Abi-Antoun, Marwan; Aldrich, Jonathan; Nahas, Nagi; Schmerl, Bradley; Garlan, David

doi:10.1007/s10515-007-0023-3

Cited by 28 publications

(16 citation statements)

References 43 publications

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“…NP includes P but whether P equals NP (i.e. N P ⊂ P ) is still an open question (Cook (1971)) and one of the main unsolved problems in mathematics 5 . The complexity class NP also includes the set of NP-complete (NPC) decision problems (Garey and Johnson (1979a)) which can be informally presented as the hardest problems in NP.…”

Section: Hard Problems and Meta-heuristicsmentioning

confidence: 99%

“…Research work on graph matching is very active and multi-disciplinary as graphs to be matched can represent images (Toshev et al (2007)), molecules (Wang et al (2004)), software artifacts (Abi-Antoun et al (2008)) etc. Formulations of the problem and proposed algorithms are manifold.…”

Section: Graph Matching In Research Literaturementioning

confidence: 99%

“…Node information can be exploited if a dissimilarity function or matrix is provided for the nodes. The objective function can thus 5 When looking for a common partial subgraph, maximizing the number of vertices is a trivial problem. The number of edges is the only interesting option and this explains the occasional confusion of the MCPS problem with the Maximum Common Edge Subgraph (MCES) problem integrate nodes and the optimal matching will contain not only edges with similar weights, but also vertices with similar labels.…”

Section: Maximum Common Partial Subgraph (Mcps)mentioning

confidence: 99%

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Approximate Graph Matching in Software Engineering

Kpodjedo

2009

2009 16th Working Conference on Reverse Engineering

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Graph representations are among the most common and effective ways to model all kinds of natural or human-made objects. Once two objects or problems have been represented as graphs (i.e. as collections of objects possibly connected by pairwise relations), their comparison is a fundamental question in many different applications and is often addressed using graph matching. The work presented in this document investigates approximate graph matching techniques and their application in software engineering, notably as efficient ways to retrieve the evolution through time of software artifacts. The research work we carried involves three distinct but related aspects. First, we consider approximate graph matching problems within the Error-Tolerant Graph Matching framework, and propose a tabu search technique initialized with local structural similarity measures. Second, we address the matching of software artifacts, such as class diagrams, and propose new concepts able to integrate efficiently the lexical information, found in typical diagrams, to our tabu search. Third, based on matchings obtained from the application of our approach to subsequent class diagrams, we proposed new design evolution metrics and assessed their usefulness in defect prediction models. The following paragraphs detail each of those three aspects.Approximate Graph Matching Many practical problems can be modeled as approximate graph matching (AGM) problems in which the goal is to find a "good" matching between two objects represented as graphs. Unfortunately, existing literature on AGM does not propose generic techniques readily usable in research areas other than image processing and biochemistry. To address this situation, we tackled in a generic way, the AGM problems. For this purpose, we first select, out of the possible formulations, the Error Tolerant Graph Matching (ETGM) framework, which is able to model most AGM formulations. Given that AGM problems are generally NP-hard, we based our resolution approach on meta-heuristics, given the demonstrated efficiency of this family of techniques on (NP-)hard problems. Our approach avoids as much as possible assumptions about graphs to be matched and tries to make the best out of basic graph features such as node connectivity and edge types. Consequently, the proposal is a local search technique using new node similarity measures derived from simple structural information. The proposed technique was devised as follows. First, we observed and empirically validated that initializing a local search with a very small subset of "correct" node matches is enough to get excellent results. Thus, instead of directly trying to correctly match all nodes and edges from two graphs, one could focus on correctly matching a few nodes. Second, in order to retrieve such node matches, we resorted to the concept of local node similarity which consists in analyzing viii nodes' neighborhoods to assess for each possible node match the likelihood of its inclusion in a good matching. We investigated many ways of c...

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Section: Hard Problems and Meta-heuristicsmentioning

confidence: 99%

Section: Graph Matching In Research Literaturementioning

confidence: 99%

Section: Maximum Common Partial Subgraph (Mcps)mentioning

confidence: 99%

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Approximate Graph Matching in Software Engineering

Kpodjedo

2009

2009 16th Working Conference on Reverse Engineering

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“…To improve the precision of the structural comparison, the base architectural model has types and properties [6]. A Port that provides services has type ProvideT, and a Port that uses services has type UseT.…”

Section: Architectural Descriptionmentioning

confidence: 99%

“…Also, SCHOLIA leverages our prior structural comparison algorithm [6] for the architectural comparisons in Section 7. SCHOLIA computes conformance metrics to help managers track architectural conformance over time, and derives traceability information that allows the architect to effectively trace architectural violations to code.…”

Section: Introductionmentioning

confidence: 99%

Static extraction and conformance analysis of hierarchical runtime architectural structure using annotations

Abi-Antoun

Aldrich

2009

SIGPLAN Not.

Self Cite

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An object diagram makes explicit the object structures that are only implicit in a class diagram. An object diagram may be missing and must extracted from the code. Alternatively, an existing diagram may be inconsistent with the code, and must be analyzed for conformance with the implementation. One can generalize the global object diagram of a system into a runtime architecture which abstracts objects into components, represents how those components interact, and can decompose a component into a nested sub-architecture.A static object diagram represents all objects and interobject relations possibly created, and is recovered by static analysis of a program. Existing analyses extract static object diagrams that are non-hierarchical, do not scale, and do not provide meaningful architectural abstraction. Indeed, architectural hierarchy is not readily observable in arbitrary code. Previous approaches used breaking language extensions to specify hierarchy and instances in code, or used dynamic analyses to extract dynamic object diagrams that show objects and relations for a few program runs.Typecheckable ownership domain annotations use existing language support for annotations and specify in code object encapsulation, logical containment and architectural tiers. These annotations enable a points-to static analysis to extract a sound global object graph that provides architectural abstraction by ownership hierarchy and by types, where architecturally significant objects appear near the top of the hierarchy and data structures are further down.Another analysis can abstract an object graph into a built runtime architecture. Then, a third analysis can compare the built architecture to a target, analyze and measure their structural conformance, establish traceability between the two and identify interesting differences.

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Configurable three‐way model merging

Sharbaf

Zamani

2020

Softw Pract Exp

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SummarySoftware development is a collaborative activity that requires teams of software engineers to cooperate and work in parallel on versions of models. However, model management techniques such as model differencing, merging, and versioning have turned out to be difficult challenges, due to the complexity of operations and graph‐like nature of models. Therefore, a well‐developed support for model merging process, as well as conflict management, is highly desired. This paper presents a novel process for model merging, called the Epsilon‐based Three‐way Merging Process (E3MP) process. Model merging is a significant problem where there are different versions of a system model amongst modeler teams. E3MP includes three components implemented into the Epsilon framework. First, modelers can define domain‐specific rules that customize the merging process. Second, E3MP enables an automated method for syntactic and semantic conflict detection amongst different versions of the system model. Third, E3MP puts forward a pattern‐based approach for conflict resolution. We applied two generic benchmarks to assess conflict detection and resolution capabilities of our approach and carried out an initial scalability evaluation for the model merge with large models and large change sets. The results of our experiments revealed that the proposed process allows generating consistent and semantically correct merged models.

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Differencing and merging of architectural views

Abstract: Abstract

Cited by 28 publications

References 43 publications

Approximate Graph Matching in Software Engineering

Approximate Graph Matching in Software Engineering

Static extraction and conformance analysis of hierarchical runtime architectural structure using annotations

Configurable three‐way model merging

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