4,233 research outputs found
On the Effect of Semantically Enriched Context Models on Software Modularization
Many of the existing approaches for program comprehension rely on the
linguistic information found in source code, such as identifier names and
comments. Semantic clustering is one such technique for modularization of the
system that relies on the informal semantics of the program, encoded in the
vocabulary used in the source code. Treating the source code as a collection of
tokens loses the semantic information embedded within the identifiers. We try
to overcome this problem by introducing context models for source code
identifiers to obtain a semantic kernel, which can be used for both deriving
the topics that run through the system as well as their clustering. In the
first model, we abstract an identifier to its type representation and build on
this notion of context to construct contextual vector representation of the
source code. The second notion of context is defined based on the flow of data
between identifiers to represent a module as a dependency graph where the nodes
correspond to identifiers and the edges represent the data dependencies between
pairs of identifiers. We have applied our approach to 10 medium-sized open
source Java projects, and show that by introducing contexts for identifiers,
the quality of the modularization of the software systems is improved. Both of
the context models give results that are superior to the plain vector
representation of documents. In some cases, the authoritativeness of
decompositions is improved by 67%. Furthermore, a more detailed evaluation of
our approach on JEdit, an open source editor, demonstrates that inferred topics
through performing topic analysis on the contextual representations are more
meaningful compared to the plain representation of the documents. The proposed
approach in introducing a context model for source code identifiers paves the
way for building tools that support developers in program comprehension tasks
such as application and domain concept location, software modularization and
topic analysis
A Generic Module System forWeb Rule Languages: Divide and Rule
An essential feature in practically usable programming languages is
the ability to encapsulate functionality in reusable modules. Modules make large
scale projects tractable by humans. For Web and Semantic Web programming,
many rule-based languages, e.g. XSLT, CSS, Xcerpt, SWRL, SPARQL, and RIF
Core, have evolved or are currently evolving. Rules are easy to comprehend
and specify, even for non-technical users, e.g. business managers, hence easing
the contributions to the Web. Unfortunately, those contributions are arguably
doomed to exist in isolation as most rule languages are conceived without modularity,
hence without an easy mechanism for integration and reuse. In this paper
a generic module system applicable to many rule languages is presented. We
demonstrate and apply our generic module system to a Datalog-like rule language,
close in spirit to RIF Core. The language is gently introduced along the
EU-Rent use case. Using the Reuseware Composition Framework, the module
system for a concrete language can be achieved almost for free, if it adheres to
the formal notions introduced in this paper
Remodularization Analysis Using Semantic Clustering
International audienceIn this paper, we report an experience on using and adapting Semantic Clustering to evaluate software remodularizations. Semantic Clustering is an approach that relies on information retrieval and clustering techniques to extract sets of similar classes in a system, according to their vocabularies. We adapted Semantic Clustering to support remodularization analysis. We evaluate our adaptation using six real-world remodularizations of four software systems. We report that Semantic Clustering and conceptual metrics can be used to express and explain the intention of the architects when performing common modularization operators, such as module decomposition
Reify Your Collection Queries for Modularity and Speed!
Modularity and efficiency are often contradicting requirements, such that
programers have to trade one for the other. We analyze this dilemma in the
context of programs operating on collections. Performance-critical code using
collections need often to be hand-optimized, leading to non-modular, brittle,
and redundant code. In principle, this dilemma could be avoided by automatic
collection-specific optimizations, such as fusion of collection traversals,
usage of indexing, or reordering of filters. Unfortunately, it is not obvious
how to encode such optimizations in terms of ordinary collection APIs, because
the program operating on the collections is not reified and hence cannot be
analyzed.
We propose SQuOpt, the Scala Query Optimizer--a deep embedding of the Scala
collections API that allows such analyses and optimizations to be defined and
executed within Scala, without relying on external tools or compiler
extensions. SQuOpt provides the same "look and feel" (syntax and static typing
guarantees) as the standard collections API. We evaluate SQuOpt by
re-implementing several code analyses of the Findbugs tool using SQuOpt, show
average speedups of 12x with a maximum of 12800x and hence demonstrate that
SQuOpt can reconcile modularity and efficiency in real-world applications.Comment: 20 page
A Case for Custom, Composable Composition Operators
Programming languages typically support a fixed set of com- position operators, with fixed semantics. This may impose limits on software designers, in case a desired operator or semantics are not supported by a language, resulting in suboptimal quality characteristics of the designed software system. We demonstrate this using the well-known State design pattern, and propose the use of a composition infrastructure that allows the designer to define custom, composable composition operators. We demonstrate how this approach improves several quality factors of the State design pattern, such as reusability and modularity, while taking a reason- able amount of effort to define the necessary pattern-related code
Composing Aspects at Shared Join Points
Aspect-oriented languages provide means to superimpose aspectual behavior on a given set of join points. It is possible that not just a single, but several units of aspectual behavior need to be superimposed on the same join point. Aspects that specify the superimposition of these units are said to "share" the same join point. Such shared join points may give rise to issues such as\ud
determining the exact execution order and the dependencies among the aspects. In this paper, we present a detailed analysis of the problem, and identify a set of requirements upon mechanisms for composing aspects at shared join points. To address the identified issues, we propose a general and declarative model for defining constraints upon the possible compositions of aspects at a shared join point. Finally, by using an extended notion of join points, we show how concrete aspectoriented programming languages, particularly AspectJ and Compose*, can adopt the proposed model
Searchâbased model transformations
Model transformations are an important cornerstone of modelâdriven engineering, a discipline which facilitates the abstraction of relevant information of a system as models. The success of the final system mainly depends on the optimization of these models through model transformations. Currently, the application of transformations is realized either by following the applyâasâlongâasâpossible strategy or by the provision of explicit rule orchestrations. This implies two main limitations. First, the optimization objectives are implicitly hidden in the transformation rules and their orchestration. Second, manually finding the best orchestration for a particular scenario is a major challenge due to the high number of possible combinations.
To overcome these limitations, we present a novel framework that builds on the nonâintrusive integration of optimization and model transformation technologies. In particular, we formulate the transformation orchestration task as an optimization problem, which allows for the efficient exploration of the transformation space and explication of the transformation objectives. Our generic framework provides several search algorithms and guides the user in providing a proper search configuration. We present different instantiations of our framework to demonstrate its feasibility, applicability, and benefits using several case studiesEuropean Commission ICT Policy Support Programme 317859Ministerio de Economia y Competitividad TIN2015-70560-RJunta de AndalucĂa P10-TIC-5960Junta de AndalucĂa P12-TIC-186
- âŠ