1,760 research outputs found
Improving Prolog Programs: Refactoring for Prolog
Refactoring is an established technique from the OO-community to restructure
code: it aims at improving software readability, maintainability and
extensibility. Although refactoring is not tied to the OO-paradigm in
particular, its ideas have not been applied to Logic Programming until now.
This paper applies the ideas of refactoring to Prolog programs. A catalogue
is presented listing refactorings classified according to scope. Some of the
refactorings have been adapted from the OO-paradigm, while others have been
specifically designed for Prolog. Also the discrepancy between intended and
operational semantics in Prolog is addressed by some of the refactorings.
In addition, ViPReSS, a semi-automatic refactoring browser, is discussed and
the experience with applying \vipress to a large Prolog legacy system is
reported. Our main conclusion is that refactoring is not only a viable
technique in Prolog but also a rather desirable one.Comment: To appear in ICLP 200
The effectiveness of refactoring, based on a compatibility testing taxonomy and a dependency graph
In this paper, we describe and then appraise a testing taxonomy proposed by van Deursen and Moonen (VD&M) based on the post-refactoring repeatability of tests. Four categories of refactoring are identified by VD&M ranging from semantic-preserving to incompatible, where, for the former, no new tests are required and for the latter, a completely new test set has to be developed. In our appraisal of the taxonomy, we heavily stress the need for the inter-dependence of the refactoring categories to be considered when making refactoring decisions and we base that need on a refactoring dependency graph developed as part of the research. We demonstrate that while incompatible refactorings may be harmful and time-consuming from a testing perspective, semantic-preserving refactorings can have equally unpleasant hidden ramifications despite their advantages. In fact, refactorings which fall into neither category have the most interesting properties. We support our results with empirical refactoring data drawn from seven Java open-source systems (OSS) and from the same analysis form a tentative categorization of code smells
Proactive Empirical Assessment of New Language Feature Adoption via Automated Refactoring: The Case of Java 8 Default Methods
Programming languages and platforms improve over time, sometimes resulting in
new language features that offer many benefits. However, despite these
benefits, developers may not always be willing to adopt them in their projects
for various reasons. In this paper, we describe an empirical study where we
assess the adoption of a particular new language feature. Studying how
developers use (or do not use) new language features is important in
programming language research and engineering because it gives designers
insight into the usability of the language to create meaning programs in that
language. This knowledge, in turn, can drive future innovations in the area.
Here, we explore Java 8 default methods, which allow interfaces to contain
(instance) method implementations.
Default methods can ease interface evolution, make certain ubiquitous design
patterns redundant, and improve both modularity and maintainability. A focus of
this work is to discover, through a scientific approach and a novel technique,
situations where developers found these constructs useful and where they did
not, and the reasons for each. Although several studies center around assessing
new language features, to the best of our knowledge, this kind of construct has
not been previously considered.
Despite their benefits, we found that developers did not adopt default
methods in all situations. Our study consisted of submitting pull requests
introducing the language feature to 19 real-world, open source Java projects
without altering original program semantics. This novel assessment technique is
proactive in that the adoption was driven by an automatic refactoring approach
rather than waiting for developers to discover and integrate the feature
themselves. In this way, we set forth best practices and patterns of using the
language feature effectively earlier rather than later and are able to possibly
guide (near) future language evolution. We foresee this technique to be useful
in assessing other new language features, design patterns, and other
programming idioms
RePOR: Mimicking humans on refactoring tasks. Are we there yet?
Refactoring is a maintenance activity that aims to improve design quality
while preserving the behavior of a system. Several (semi)automated approaches
have been proposed to support developers in this maintenance activity, based on
the correction of anti-patterns, which are `poor' solutions to recurring design
problems. However, little quantitative evidence exists about the impact of
automatically refactored code on program comprehension, and in which context
automated refactoring can be as effective as manual refactoring. Leveraging
RePOR, an automated refactoring approach based on partial order reduction
techniques, we performed an empirical study to investigate whether automated
refactoring code structure affects the understandability of systems during
comprehension tasks. (1) We surveyed 80 developers, asking them to identify
from a set of 20 refactoring changes if they were generated by developers or by
a tool, and to rate the refactoring changes according to their design quality;
(2) we asked 30 developers to complete code comprehension tasks on 10 systems
that were refactored by either a freelancer or an automated refactoring tool.
To make comparison fair, for a subset of refactoring actions that introduce new
code entities, only synthetic identifiers were presented to practitioners. We
measured developers' performance using the NASA task load index for their
effort, the time that they spent performing the tasks, and their percentages of
correct answers. Our findings, despite current technology limitations, show
that it is reasonable to expect a refactoring tools to match developer code
Improving Prolog programs: Refactoring for Prolog
Refactoring is an established technique from the object-oriented (OO)
programming community to restructure code: it aims at improving software
readability, maintainability and extensibility. Although refactoring is not
tied to the OO-paradigm in particular, its ideas have not been applied to Logic
Programming until now.
This paper applies the ideas of refactoring to Prolog programs. A catalogue
is presented listing refactorings classified according to scope. Some of the
refactorings have been adapted from the OO-paradigm, while others have been
specifically designed for Prolog. The discrepancy between intended and
operational semantics in Prolog is also addressed by some of the refactorings.
In addition, ViPReSS, a semi-automatic refactoring browser, is discussed and
the experience with applying ViPReSS to a large Prolog legacy system is
reported. The main conclusion is that refactoring is both a viable technique in
Prolog and a rather desirable one.Comment: To appear in Theory and Practice of Logic Programming (TPLP
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An empirical investigation into the impact of refactoring on regression testing
It is widely believed that refactoring improves software quality and developer’s productivity by making it easier to maintain and understand software systems. On the other hand, some believe that refactoring has the risk of functionality regression and increased testing cost. This paper investigates the impact of refactoring edits on regression tests using the version history of Java open source projects: (1) Are there adequate regression tests for refactoring in practice? (2) How many of existing regression tests are relevant to refactoring edits and thus need to be re-run for the new version? (3) What proportion of failure-inducing changes are relevant to refactorings? By using a refactoring reconstruction analysis and a change impact analysis in tandem, we investigate the relationship between the types and locations of refactoring edits identified by RefFinder and the affecting changes and affected tests identified by the FaultTracer change impact analysis. The results on three open source projects, JMeter, XMLSecurity, and ANT, show that only 22% of refactored methods and fields are tested by existing regression tests. While refactorings only constitutes 8% of atomic changes, 38% of affected tests are relevant to refactorings. Furthermore, refactorings are involved in almost a half of failed test cases. These results call for new automated regression test augmentation and selection techniques for validating refactoring edits.Electrical and Computer Engineerin
A Systematic Aspect-Oriented Refactoring and Testing Strategy, and its Application to JHotDraw
Aspect oriented programming aims at achieving better modularization for a
system's crosscutting concerns in order to improve its key quality attributes,
such as evolvability and reusability. Consequently, the adoption of
aspect-oriented techniques in existing (legacy) software systems is of interest
to remediate software aging. The refactoring of existing systems to employ
aspect-orientation will be considerably eased by a systematic approach that
will ensure a safe and consistent migration.
In this paper, we propose a refactoring and testing strategy that supports
such an approach and consider issues of behavior conservation and (incremental)
integration of the aspect-oriented solution with the original system. The
strategy is applied to the JHotDraw open source project and illustrated on a
group of selected concerns. Finally, we abstract from the case study and
present a number of generic refactorings which contribute to an incremental
aspect-oriented refactoring process and associate particular types of
crosscutting concerns to the model and features of the employed aspect
language. The contributions of this paper are both in the area of supporting
migration towards aspect-oriented solutions and supporting the development of
aspect languages that are better suited for such migrations.Comment: 25 page
Evaluation of Kermeta for Solving Graph-based Problems
Kermeta is a meta-language for specifying the structure and behavior of graphs of interconnected objects called models. In this paper,\ud
we show that Kermeta is relatively suitable for solving three graph-based\ud
problems. First, Kermeta allows the specification of generic model\ud
transformations such as refactorings that we apply to different metamodels\ud
including Ecore, Java, and Uml. Second, we demonstrate the extensibility\ud
of Kermeta to the formal language Alloy using an inter-language model\ud
transformation. Kermeta uses Alloy to generate recommendations for\ud
completing partially specified models. Third, we show that the Kermeta\ud
compiler achieves better execution time and memory performance compared\ud
to similar graph-based approaches using a common case study. The\ud
three solutions proposed for those graph-based problems and their\ud
evaluation with Kermeta according to the criteria of genericity,\ud
extensibility, and performance are the main contribution of the paper.\ud
Another contribution is the comparison of these solutions with those\ud
proposed by other graph-based tools
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