Analysis of Feature Models Using Alloy: A Survey

Feature Models (FMs) are a mechanism to model variability among a family of closely related software products, i.e. a software product line (SPL). Analysis of FMs using formal methods can reveal defects in the specification such as inconsistencies that cause the product line to have no valid products. A popular framework used in research for FM analysis is Alloy, a light-weight formal modeling notation equipped with an efficient model finder. Several works in the literature have proposed different strategies to encode and analyze FMs using Alloy. However, there is little discussion on the relative merits of each proposal, making it difficult to select the most suitable encoding for a specific analysis need. In this paper, we describe and compare those strategies according to various criteria such as the expressivity of the FM notation or the efficiency of the analysis. This survey is the first comparative study of research targeted towards using Alloy for FM analysis. This review aims to identify all the best practices on the use of Alloy, as a part of a framework for the automated extraction and analysis of rich FMs from natural language requirement specifications.Comment: In Proceedings FMSPLE 2016, arXiv:1603.0857

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

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

Reflective and relativistic refactoring with feature-awareness

Refactoring is a core technology in modern software development. It is central to popular software design movements, such as Extreme Programming [23] and Agile software development [91], and all major Integrated Development Environments (IDEs) today offer some form of refactoring support. Despite this, refactoring engines have languished behind research. Modern IDEs offer no means to sequence refactorings to automate program changes. Further, current refactoring engines exhibit problems of speed and expressivity, which makes writing composite refactorings such as design patterns infeasible. Even worse, existing refactoring tools for Object-Oriented languages are unaware of configurations in Software Product Lines (SPLs) codebases. With this motivation in mind, this dissertation makes three contributions to address these issues: First, we present the Java API library, called R2, to script Eclipse refactorings to retrofit design patterns into existing programs. We encoded 18 out of 23 design patterns described by Gang-of-Four [57] as R2 scripts and explain why the remaining refactorings are inappropriate for refactoring engines. R2 sheds light on why refactoring speed and expressiveness are critical issues for scripting. Second, we present a new Java refactoring engine, called R3, that addresses an Achilles heel in contemporary refactoring technology, namely scripting performance. Unlike classical refactoring techniques that modify Abstract Syntax Trees (ASTs), R3 refactors programs by rendering ASTs via pretty printing. AST rendering never changes the AST; it only displays different views of the AST/program. Coupled with new ways to evaluate refactoring preconditions, R3 increases refactoring speed by an order of magnitude over Eclipse and facilitates computing views of a program where the original behavior is preserved. Third, we provide a feature-aware refactoring tool, called X15, for SPL codebases written in Java. X15 takes advantage of R3's view rendering to implement a projection technology in Feature-Oriented Software Development, which produces subprograms of the original SPL by hiding unneeded feature code. X15 is the first feature-aware refactoring tool for Java that implements a theory of refactoring feature modules, and allows users to edit and refactor SPL programs via “views”. In the most demanding experiments, X15 barely runs a second slower than R3, giving evidence that refactoring engines for SPL codebases can indeed be efficient.Computer Science

Consolidation of Customized Product Copies into Software Product Lines

In software development, project constraints lead to customer-specific variants by copying and adapting the product. During this process, modifications are scattered all over the code. Although this is flexible and efficient in the short term, a Software Product Line (SPL) offers better results in the long term, regarding cost reduction, time-to-market, and quality attributes. This book presents a novel approach named SPLevo, which consolidates customized product copies into an SPL

Consolidation of Customized Product Copies into Software Product Lines

Copy-based customization is a widespread technique to serve individual customer needs with existing software solutions. To cope with long term disadvantages resulting from this practice, this dissertation developed an approach to support the consolidation of such copies into a Software Product Line with a future-compliant product base providing managed variability