Implementing Feature Variability for Models and Code with Projectional Language Workbenches

Abstract Product line engineering deals with managing and implementing the variability among a set of related products. We distinguish between two kinds of variability: configuration and customization. Customization variability can be described using programming language code or creative construction DSLs, whereas configuration variability is described using configuration based approaches, such as feature models. Many product lines have both kinds of variability, and they need to be integrated efficiently. This paper describes an approach for product line engineering using projectional language workbenches. These represent code and models with the same fundamental technology, enabling the mixing of models and code. They make the tight integration between several domain-specific languages possible and simple. Since they can store arbitrary information in models, it is possible to overlay configuration variability over customization variability (i.e. apply feature model-based configuration to code and models). Because of the projectional approach to editing, programs can be shown with or without the dependencies on feature models, they can even be rendered (and edited) for a specific variant. This approach leads to highly integrated and productive tools for product line development. The paper explains the approach, outlines the implementation of a prototype tool based on Jetbrains MPS and illustrates the benefits using a small product line for embedded systems

Cross-language program analysis for dynamic web applications

Web applications have become one of the most important and prevalent types of software. In modern web applications, the display of any web page is usually an interplay of multiple languages and involves code execution at different locations (the server side, the database side, and the client side). These characteristics make it hard to write and maintain web applications. Much of the existing research and tool support often deals with one single language and therefore is still limited in addressing those challenges. To fill in this gap, this dissertation is aimed at developing an infrastructure for cross-language program analysis for dynamic web applications to support creating reliable and robust web applications with higher quality and lower costs. To reach that goal, we have developed the following research components. First, to understand the client-side code that is embedded in the server-side code, we develop an output-oriented symbolic execution engine that approximates all possible outputs of a server-side program. Second, we use variability-aware parsing, a technique recently developed for parsing conditional code in software product lines, to parse those outputs into a compact tree representation (called VarDOM) that represents all possible DOM variants of a web application. Third, we leverage the VarDOM to extract semantic information from the server-side code. Specifically, we develop novel concepts, techniques, and tools (1) to build call graphs for embedded client code in different languages, (2) to compute cross-language program slices, and (3) to compute a novel test coverage criterion called output coverage that aids testers in creating effective test suites for detecting output-related bugs. The results have been demonstrated in a wide range of applications for web programs such as IDE services, fault localization, bug detection, and testing

Generative und Merkmal-orientierte Entwicklung von Software-Produktlinien mit noninvasiven Frames

Frames sind parametrisierte Elemente zur Erzeugung von Programmen in einer beliebigen Zielprogrammiersprache. Ihre Handhabung ist einfach und schnell zu erlernen. Allerdings findet bei Verwendung von Frames eine “Verunreinigung” des Programmcodes, der als Basis für die Generatorentwicklung dient, mit Befehlen der Generatorsprache statt. Dies erschwert die Weiterverwendung der gewohnten Entwicklungsumgebung für die Zielprogrammiersprache. Eine eventuelle Weiterentwicklung der Programmbasis muss anschließend in Form von Frames erfolgen. Im Rahmen dieser Arbeit erfolgt die Beschreibung noninvasiver Frames, bei denen Informationen zur Position der Frames getrennt vom Programmcode aufbewahrt werden. Ihre Vermischung erfolgt in einem separaten Schritt zur Darstellung oder zur eigentlichen Codeerzeugung. Der Prozess der Generatorentwicklung auf der Basis noninvasiver Frames passt sich gut in die Prozesse von Merkmal-orientierter (FOSD) und Generativer Softwareentwicklung (GSE) ein, weil noninvasive Frames die automatisierte Prüfung aller mit dem Generator erzeugbaren Programme hinsichtlich Syntax und bestimmter semantischer Eigenschaften unterstützen und die Generierung durch Auswahl der gewünschten Programmeigenschaften ermöglichen. Die Machbarkeit der Entwicklung von Softwaregeneratoren mit noninvasiven Frames wird anhand zweier Fallstudien demonstriert

Extending Type Inference to Variational Programs

Through the use of conditional compilation and related tools, many software projects can be used to generate a huge number of related programs. The problem of typing such variational software is difficult. The brute-force strategy of generating all variants and typing each one individually is (1) usually infeasible for efficiency reasons and (2) produces results that do not map well to the underlying variational program. Recent research has focused mainly on efficiency and addressed only the problem of type checking. In this work we tackle the more general problem of variational type inference and introduce variational types to represent the result of typing a variational program. We introduce the variational lambda calculus (VLC) as a formal foundation for research on typing variational programs. We define a type system for VLC in which VLC expressions are mapped to correspondingly variational types. We show that the type system is correct by proving that the typing of expressions is preserved over the process of variation elimination, which eventually results in a plain lambda calculus expression and its corresponding type. We identify a set of equivalence rules for variational types and prove that the type unification problem modulo these equivalence rules is unitary and decidable; we also present a sound and complete unification algorithm. Based on the unification algorithm, the variational type inference algorithm is an extension of algorithm W. We show that it is sound and complete and computes principal types. We also consider the extension of VLC with sum types, a necessary feature for supporting variational data types, and demonstrate that the previous theoretical results also hold under this extension. Finally, we characterize the complexity of variational type inference and demonstrate the efficiency gains over the brute-force strategy.This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by the Association for Computing Machinery and can be found at: http://toplas.acm.org/.Keywords: variational type inference, variational types, variational lambda calculu

Structural abstraction: a mechanism for modular program construction

Abstraction mechanisms in programming languages aim to allow orthogonal pieces of functionality to be developed separately; complex software can then be constructed through the composition of these pieces. The effectiveness of such mechanisms lies in their support for modularity and reusability: The behavior of a piece of code should be reasoned about modularly---independently of the specific compositions it may participate in; the computation of a piece of code should allow specialization, so that it is reusable for different compositions. This dissertation introduces structural abstraction: a mechanism that advances the state of the art by allowing the writing of highly reusable code---code whose structure can be specialized per composition, while maintaining a high level of modularity. Structural abstraction provides a disciplined way for code to inspect the structure of its clients in composition, and declare its own structure accordingly. The hallmark feature of structural abstraction is that, despite its emphasis on greater reusability, it still allows modular type checking: A piece of structurally abstract code can be type-checked independently of its uses in compositions---an invaluable feature for highly reusable components that will be statically composed by other programmers. This dissertation introduces two structural abstraction techniques: static type conditions, and morphing. Static type conditions allow code to be conditionally declared based on subtyping constraints. A client of a piece of code can configure a desirable set of features by composing the code with types that satisfy the appropriate subtyping conditions. Morphing allows code to be iteratively declared, by statically reflecting over the structural members of code that it would be composed with. A morphing piece of code can mimic the structure of its clients in composition, or change its shape according to its clients in a pattern-based manner. Using either static type conditions or morphing, the structure of a piece of code is not statically determined, but can be automatically specialized by clients. Static type conditions and morphing both guarantee the modular type-safety of code: regardless of specific client configurations, code is guaranteed to be well-typed.Ph.D.Committee Chair: Yannis Smaragdakis; Committee Member: Oege de Moor; Committee Member: Richard LeBlanc; Committee Member: Santosh Pande; Committee Member: Spencer Rugabe

Statically Safe Program Generation with SafeGen

SafeGen is a meta-programming language for writing statically safe generators of Java programs. If a program generator written in SafeGen passes the checks of the SafeGen compiler, then the generator will only generate well-formed Java programs, for any generator input. In other words, statically checking the generator guarantees the correctness of any generated program, with respect to static checks commonly performed by a conventional compiler (including type safety, existence of a superclass, etc.). To achieve this guarantee, SafeGen supports only language primitives for reflection over an existing well-formed Java program, primitives for creating program fragments, and a restricted set of constructs for iteration, conditional actions, and name generation. SafeGen’s static checking algorithm is a combination of traditional type checking for Java, and a series of calls to a theorem prover to check the validity of first-order logical sentences constructed to represent well-formedness properties of the generated program under all inputs. The approach has worked quite well in our tests, providing proofs for correct generators or pointing out interesting bugs

Statically Safe Program Generation with SafeGen

SafeGen is a meta-programming language for writing statically safe generators of Java programs. If a program generator written in SafeGen passes the checks of the SafeGen compiler, then the generator will only generate well-formed Java programs, for any generator input. In other words, statically checking the generator guarantees the correctness of any generated program, with respect to static checks commonly performed by a conventional compiler (including type safety, existence of a superclass, etc.). To achieve this guarantee, SafeGen supports only language primitives for reflection over an existing well-formed Java program, primitives for creating program fragments, and a restricted set of constructs for iteration, conditional actions, and name generation. SafeGen’s static checking algorithm is a combination of traditional type checking for Java, and a series of calls to a theorem prover to check the validity of first-order logical sentences constructed to represent well-formedness properties of the generated program under all inputs. The approach has worked quite well in our tests, providing proofs for correct generators or pointing out interesting bugs