Abstract Code and design smells are recurring design problems in software systems that must be identified to avoid their possible negative consequences on development and maintenance. Consequently, several smell detection approaches and tools have been proposed in the literature. However, so far, they allow the detection of predefined smells but the detection of new smells or smells adapted to the context of the analysed systems is possible only by implementing new detection algorithms manually. Moreover, previous approaches do not explain the transition from specifications of smells to their detection. Finally, the validation of the existing approaches and tools has been limited on few proprietary systems and on a reduced number of smells. In this paper, we introduce an approach to automate the generation of detection algorithms from specifications written using a domain-specific language. This language is defined from a thorough domain analysis. It allows the specification of smells using high-level domain-related abstractions. It allows the adaptation of the specifications of smells to the context of the analysed systems. We specify 10 smells, generate automatically their detection algorithms using templates, and validate the algorithms in terms of precision and recall on Xerces v2.7.0 and GanttProject v1.10.2, two open-source object-oriented systems. We also compare the detection results with those of a previous approach, iPlasma .

Code and design smells are poor solutions to recurring implementation and design problems. They may hinder the evolution of a system by making it hard for software engineers to carry out changes. We propose three contributions to the research field related to code and design smells: (1) DECOR, a method that embodies and defines all the steps necessary for the specification and detection of code and design smells, (2) DETEX, a detection technique that instantiates this method, and (3) an empirical validation in terms of precision and recall of DETEX. The originality of DETEX stems from the ability for software engineers to specify smells at a high level of abstraction using a consistent vocabulary and domain-specific language for automatically generating detection algorithms. Using DETEX, we specify four well-known design smells: the antipatterns Blob, Functional Decomposition, Spaghetti Code, and Swiss Army Knife, and their 15 underlying code smells, and we automatically generate their detection algorithms. We apply and validate the detection algorithms in terms of precision and recall on XERCES v2.7.0, and discuss the precision of these algorithms on 11 open-source systems.

Dynamic software adaptation can cause the running system to be out-of-synchronous with its model, and, thus, make the system model obsolete for the use in consistency checking. In this paper, we propose a framework for ensuring the synchronization between the model and the runtime system during dynamic adaptation. I.e., this framework maintains the high-level model of the runtime system, which is essential for system validation. We are also plugging several model validation tools to the framework, for performing system validation during dynamic adaptation.

When an application must evolve to cope with new context and user requirements, integrating new functionalities into its software architecture is necessary. The architect has thus to manually modify the architecture description, which is often tedious and error prone. In this paper, we propose FIESTA, a generic framework for automatically integrating new functionalities into an architecture description. Our approach is inspired by TranSAT, an integration framework. However, TranSAT is dedicated to a specific architecture description language (ADL) while our approach is ADL-independent. We have performed a domain analysis, studying for many ADLs how to integrate new functionalities. Based on this analysis, we have defined a generic ADL model to manipulate and reason about architectural elements that are involved in integration. Furthermore, we have developed a generic integration engine.

Software architecture is a key concept in the design of a complex system. An architecture models the structure and behavior of the system, including the software elements and the relationships between them. While architectures were originally specified informally, recent years have seen the creation of a number of Architecture Description Languages (ADLs) [4]. ADLs are designed around the dimensions of composition and interaction, allowing the architect to introduce new concerns by constructing and combining increasingly complex elements

Abstract — Fast and optimized protocol stacks play a major role in the performance of network services. This role is especially important in embedded class systems, where performance metrics such as data throughput tend to be limited by the CPU. It is common on such systems, to have protocol stacks that are optimized by hand for better performance and smaller code footprint. In this paper, we propose a strategy to automate this process. Our approach uses program specialization, and enables appli-cations using the network to request specialized code based on the current usage scenario. The specialized code is generated dy-namically and loaded in the kernel to be used by the application. We have successfully applied our approach to the TCP/IP implementation in the Linux kernel and used the optimized protocol stack in existing applications. These applications were minimally modified to request the specialization of code based on the current usage context, and to use the specialized code generated instead of its generic version. Specialization can be performed locally, or deferred to a remote specialization server using a novel mechanism [1]. Experiments conducted on three platforms show that the specialized code runs about 25 % faster and its size reduces by up to 20 times. The throughput of the protocol stack improves by up to 21%. I.

Automating software evolution requires both identifying precisely the affected program points and selecting the appropriate modification at each point. This task is particularly complicated when considering a large program, even when the modifications appear to be systematic. We illustrate this situation in the context of evolving the Linux kernel to support Bossa, an event-based framework for process-scheduler development. To support Bossa, events must be added at points scattered throughout the kernel. In each case, the choice of event depends on properties of one or a sequence of instructions. To describe precisely the choice of event, we propose to guide the event insertion by using a set of rules, amounting to an aspect that describes the control-flow contexts in which each event should be generated. In this paper, we present our approach and describe the set of rules that allows proper event insertion. These rules use temporal logic to describe sequences of instructions that require events to be inserted. We also give an overview of an implementation that we have developed to automatically perform this evolution.

Partial evaluation is a program-transformation technique that automatically specializes a program with respect to user-supplied invariants. Despite successful applications in areas such as graphics, operating systems, and software engineering, partial evaluators have yet to achieve widespread use. One reason is the difficulty of adequately describing specialization opportunities. Indeed, under-specialization or over-specialization often occurs, without any direct feedback to the user as to the source of the problem.We have developed a high-level, module-based language allowing the programmer to guide the choice of both the code to specialize and the invariants to exploit during the specialization process. To ease the use of partial evaluation, the syntax of this language is similar to the declaration syntax of the target language of the partial evaluator. To provide feedback to the programmer, declarations are checked throughout the analyses performed by partial evaluation. The language has been successfully used by a signal-processing expert in the design of a specializable Forward Error Correction component.