DeMIMA: A Multilayered Approach for Design Pattern Identification

Design patterns are important in object-oriented programming because they offer design motifs, elegant solutions to recurrent design problems, which improve the quality of software systems. Design motifs facilitate system maintenance by helping to understand design and implementation. However, after implementation, design motifs are spread throughout the source code and are thus not directly available to maintainers. We present DeMIMA, an approach to identify semi-automatically micro-architectures that are similar to design motifs in source code and to ensure the traceability of these micro-architectures between implementation and design. DeMIMA consists of three layers: two layers to recover an abstract model of the source code, including binary class relationships, and a third layer to identify design patterns in the abstract model. We apply DeMIMA to five open-source systems and, on average, we observe 34% precision for the considered 12 design motifs. Through the use of explanation-based constraint programming, DeMIMA ensures 100% recall on the five systems. We also apply DeMIMA on 33 industrial components.     

Synthesis and Electrical Properties of Well-Ordered Layered α-MoO3 Nanosheets

Nano-Micro Letters - α-MoO3 ordered nanosheets have been synthesized under hydrothermal conditions using commercial MoO3 and hydroquinone as structuring agent. X-ray diffraction (XRD),...     

A systematic literature review on the detection of smells and their evolution in object-oriented and service-oriented systems

This systematic literature review paper investigates the key techniques employed to identify smells in different paradigms of software engineering from object-oriented (OO) to service-oriented (SO). In this review, we want to identify commonalities and differences in the identification of smells in OO and SO systems. Our research method relies on an automatic search from the relevant digital libraries to find the studies published since January 2000 on smells until December 2017. We have conducted a pilot and author-based search that allows us to select the 78 most relevant studies after applying inclusion and exclusion criteria. We evaluated the studies based on the smell detection techniques and the evolution of different methodologies in OO and SO. Among the 78 relevant studies selected, we have identified six different studies in which linguistic source code analysis received less attention from the researchers as compared to the static source code analysis. Smells like the yo-yo problem, unnamed coupling, intensive coupling, and interface bloat received considerably less attention in the literature. We also identified a catalog of 30 smells infrequently reported for SO systems and that require further attention. Moreover, a suite of 20 smells reported for SO systems can also be detected using static source code metrics in OO. Finally, our review highlighted three major research trends that are further subdivided into 20 research patterns initiating the detection of smells toward their correction.     

An Efficient Greedy Traffic Aware Routing Scheme for Internet of Vehicles

A new paradigm of VANET has emerged in recent years: Internet of Vehicles (IoV). These networks are formed on the roads and streets between travellers who have relationships, interactions and common social interests. Users of these networks exchange information of common interest, for example, traffic jams and dangers on the way. They can also exchange files such as multimedia files. IoV is considered as part of the Internet of Things (IoT) where objects are vehicles, which can create a multitude of services dedicated to the intelligent transportation system. The interest is to permit to all connected vehicles to communicate with each other and/or with a central server, through other vehicles. Vehicle to Vehicle (V2V) communication is the main component, because the services encompassed in the IoV are based on the vehicles in question, such as transmitter, relay and receiver. This work is focusing on designing and developing a Quality of Service (QoS) routing scheme dedicated to IoV networks. Especially, we aim to improve the Greedy Traffic Aware Routing (GyTAR) protocol to support QoS in IoV networks. To evaluate the proposed approach in terms of QoS in the context of IoV networks, the performance metrics such as average end-to-end delay and packet delivery ratio are taken into consideration to analyse the network situation.     

Hydromagnetic Double-Diffusive Laminar Natural Convection in a Radiatively Participating Fluid

ABSTRACT

Two-dimensional hydromagnetic double-diffusive convection of a radiatively participating fluid confined in a rectangular enclosure is studied numerically for fixed Prandtl, Rayleigh, and Lewis numbers, Pr = 13.6, Ra = 10⁵, Le = 2. Uniform temperatures and concentrations are imposed along the vertical walls, while the horizontal walls are assumed to be adiabatic and impermeable. The damping and stabilization effects of an external horizontal magnetic field are studied for three different optical thicknesses of the semitransparent fluid as well as for an opaque medium. For moderate optical thickness, a steady compositionally dominated flow is observed for all values of Hartmann number considered, and the magnetic damping is remarkably lower than in the opaque medium, for which the flow is always thermally dominated. For optically thin and optically thick media, the thermally dominated flow is stabilized and becomes compositionally dominated as soon as the Hartmann number is increased.     

Species distribution,antibiotic resistance and virulence traits in enterococci from meat in Tunisia

Antimicrobial resistance and the mechanisms implicated were studied in 119 enterococci from 105 meat samples from Tunisian markets. Almost 24.5% of recovered enterococci showed resistance against four or more antimicrobial agents and these isolates were identified to the species level. Enterococcus faecalis was the most prevalent species (41%). High percentages of erythromycin and tetracycline resistances were found among our isolates, and lower percentages were identified to aminoglycosides, ciprofloxacin and chloramphenicol. All tetracycline-resistant isolates carried the tet(M) and/or tet(L) genes. The erm(B) gene was detected in 78.5% of erythromycin-resistant isolates, ant(6)-Ia gene in 58.8% of streptomycin-resistant isolates, and cat(A) gene in one chloramphenicol-resistant isolate. Forty-eight isolates carried the gelE gene and exhibited gelatinase activity. The hyl and esp genes were detected in one and three Enterococcus faecium isolates, respectively. Streptomycin-resistant isolates showed a high genetic diversity by PFGE and MLST. Meat might play a role in the spread through the food chain of enterococci with these virulence and resistance characteristics to humans.     

Feature Identification: An Epidemiological Metaphor

Feature identification is a technique to identify the source code constructs activated when exercising one of the features of a program. We propose new statistical analyses of static and dynamic data to accurately identify features in large multithreaded object-oriented programs. We draw inspiration from epidemiology to improve previous approaches to feature identification and develop an epidemiological metaphor. We build our metaphor on our previous approach to feature identification, in which we use processor emulation, knowledge-based filtering, probabilistic ranking, and metamodeling. We carry out three case studies to assess the usefulness of our metaphor, using the "save a bookmark" feature of Web browsers as an illustration. In the first case study, we compare our approach with three previous approaches (a naive approach, a concept analysis-based approach, and our previous probabilistic approach) in identifying the feature in MOZILLA, a large, real-life, multithreaded object-oriented program. In the second case study, we compare the implementation of the feature in the FIREFOX and MOZILLA Web browsers. In the third case study, we identify the same feature in two more Web browsers, Chimera (in C) and ICEBrowser (in Java), and another feature in JHOTDRAW and XFIG, to highlight the generalizability of our metaphor     

Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval

This paper recasts the problem of feature location in source code as a decision-making problem in the presence of uncertainty. The solution to the problem is formulated as a combination of the opinions of different experts. The experts in this work are two existing techniques for feature location: a scenario-based probabilistic ranking of events and an information-retrieval-based technique that uses latent semantic indexing. The combination of these two experts is empirically evaluated through several case studies, which use the source code of the Mozilla Web browser and the Eclipse integrated development environment. The results show that the combination of experts significantly improves the effectiveness of feature location as compared to each of the experts used independently     

From a domain analysis to the specification and detection of code and design smells

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.