Coevolution of variability models and related software artifacts

Variant-rich software systems offer a large degree of customization, allowing users to configure the target system according to their preferences and needs. Facing high degrees of variability, these systems often employ variability models to explicitly capture user-configurable features (e.g., systems options) and the constraints they impose. The explicit representation of features allows them to be referenced in different variation points across different artifacts, enabling the latter to vary according to specific feature selections. In such settings, the evolution of variability models interplays with the evolution of related artifacts, requiring the two to evolve together, or coevolve. Interestingly, little is known about how such coevolution occurs in real-world systems, as existing research has focused mostly on variability evolution as it happens in variability models only. Furthermore, existing techniques supporting variability evolution are usually validated with randomly-generated variability models or evolution scenarios that do not stem from practice. As the community lacks a deep understanding of how variability evolution occurs in real-world systems and how it relates to the evolution of different kinds of software artifacts, it is not surprising that industry reports existing tools and solutions ineffective, as they do not handle the complexity found in practice. Attempting to mitigate this overall lack of knowledge and to support tool builders with insights on how variability models coevolve with other artifact types, we study a large and complex real-world variant-rich software system: the Linux kernel. Specifically, we extract variability-coevolution patterns capturing changes in the variability model of the Linux kernel with subsequent changes in Makefiles and C source code. From the analysis of the patterns, we report on findings concerning evolution principles found in the kernel, and we reveal deficiencies in existing tools and theory when handling changes captured by our patterns.     

In situ syntheses of a suspension agent based on a styrene–acrylic acid copolymer for the suspension polymerization of styrene

We carried out the suspension polymerization of styrene, initiated with benzoyl peroxide at 80°C, in the presence of the simultaneous polymerization of acrylic acid in the water phase, initiated by potassium peroxidisulfate (KPS) at the same temperature. The polymerization in the water phase was started at certain times after the beginning of the polymerization of styrene. Then, a continuous addition of KPS was carried out at a given landing rate and during variable feeding times. The water‐phase polymerization actually produced a copolymer of styrene and acrylic acid, which displayed surface‐active properties. The particle size distribution depended on the variables mentioned earlier (starting time, KPS feeding rate, and addition time), being controlled by the molecular weight, and on the composition of the copolymer produced and its availability at the increasing conversion of styrene. A second distribution of submicronic particles was produced. Both families of particles had about the same molecular weight. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 3271–3285, 2002     

Ant Colony Optimization Inspired Algorithm for 3D Object Segmentation into its Constituent Parts

Neural Processing Letters - This work focuses on the use of an Ant colony optimization (ACO) based approach to the problem of 3D object segmentation. The ACO metaheuristic uses a set of agents...     

Path planning approach based on flock dynamics of moving particles

A novel method based on the behaviour of a flock of moving particles is proposed in order to solve the path planning problem of a mobile robot in two-dimensional dynamical sceneries. The mentioned particles search free obstacles zones into the scenery using a set of collective behaviour rules. The positions of the members of the flock form the search space. A heuristic method, referred to as dynamical particle chain (DPC), is used to join the position of the robot with the target through consecutive connections among the particles of the flock. The result is a free obstacle path, which is able to adapt its structure to environmental changes. The feasibility of the proposed method and its comparison with other algorithms are also discussed and illustrated.     

N-[2-[4-(4-Chlorophenyl)piperazin-1-yl]ethyl]-3-methoxybenzamide: a potent and selective dopamine D4 ligand

A series of new 1-aryl-4-alkylpiperazines containing a terminal benzamide fragment or a tetralin-1-yl nucleus on the alkyl chain were synthesized and tested for binding at cloned human dopamine D4 and D2 receptor subtypes. A SAFIR (structure-affinity relationship) study on this series is herein discussed. The most relevant D4 receptor affinities were displayed by N-[omega-[4-arylpiperazin-1-yl]alkyl]-methoxybenzamides (compounds 5, 16-20), their IC50 values ranging between 0.057 and 7.8 nM. Among these, N-[2-[4-(4-chlorophenyl)piperazin-1-yl]ethyl]-3-methoxybenzamide (17) emerged since it exhibited very high affinity for dopamine D4 receptor (IC50 = 0.057 nM) with selectivity of >10 000 for the D4 versus the D2 receptor; compound 17 was also selective versus serotonin 5-HT1A and adrenergic alpha1 receptors.     

Explanation of Bitter Taste of Venom of Ponerine Ant, Pachycondyla apicalis

The venom gland of workers of Pachycondyla (= Neoponera) apicalis (Hymenoptera: Formicidae) contains the bitter-tasting cyclic dipeptide of leucine and phenylalanine [cyclo-leu-phe or 3-benzyl-6-(2-methylpropyl)-2,5-piperazinedione]. The venom also contains proteins of undetermined activity. It is suggested that the function of the venom may be both defensive and offensive. The mandibular glands of N. apicalis contains δ-decalactone and benzaldehyde.