Feature Model Synthesis from Language-Independent Functional Descriptions

Author(s):  
Mariem Mefteh ◽  
Nadia Bouassida ◽  
Hanene Ben-Abdallah
2015 ◽  
Vol 21 (4) ◽  
pp. 1794-1841 ◽  
Author(s):  
Guillaume Bécan ◽  
Mathieu Acher ◽  
Benoit Baudry ◽  
Sana Ben Nasr

2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Andreea Vescan ◽  
Adrian Pintea ◽  
Lukas Linsbauer ◽  
Alexander Egyed

AbstractSoftware Product Lines (SPLs) make it possible to configure a single system based on features in order to create many different variants and cater to a wide range of customers with varying requirements. This configuration space is often modeled using Feature Models (FMs). However, in practice, the SPL (and consequently the FM) is often created after a set of variants has already been created manually. Automating the task of reverse engineering a feature model that describes a set of variants makes the process of adopting an SPL easier. The genetic programming pipeline is a good fit for feature models and has been shown to produce good reverse engineering results. In this paper, we replicate the results of such an existing approach with a larger set of feature models and investigate the effects of various genetic programming parameters and operators on the results. The design of our replication experiments employs three perspectives: duplicate the exact conditions using various features models, study the interaction of two parameters of the genetic programming approach, and optimize the values for the population and generation parameters and for the mutation and crossover operators. Results reinforce the previously obtained outcome, the original study being confirmed. The relations between the number of features and number of generations, respectively number of features and size of populations were also investigated and best values based on obtained results are provided. The current study also aimed to optimize various parameters of the genetic programming approach, the interpretation of those experiments discovering concrete values.


Author(s):  
Lukas Linsbauer ◽  
Roberto Erick Lopez-Herrejon ◽  
Alexander Egyed

Author(s):  
Carmen García-Alba

This study is part of a larger research study (doctoral dissertation), in which a comparative study with adolescent samples is done: 50 anorexic restricting patients (ANP), 50 patients diagnosed with depression (DP) and 50 non patients (NP). The proposed objective is two-fold: 1) To try to clarify the existing relationship between Anorexia (AN) and Depression (D), investigated from diverse disciplines but without conclusive results. 2) To detect in the ANP personality different traits from those of other groups, which should, if possible, allow to detect them at an early stage for an adequate prognosis. The current article presents the Rorschach findings in relation to the cognitive functioning of the ANP. In them, the following has been detected: (1) An information processing similar to that of the other groups, even with a more complete (L ≤ .99), more complex (DQ+↑) and better discriminated (Zd↑) grasp of the stimulus; (2) Mediating processes very similar to those of the other groups, sharing with them the perceptive maladjustments (X–%↑) and an excessive individualism (Xu%↑); (3) A clearly differentiating ideation disorder. Definitely, the ANP use predominantly ideation (M↑), but their thought, usually well-adjusted (MQo↑), presents eventual operations of delusional type (MQnone↑). Above that, their thinking is marked by a great passivity (Mp↑), which makes them more vulnerable to accept ideas without criticizing them and it results in a very inefficient thinking, which spins around these concepts without finding solutions, entering into a sort of ruminating which is completely unproductive. The differences toward the obsessive pathology are established. The discriminant analysis conducted with all the Rorschach variables that resulted as significant throughout the research, provides quite a consistent function which discriminates the ANP: MQnone↑, Mp↑, FD↓, Ma↑, MQo↑, AdjD↑, Sum H↑, (H)↑. Based on this we can understand that these adolescents, being in a developmental period of big changes and disorientations in relation with their own image, confronted with life events, and possibly starting off with some biologic vulnerability: (1) Due to the alterations of their ideation, accept without criticism (Mp) irrational ideas dominating in our culture, in which slimness appears as the only model, synthesis of intelligence, beauty and success; remaining captured in this type of mental activity (MQnone), which they cannot escape nor criticize (Mp), despite they reason adequately on other topics (MQo); (2) Their alterations of self-perception [(H)] make them hide themselves in a fantasized image, which is the axis of their interests and the only thing that really matters to them; (3) The resources they have to decide on behaviors and to finish these deliberately (AdjD), and their scarce tendency to the introspection (FD) lead to their decision of not eating, based on distorted and passively accepted thinking, which has great power and thus, so difficult to modify. Finally, based on the Rorschach data obtained, the hypothesis of a personality disorder as underlying pathology is pointed out.


Author(s):  
Hitesh Yadav ◽  
Rita Chhikara ◽  
Charan Kumari

Background: Software Product Line is the group of multiple software systems which share the similar set of features with multiple variants. Feature model is used to capture and organize features used in different multiple organization. Objective: The objective of this research article is to obtain an optimized subset of features which are capable of providing high performance. Methods: In order to achieve the desired objective, two methods have been proposed. a) An improved objective function which is used to compute the contribution of each feature with weight based methodology. b) A hybrid model is employed to optimize the Software Product Line problem. Results: Feature sets varying in size from 100 to 1000 have been used to compute the performance of the Software Product Line. Conclusion: The results shows that proposed hybrid model outperforms the state of art metaheuristic algorithms.


Author(s):  
Raúl Mazo ◽  
Camille Salinesi ◽  
Daniel Diaz ◽  
Olfa Djebbi ◽  
Alberto Lora-Michiels

Drawing from an analogy between features based Product Line (PL) models and Constraint Programming (CP), this paper explores the use of CP in the Domain Engineering and Application Engineering activities that are put in motion in a Product Line Engineering strategy. Specifying a PL as a constraint program instead of a feature model carries out two important qualities of CP: expressiveness and direct automation. On the one hand, variables in CP can take values over boolean, integer, real or even complex domains and not only boolean values as in most PL languages such as the Feature-Oriented Domain Analysis (FODA). Specifying boolean, arithmetic, symbolic and reified constraint, provides a power of expression that spans beyond that provided by the boolean dependencies in FODA models. On the other hand, PL models expressed as constraint programs can directly be executed and analyzed by off-the-shelf solvers. This paper explores the issues of (a) how to specify a PL model using CP, including in the presence of multi-model representation, (b) how to verify PL specifications, (c) how to specify configuration requirements, and (d) how to support the product configuration activity. Tests performed on a benchmark of 50 PL models show that the approach is efficient and scales up easily to very large and complex PL specifications.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Raymond J. Langley ◽  
Marie E. Migaud ◽  
Lori Flores ◽  
J. Will Thompson ◽  
Elizabeth A. Kean ◽  
...  

AbstractAcute respiratory failure (ARF) requiring mechanical ventilation, a complicating factor in sepsis and other disorders, is associated with high morbidity and mortality. Despite its severity and prevalence, treatment options are limited. In light of accumulating evidence that mitochondrial abnormalities are common in ARF, here we applied broad spectrum quantitative and semiquantitative metabolomic analyses of serum from ARF patients to detect bioenergetic dysfunction and determine its association with survival. Plasma samples from surviving and non-surviving patients (N = 15/group) were taken at day 1 and day 3 after admission to the medical intensive care unit and, in survivors, at hospital discharge. Significant differences between survivors and non-survivors (ANOVA, 5% FDR) include bioenergetically relevant intermediates of redox cofactors nicotinamide adenine dinucleotide (NAD) and NAD phosphate (NADP), increased acyl-carnitines, bile acids, and decreased acyl-glycerophosphocholines. Many metabolites associated with poor outcomes are substrates of NAD(P)-dependent enzymatic processes, while alterations in NAD cofactors rely on bioavailability of dietary B-vitamins thiamine, riboflavin and pyridoxine. Changes in the efficiency of the nicotinamide-derived cofactors’ biosynthetic pathways also associate with alterations in glutathione-dependent drug metabolism characterized by substantial differences observed in the acetaminophen metabolome. Based on these findings, a four-feature model developed with semi-quantitative and quantitative metabolomic results predicted patient outcomes with high accuracy (AUROC = 0.91). Collectively, this metabolomic endotype points to a close association between mitochondrial and bioenergetic dysfunction and mortality in human ARF, thus pointing to new pharmacologic targets to reduce mortality in this condition.


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