A Heuristic Algorithm to Detect Feature Interactions in Requirements
نویسندگان
چکیده
We present a heuristic algorithm to systematically detect feature interactions in requirements, which are expressed as constraints on system event traces. The algorithm is part of a broader methodology for requirements elicitation and formal specification. Given a new constraint and a set of already accepted constraints, it computes a set of candidate constraints that possibly interact with the new one. We illustrate the algorithm by adding new features to a simple lift.
منابع مشابه
Feature Selection in Structural Health Monitoring Big Data Using a Meta-Heuristic Optimization Algorithm
This paper focuses on the processing of structural health monitoring (SHM) big data. Extracted features of a structure are reduced using an optimization algorithm to find a minimal subset of salient features by removing noisy, irrelevant and redundant data. The PSO-Harmony algorithm is introduced for feature selection to enhance the capability of the proposed method for processing the measure...
متن کاملIdentification of Genetic Polymorphism Interactions in Sporadic Alzheimer’s Disease Using Logic Regression
Objectives: Genetic polymorphism interactions are among the important factors in affliction with complex diseases like Alzheimer’s disease. The important goal of genetic association studies is to identify a combination of polymorphisms and measure their importance in increasing the risk of occurrence of such diseases. In this study, feature selection approach of logic regression was used to ide...
متن کاملDetecting communities of workforces for the multi-skill resource-constrained project scheduling problem: A dandelion solution approach
This paper proposes a new mixed-integer model for the multi-skill resource-constrained project scheduling problem (MSRCPSP). The interactions between workers are represented as undirected networks. Therefore, for each required skill, an undirected network is formed which shows the relations of human resources. In this paper, community detection in networks is used to find the most compatible wo...
متن کاملSequential and Mixed Genetic Algorithm and Learning Automata (SGALA, MGALA) for Feature Selection in QSAR
Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...
متن کاملA comparative study of two meta-heuristic algorithms in optimizing cost of reinforced concrete segmental lining
In this work, we tried to automatically optimize the cost of the concrete segmental lining used as a support system in the case study of Mashhad Urban Railway Line 2 located in NE Iran. Two meta-heuristic optimization methods including particle swarm optimization (PSO) and imperialist competitive algorithm (ICA) were presented. The penalty function was used for unfeasible solutions, and the seg...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2000