Automated metamorphic testing on the analyses of feature models

Copyright © 2010 Elsevier B.V. All rights reserved.Context: A feature model (FM) represents the valid combinations of features in a domain. The automated extraction of information from FMs is a complex task that involves numerous analysis operations, techniques and tools. Current testing methods in this context are manual and rely on the ability of the tester to decide whether the output of an analysis is correct. However, this is acknowledged to be time-consuming, error-prone and in most cases infeasible due to the combinatorial complexity of the analyses, this is known as the oracle problem.Objective: In this paper, we propose using metamorphic testing to automate the generation of test data for feature model analysis tools overcoming the oracle problem. An automated test data generator is presented and evaluated to show the feasibility of our approach.Method: We present a set of relations (so-called metamorphic relations) between input FMs and the set of products they represent. Based on these relations and given a FM and its known set of products, a set of neighbouring FMs together with their corresponding set of products are automatically generated and used for testing multiple analyses. Complex FMs representing millions of products can be efficiently created by applying this process iteratively.Results: Our evaluation results using mutation testing and real faults reveal that most faults can be automatically detected within a few seconds. Two defects were found in FaMa and another two in SPLOT, two real tools for the automated analysis of feature models. Also, we show how our generator outperforms a related manual suite for the automated analysis of feature models and how this suite can be used to guide the automated generation of test cases obtaining important gains in efficiency.Conclusion: Our results show that the application of metamorphic testing in the domain of automated analysis of feature models is efficient and effective in detecting most faults in a few seconds without the need for a human oracle.This work has been partially supported by the European Commission(FEDER)and Spanish Government under CICYT project SETI(TIN2009-07366)and the Andalusian Government project ISABEL(TIC-2533)

Product line architecture recovery with outlier filtering in software families: the Apo-Games case study

Software product line (SPL) approach has been widely adopted to achieve systematic reuse in families of software products. Despite its benefits, developing an SPL from scratch requires high up-front investment. Because of that, organizations commonly create product variants with opportunistic reuse approaches (e.g., copy-and-paste or clone-and-own). However, maintenance and evolution of a large number of product variants is a challenging task. In this context, a family of products developed opportunistically is a good starting point to adopt SPLs, known as extractive approach for SPL adoption. One of the initial phases of the extractive approach is the recovery and definition of a product line architecture (PLA) based on existing software variants, to support variant derivation and also to allow the customization according to customers’ needs. The problem of defining a PLA from existing system variants is that some variants can become highly unrelated to their predecessors, known as outlier variants. The inclusion of outlier variants in the PLA recovery leads to additional effort and noise in the common structure and complicates architectural decisions. In this work, we present an automatic approach to identify and filter outlier variants during the recovery and definition of PLAs. Our approach identifies the minimum subset of cross-product architectural information for an effective PLA recovery. To evaluate our approach, we focus on real-world variants of the Apo-Games family. We recover a PLA taking as input 34 Apo-Game variants developed by using opportunistic reuse. The results provided evidence that our automatic approach is able to identify and filter outlier variants, allowing to eliminate exclusive packages and classes without removing the whole variant. We consider that the recovered PLA can help domain experts to take informed decisions to support SPL adoption.This research was partially funded by INES 2.0; CNPq grants 465614/2014-0 and 408356/2018-9; and FAPESB grants JCB0060/2016 and BOL2443/201

Location-based Modeling and Analysis: Tropos-based Approach

The continuous growth of interest in mobile applications makes the concept of location essential to design and develop software systems. Location-based software is supposed to be able to monitor the location and choose accordingly the most appropriate behavior. In this paper, we propose a novel conceptual framework to model and analyze location-based software. We mainly focus on the social facets of locations adopting concepts such as social actor, resource, and location-based behavior. Our approach is based on Tropos methodology and allows the analyst to elicit and model software requirements according to the different locations where the software will operate. We propose an extension of Tropos modeling and adapt its process to suit well with the development of location-based software. The proposed framework also includes automated analysis techniques to reason about the relation between location and location-based behavior

A Reengineering Method from Procedural SW to Object-Oriented SW for SaaS in Cloud Computing

One of the strong requirements for SaaS in cloud computing is the reengineering capability to transform procedural SW to object-oriented SW in case that there is no object-oriented SW available for a target application but procedural SW. Consequently it will be necessary to convert the procedural to the object-oriented automatically by quantifiably acceptable means of conversion that guarantees the quality of SaaS. This paper presents such a conversion method from C to C++ with the quantifiable means based on similarities for classes and inheritance required for SaaS. The first phase of the conversion is to simplify the C source code into a graph with a minimum number of tightly coupled components. The second phase is to generate all the possible groups of the class candidates from the graph. The third phase is to generate class signature similarities in each group to determine class inheritance. The last phase is to generate class and inheritance similarities between each group and the domain in the application. Compared with other approaches, this method gives SaaS experts with a comprehensive and integrated base to control selection of the best or optimal group of the class candidates for the application from cloud computing

Creating a Relational Distributed Object Store

In and of itself, data storage has apparent business utility. But when we can convert data to information, the utility of stored data increases dramatically. It is the layering of relation atop the data mass that is the engine for such conversion. Frank relation amongst discrete objects sporadically ingested is rare, making the process of synthesizing such relation all the more challenging, but the challenge must be met if we are ever to see an equivalent business value for unstructured data as we already have with structured data. This paper describes a novel construct, referred to as a relational distributed object store (RDOS), that seeks to solve the twin problems of how to persistently and reliably store petabytes of unstructured data while simultaneously creating and persisting relations amongst billions of objects.Comment: 12 pages, 5 figure

Location-based software modeling and analysis: Tropos-based approach

Abstract. The continuous growth of interest in mobile applications makes the concept of location essential to design and develop software systems. Location-based software is supposed to be able to monitor the surrounding location and choose accordingly the most appropriate behavior. In this paper, we propose a novel conceptual framework to model and analyze location-based software. We mainly focus on the social facets of locations adopting concepts such as actor, resource, and location-based behavior. Our approach is based on Tropos methodology and allows the analyst to elicit and model software requirements according to the different locations where the software will operate. We propose an extension of Tropos modeling and adapt its process to suit well with the development of location-based software. The proposed framework also includes automated analysis techniques to reason about the relation between location and location-based software.