Scaling up the Fitness Function for Reverse Engineering Feature Models

Product line software engineering (PLSE) is an emerging software engineering paradigm, which guides organizations toward the development of products from core assets rather than the development of products one by one from scratch. In order to develop highly reusable core assets, PLSE must have the ability to exploit commonality and manage variability among products from a domain perspective. Feature modeling is one of the most popular domain analysis techniques, which analyzes commonality and variability in a domain to develop highly reusable core assets for a product line. Various attempts have been made to extend and apply it to the development of software product lines. However, feature modeling can be difficult and time-consuming without a precise understanding of the goals of feature modeling and the aid of practical guidelines. In this paper, we clarify the concept of features and the goals of feature modeling, and provide practical guidelines for successful product line software engineering. The authors have extensively used feature modeling in several industrial product line projects and the guidelines described in this paper are based on these experiences.

Software product line engineering (SPLE) is a paradigm to promote systematic software reuse. A Feature Model (FM) is a common means to illustrate the commonality and variability of software products in a family. In most existing FM extraction approaches, keywords in the requirement document or certain types of system behavior or external events are considered features. The resulting FM is a combination of user activities and system actions (SAs), making it hard to understand. In this paper, we present an automatic approach to generate a product line FM from multiple requirement documents. We consider user activity and SAs separately in our approach and focus on the expected behaviors of the software system, together with the data being processed. The resulting FM clearly illustrates the expected functionalities of the software system and their variability in the product line. We also compared our approach with existing techniques by processing the same textual documents, and noted improvements in our results.

Software product lines are able to describe multiple products sharing a common base of features and are commonly described as feature models. For complex software product lines, automatic analyses are required to ensure validity and to improve the interactive configuration process. Modern SAT solvers are vital components for the validation process of feature models. The increasing variability of software product lines implies the need to use more expressive solvers like SMT solvers. To assist the development of feature modeling tools, we compare SAT and SMT solvers for the automated analysis of feature models. During this thesis, we create an abstract data type to formally define analyses for feature model defects and their explanations. The result shows that SAT solvers are more efficient at detecting the defects, while SMT solvers can find explanations for them multiple times faster. Feature models can be further expanded by attaching attributes to features. Such attributes may contain a numerical value. Additionally, one attribute can be defined for multiple features. In this thesis, we aim to support the interactive configuration process, by providing the range of the sum of values for an attribute. Such ranges depend on the remaining choices in a configuration of the product line. We provide an exact computation using SMT and an approximation using a heuristic. The evaluation results show that an SMT solver is not suitable for supporting interactive configuration. However, the approximated ranges of the provided heuristic were very close to the exact ones.

In software product line engineering (SPLE), commonality and variability across products of a product line domain are captured typically by a feature model. Reusable components are then developed from features. However, mapping features to components remains a complex task requiring a systematic way of exploring and analyzing various concerns arising from inadequate/insufficient domain assumptions. Essentially, those concerns prevent SPLE from achieving various quality attributes. This paper proposes a problem frames-based approach to addressing this problem. An elevator product line example is used to demonstrate the feasibility of the approach.

Evolutionary Testing has been shown a promising technology for the automatic test data generation. It reformulates test data generation as a metaheuristic search. A well- designed fitness function is essential to the efficiency of evolutionary search. Many efforts have been directed at the design and implementation of fitness function in recent years. However, previous work has just focused on the control dependency of the target on the branches in the same function. When function calls exist in the desired execution trace to the target, the evaluation of the test data on the coverage of these function calls, which should be provided to the evolutionary search, is not captured by the existing fitness function. In this case, the existing fitness function can not fairly evaluate the test data. And the evolutionary search will be hampered or even fail in severe cases. In this paper, a new term is first proposed to incorporate into the existing fitness function. It is applied to evaluate the test data's coverage of function calls along the desired path to the target. The new fitness function can evaluate the test data more fairly, resulting in a better guidance to the evolutionary search. This can be seen by the experiments carried out on two cases.

Software Product Line Engineering aims to ensure the correctness, completeness and consistency among its artifacts and the specified domain, in order to prevent the spread of defects for the products derived from this domain. Among initial artifacts of a software product line, feature models are artifacts generated in various domain engineering approaches. Although software inspection is highlighted as an effective review activity for detection of defects in software artifacts, mainly in the early models of software projects, a recent quasi-systematic review of literature indicated a lack of techniques to support the inspection of software product line artifacts, which include features models. Thus, this paper presents FMCheck, a checklist-based inspection technique to support the detection of defects on feature models. This technique was developed to be configurable and to be applied on several extensions of the original feature model notation presented by FODA approach, including the Odyssey-FEX notation, in particular. FMCheck was submitted to a proof of concept and to a further in vitro feasibility study, in which it could be seen the feasibility of FMCheck application and also that inspections applying FMCheck are more effective than ad-hoc inspections, when applied on four distinct domains.

Software product family or line is a software engineering paradigm that systematizes reuse. In software product line engineering, two phases are distinguished: domain engineering which is in charge of developing a common infrastructure and assets and application engineering which makes use of those assets to generate the products. One of the key aspects of product lines is variability and its management. However, the main focus has been on functional variability and quality variability in software product lines has not received so much attention by researchers. In a product line different members of the line may require different levels of a quality requirement, for instance they could differ in terms of their availability, security, reliability, etc. Due to this variability, quality evaluation in software product lines is much more complicated that in single-systems. One alternative is to evaluate all the products of a line but it is very expensive and ways of reducing evaluation efforts are necessary. In this direction, the paper presents a method for facilitating cost-effective quality evaluation of a product line taking into consideration variability on quality attributes.

Two mechanisms widely used in the Software Product Lines (SPL) Engineering are the feature model and the conditional compilation. The former models the variability in the problem space and the latter realizes it in the solution space. Even though the research community know that the feature model imposes a number of constraints to the product line implementation, there is a lack of support to co-evolve problem space and solution space. In this paper, we present an exploratory study whether problem space constraints are considered at source code level of #ifdef-based SPL implementations. In order to accomplish our goal, we developed a preliminary approach to check problem and solution spaces in a prototype tool (fclcheck). The results show a lack of realization of feature model constraints while implementing variation points with that mechanism. We also evaluated the scalability of the approach and the recoverability of the tool.

A text-based approach to feature modelling: Syntax and semantics of TVL

Software product line (SPL) engineering has emerged to become a mature domain for maximizing reuse within the context of a family of related software products. Within the process of SPL, the variability and commonality among the different products within the scope of a family is captured and modeled into a system's `feature model'. Currently, there are no architecture description languages (ADLs) that support the relationship between the feature model domain and the system architecture domain, leaving a gap which significantly increases the complexity of analyzing the system's architecture and insuring that it complies with its set feature model and variability requirements. In this paper we present ADLARS, an architecture description language that supports the relationship between the system's feature model and the architectural structures in an attempt to alleviate the aforementioned problem. The link between the two spaces also allows the automatic generation of product architectures from the family reference architecture

Version control (VC) and Software Product Line Engineering (SPLE) are two software engineering disciplines to manage variability in time and variability in space. In this paper, a thorough comparison of VC and SPLE is provided, showing that both disciplines imply a number of desirable properties. As a proof of concept for the combination of VC and SPLE, we present SuperMod, a tool realizes an existing conceptual framework that transfers the iterative VC editing model to SPLE. The tool allows to develop a software product line in a single-version workspace step by step, while variability management is completely automated. It offers familiar version control metaphors such as check-out and commit, and in addition uses the SPLE concepts of feature models and feature configuration the definition of logical variability and to define the logical scope of a change. SuperMod has been implemented in a model-driven way and primarily targets EMF models as software artifacts. We successfully apply the tool to a standard SPLE example.

Context. From recent works on product properties resulting from configurations and the optimisation of these properties, one comes quickly to more complex challenges such as multi-objective optimisation, conflicting objectives, multiple stakeholders, and conflict resolution. The intuition is that Software Product Line Engineering (SPLE) can draw from other disciplines that deal with decision spaces and complex decision scenarios.Objectives. We aim to (1) explore links to such disciplines, (2) systematise and compare concepts, and (3) identify opportunities, where SPLE approaches can be enriched.Method. We undertake an exploratory study: Starting from common SPLE activities and artefacts, we identify aspects where we expect to find corresponding counterparts in other disciplines. We focus on Multiple Criteria Decision Analysis (MCDA), Multi-Objective Optimisation (MOO), and Design Space Exploration (DSE), and perform a comparison of the key concepts.Results. The resulting comparison relates SPLE activities and artefacts to concepts from MCDA, MOO, and DSE and identifies areas where SPLE approaches can be enriched. We also provide examples of existing work at the intersections of SPLE with the other fields. These findings are aimed to foster the conversation on research opportunities where SPLE can draw techniques from other disciplines dealing with complex decision scenarios.

SUMMARYFeature modeling an attractive technique for capturing commonality as well as variability within an application domain for generative programming and software product line engineering. Feature models symbolize an overarching representation of the possible application configuration space, and can hence be customized based on specific domain requirements and stakeholder goals. Most interactive or semi‐automated feature model customization processes neglect the need to have a holistic approach towards the integration and satisfaction of the stakeholder's soft and hard constraints, and the application‐domain integrity constraints. In this paper, we will show how the structure and constraints of a feature model can be modeled uniformly through Propositional Logic extended with concrete domains, calledPscr(𝒩). Furthermore, we formalize the representation of soft constraints in fuzzy 𝒫(𝒩) and explain how semi‐automated feature model customization is performed in this setting. The model configuration derivation process that we propose respects the soundness and completeness properties. Copyright © 2011 John Wiley & Sons, Ltd.

Software Product Line Engineering (SPLE) is an approach for software reuse. It concerns to produce customized software products as atomic or composite services to be reused in SOA-based applications. A common set of artifacts is used to build these services in a planned and managed way. The main purpose of SPLE is to explore commonalities and variabilities. The SPLE approach provides a strategic software reuse that can produce quality Software as a Service (SaaS) while cutting cost and reducing time-to-market. This paper proposes a process to construct services as Software Product Lines by using Model Driven techniques. The process combines the use of maps, visual techniques for SPL modeling, especially features diagrams and MD techniques. In addition to the process, we have developed a tool to support map, feature, and class diagrams modeling.

IBED: Combining IBEA and DE for optimal feature selection in software product line engineering