In many cases, software artifacts share similarity across projects and development teams. However, often this similarity is only partially reflected on the level of design and implementation, and therefore the possibilities for its detection are limited in current variability analysis, clone detection, and application search approaches. In this paper, we propose a method for identification and comparison of similarly behaving software. The method, supported by a prototype tool, analyzes the behavioral similarity of object-oriented code artifacts based on shallow (behavior interface) and deep (behavior transformation) descriptions of the exhibited operations. It further recommends on suitable mechanisms inspired by the notion of polymorphism in order to guide and support current and future reuse. The approach was evaluated on two data-sets, obtained following two different scenarios: clone-and-own and independent development by different teams.

As software becomes more complex, reusing and integrating artifacts from existing projects that may be taken from open or organization-proprietary repositories is becoming an increasingly important practice. This practice requires an in-depth understanding of the projects to be reused and particularly their common and variable features and their non-functional requirements. Different approaches have been suggested to analyze similarity and variability of different kinds of artifacts (mainly, requirements and code), e.g., clone detection and feature mining. These approaches, however, mainly address functional aspects of the software artifacts, while mostly neglecting aspects dictated by non-functional requirements. The recent progress with the General Data Protection Regulation (GDPR) highlights the importance of handling privacy concerns in software development. However, existing approaches do not directly refer to privacy challenges in software reuse. In this paper we propose integrating these two lines of research and introduce a privacy-aware software reuse approach. Particularly, we suggest to extend VarMeR – Variability Mechanisms Recommender – which analyzes software similarity based on exhibited behaviors and recommends on polymorphism-inspired reuse mechanisms, with privacy awareness considerations. These considerations are reflected in “privacy levels” of the reused artifacts.

Adoption of Software Product Line Engineering (SPLE) to support systematic reuse of software-related artifacts within product families is challenging, time-consuming and error-prone. Analyzing the variability of existing artifacts needs to reflect different perspectives and preferences of stakeholders in order to facilitate decisions in SPLE adoption. Considering that requirements drive many development methods and activities, we introduce an approach to analyze variability of behaviors as presented in functional requirements. The approach, called semantic and ontological variability analysis (SOVA), uses ontological and semantic considerations to automatically analyze differences between initial states (preconditions), external events (triggers) that act on the system, and final states (post-conditions) of behaviors. The approach generates feature diagrams typically used in SPLE to model variability. Those diagrams are organized according to perspective profiles, reflecting the needs and preferences of the potential stakeholders for given tasks. We conducted an empirical study to examine the usefulness of the approach by comparing it to an existing tool which is mainly based on a latent semantic analysis measurement. SOVA appears to create outputs that are more comprehensible in significantly shorter times. These results demonstrate SOVA's potential to allow for flexible, behavior-oriented variability analysis.

In this tutorial we will review some ways to automate domain modeling and discuss the boundaries of automation in this context. We will concentrate on an ontological and conceptual approach which examines software behaviors and not just domain terminology and semantic similarity. We will show and demonstrate a tool named SOVA -- Semantic and Ontological Variability Analysis, which supports automatic domain modeling from software requirements written in free text. We will further discuss how the existence of different SPLs in the same domain may improve the domain models through cross product line analysis.

As the complexity and variety of systems and software products have increased, the ability to manage their variability effectively and efficiently became crucial. To this end, variability can be specified either as an integral part of the development artifacts or in a separate orthogonal variability model. Lately, orthogonal variability models attract a lot of attention due to the fact that they do not require changing the complexity of the development artifacts and can be used in conjunction with different development artifacts. Despite this attention and to the best of our knowledge, no empirical study examined the comprehensibility of orthogonal variability models.

Situational methods are approaches to the development of software systems that are designed and constructed to fit particular circumstances that often refer to project characteristics. One common way to create situational methods is to reuse method components, which are the building blocks of development methods. For this purpose, method components must be stored in a method base, and then retrieved and composed specifically for the situation in hand. Most approaches in the field of situational method engineering require the expertise of method engineers to support the retrieval and composition of method components. Furthermore, this is usually done in an ad-hoc manner and for pre-defined situations. In this paper, the authors propose an approach, supported by a tool that creates situational methods semi-automatically. This approach refers to structural and behavioral considerations and a wide variety of characteristics when comparing method components and composing them into situational methods. The resultant situational methods are stored in the method base for future usage and composition. Based on an experimental study of the approach, the authors show that it provides correct and suitable draft situational methods, which human evaluators have assessed as relevant for the given situations.

Design patterns provide reusable solutions for recurring design problems. They constitute an important tool for improving software quality. However, correct usage of design patterns depends to a large extent on the designer. Design patterns often include models that describe the suggested solutions, while other aspects of the patterns are neglected or described informally only in text. Furthermore, design pattern solutions are usually described in an object-oriented fashion that is too close to the implementation, masking the essence of and motivation behind a particular design pattern. We suggest an approach to modeling the different aspects of design patterns and semi-automatically utilizing these models to improve software design. Evaluating our approach on commonly used design patterns and a case study of an automatic application for composing, taking, checking, and grading analysis and design exams, we found that the suggested approach successfully locates the main design problems modeled by the selected design patterns.

Reference models are an important aid for business process modeling and design. Their aim is to capture domain knowledge and assist in the design of enterprise-specific business processes. The application of reference models for process design requires guidance in reusing these models and flexibility in adapting them to specific enterprises. One popular modeling language for specifying reference models is event-driven process chain (EPC), which has been extended to express configurable reference models, i.e., configurable EPC (C–EPC). These models provide explicit reuse guidance but allow a limited level of flexibility following a reuse by configuration approach. To increase the level of adaptability of reference models, in this paper, we propose to utilize the application-based domain modeling (ADOM) approach to specify and apply reference models by using EPC. ADOM supports the enforcement of reference model constraints while allowing high levels of flexibility, adaptability, and variability in the business processes of particular enterprises. This paper presents the syntax and semantics of the proposed approach, called ADOM–EPC, and its specialization and configuration capabilities. ADOM–EPC is evaluated by comparing it to C–EPC, a leading approach for reference modeling and reuse, in terms of expressiveness and comprehensibility. Although the expressiveness of ADOM–EPC, i.e., its set of specified reuse operations, exceeds that of C–EPC, the understandability of the two types of reference models is similar.

UML has been largely adopted as a standard modeling language. The emergence of UML from different modeling languages that refer to various system aspects causes a wide variety of completeness and correctness problems in UML models. Several methods have been proposed for dealing with correctness issues, mainly providing internal consistency rules but ignoring correctness and completeness with respect to the system requirements and the domain constraints. In this article, we propose addressing both completeness and correctness problems of UML models by adopting a domain analysis approach called application-based domain modeling (ADOM). We present experimental results from our study which checks the quality of application models when utilizing ADOM on UML. The results advocate that the availability of the domain model helps achieve more complete models without reducing the comprehension of these models.

Web service discovery is one of the main applications of semantic Web services, which extend standard Web services with semantic annotations. Current discovery solutions were developed in the context of automatic service composition. Thus, the “client” of the discovery procedure is an automated computer program rather than a human, with little, if any, tolerance to inexact results. However, in the real world, services which might be semantically distanced from each other are glued together using manual coding. In this article, we propose a new retrieval model for semantic Web services, with the objective of simplifying service discovery for human users. The model relies on simple and extensible keyword-based query language and enables efficient retrieval of approximate results, including approximate service compositions. Since representing all possible compositions and all approximate concept references can result in an exponentially-sized index, we investigate clustering methods to provide a scalable mechanism for service indexing. Results of experiments, designed to evaluate our indexing and query methods, show that satisfactory approximate search is feasible with efficient processing time.

As system complexity has increased, so has interest in reusing software components in early development phases. While most current modeling methods support design of generic parameterized frameworks or patterns and weaving them into specific models, they do not support open reuse, i.e., the ability to develop partially specified components and refine them in the target application. We introduce an open reuse formalism that is based on OPM/Web, an extension of object-process methodology for distributed systems and Web applications. Our open reuse is accomplished by a three-step process, consisting of designing reusable models, creating basic woven models, and enhancing their specification. We model a reusable component through partially specified environmental elements that are bound to concrete counterparts when the component is integrated into the system under development. Rules for modeling and combining components are defined and applied to a Web example.