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Software requirements are often described in natural language because they are useful to communicate and validate. Due to their focus on particular facets of a system, this kind of specifications tends to keep relevant concerns (also known as early aspects) from the analysts’ view. These concerns are known as crosscutting concerns because they appear scattered among documents. Concern mining tools can help analysts to uncover concerns latent in the text and bring them to their attention. Nonetheless, analysts are responsible for vetting tool-generated solutions, because the detection of concerns is currently far from perfect. In this article, we empirically investigate the role of analysts in the concern vetting process, which has been little studied in the literature. In particular, we report on the behavior and performance of 55 subjects in three case-studies working with solutions produced by two different tools, assessed in terms of binary classification measures. We discovered that analysts can improve “bad” solutions to a great extent, but performed significantly better with “good” solutions. We also noticed that the vetting time is not a decisive factor to their final accuracy. Finally, we observed that subjects working with solutions substantially different from those of existing tools (better recall) can also achieve a good performance. Fil: Rago, Alejandro Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto de Investigación en Ciencias de La Salud; Argentina Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto de Investigación en Ciencias de La Salud; Argentina Fil: Marcos, Claudia Andrea. Universidad Nacional del Centro de la Provincia de Buenos Aires; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Providing recommendations to groups of users has become a promising research area, since many items tend to be consumed by groups of people. Various techniques have been developed aiming at making recommendations to a group as a whole. Most works use aggregation techniques to combine preferences, recommendations or profiles. However, satisfying all group members in an even way still remains as a challenge. To deal with this problem, we propose an extension of a multi-agent approach based on negotiation techniques for group recommendation. In the approach, we use the multilateral Monotonic Concession Protocol (MCP) to combine individual recommendations into a group recommendation. In this work, we extend the MCP protocol to allow users to personalize the behavior of the agents. This extension was evaluated in two different domains (movies and points of interest) with satisfactory results. We compared our approach against different baselines, namely: a preference aggregation algorithm, a recommendation aggregation algorithm, and a simple one-step negotiation. The results show evidence that, when using our negotiation approach, users in the groups are more uniformly satisfied than with traditional aggregation approaches. Fil: Villavicencio, Christian Paulo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Monteserin, Ariel José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina

Technical debt indexes are metrics for assessing the quality of a software system. Both academic and commercial tools have begun to provide computations of such indexes based on design violations and smells (e.g., cycles among system elements). When computing a debt index for a given project, a common use case is that engineers look at the index values for spotting design issues that negatively affect system evolution and quality. In this context, those smells being critical for the system architecture should be promptly identified soastoe valuate proper remediation actions. However, the interpretation of an index value in terms of problematic smells is usually a manual and labor-intensive task for engineers. To help with this task, we propose a tool called Sen4Smells that performs an automated sensitivity analysis for a given debt index based on the evolution of both the index values and the corresponding smells across (past) system versions. The Sen4Smells output is a ranking of smells that, due to their variations or instability, are major contributors to the debt index, and thus, can impact on architecture quality. Sen4Smells is designed as a pipeline that combines information from existing tools for smell detection, predefined d ebt i ndex f ormulas, and the Sobol method for sensitivity analysis. As a demonstration of the tool functionality, we briefly present implementations for the Arcan and Sonargraph tools with their respective debt indexes.

Providing recommendations to groups of users has become popular in many applications today. Although several group recommendation techniques exist, the generation of items that satisfy all group members in an even way still remains a challenge. To this end, we have developed a multi-agent approach called PUMAS-GR that relies on negotiation techniques to improve group recommendations. We applied PUMAS-GR to the movies domain, and used the monotonic concession protocol to reach a consensus on the movies proposed to a group. Fil: Villavicencio, Christian Paulo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Monteserin, Ariel José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina

Service-Oriented Architecture (SOA) has become a dominant approach for developing distributed enterprise-wide applications. Most organizations capitalize on SOA by discovering and reusing services already accessible over the Internet. In addition to functional requirements, the implementation of a SOA design must consider quality-attribute properties (e.g., performance, interoperability or security, among others), which require developers to explore and assess candidate solutions fulfilling the same functional requirements. This exploration is usually driven by architectural knowledge and SOA principles, but it can be a time-consuming and error-prone process, even for expert developers. To deal with this issue, we present a case-based reasoning approach called AWESOME to assist developers in exploring different development alternatives, by modeling quality-attribute aspects and SOA design patterns as cases. Our approach has been evaluated with four case-studies, and the results have shown that the solutions generated by AWESOME are judged as satisfactory by a number of SOA experts. Fil: Rodríguez, Guillermo Horacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Soria, Alvaro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina

Some of the challenges faced by most software projects are tight budget constraints and schedules, which often make managers and developers prioritize the delivery of a functional product over other engineering activities, such as software documentation. In particular, having little or low-quality documentation of the software architecture of a system can have negative consequences for the project, as the architecture is the main container of the key design decisions to fulfill the stakeholders' goals. To further complicate this situation, generating and maintaining architectural documentation is a non-trivial and time-consuming activity. In this context, we present a tool approach that aims at i assisting the documentation writer in their tasks and ii ensuring a cost-effective documentation process by means of optimization techniques. Our tool, called SADHelper, follows the principle of producing reader-oriented documentation, in order to focus the available, and often limited, resources on generating just enough documentation that satisfies the stakeholders' concerns. The approach was evaluated in two experiments with users of software architecture documents, with encouraging results. These results show evidence that our tool can be useful to reduce the documentation costs and even improve the documentation quality, as perceived by their stakeholders. Copyright © 2015 John Wiley & Sons, Ltd.

Code smells are a popular mechanism to find structural design problems in software systems. Consequently, several tools have emerged to support the detection of code smells. However, the number of smells returned by current tools usually exceeds the amount of problems that the developer can deal with, particularly when the effort available for performing refactorings is limited. Moreover, not all the code smells are equally relevant to the goals of the system or its health. This article presents a semi-automated approach that helps developers focus on the most critical problems of the system. We have developed a tool that suggests a ranking of code smells, based on a combination of three criteria, namely: past component modifications, important modifiability scenarios for the system, and relevance of the kind of smell. These criteria are complementary and enable our approach to assess the smells from different perspectives. Our approach has been evaluated in two case-studies, and the results show that the suggested code smells are useful to developers. Fil: Vidal, Santiago Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Marcos, Claudia Andrea. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina

A key challenge of software architecture design is how to satisfy quality-attribute requirements, which often conflict with each other. This is usually a complex task, because there are several candidates for architectural solutions meeting the same requirements, and quality-attribute tradeoffs of those solutions need to be considered by the architects. In this context, we present the SQuAT framework to assist architects in the exploration of design solutions and their tradeoffs. This framework provides a modular approach for integrating quality-attribute analyzers and solvers, and also features a distributed search-based optimization. In this paper, we report on an experience using SQuAT with Palladio architectural models, which integrates third-party tools for performance and modifiability, and shows the tradeoffs among candidate solutions to the architect. Furthermore, we enhance the standard search schema of SQuAT with a distributed negotiation technique based on monotonic concession, in order to provide better tradeoffs for the architect's decision making.

A key aspect of software architecture design is to satisfy quality-attribute requirements, such as performance or modifiability. This is usually a complex task, because there are often several candidate solutions meeting the same requirements, and the quality-attribute tradeoffs of those solutions need to be considered by architects. In previous work, we developed an agent-based approach called DesignBots to assist architects in the exploration of design solutions driven by quality attributes. The agents performed a local search, each one optimizing a particular quality, but they were limited regarding tradeoff analysis capabilities. In this paper, we propose negotiation techniques for improving the tradeoff analysis of the agents, inspired by how human architects (and stakeholders) normally work in real-life projects when assessing alternative designs. In particular, we develop two negotiation strategies that integrate with the DesignBots framework. The experimental results obtained so far with an architectural case-study show that the negotiation can produce more satisfying tradeoffs than those currently provided by DesignBots.

Developing high-quality requirements specifications often demands a thoughtful analysis and an adequate level of expertise from analysts. Although requirements modeling techniques provide mechanisms for abstraction and clarity, fostering the reuse of shared functionality (e.g., via UML relationships for use cases), they are seldom employed in practice. A particular quality problem of textual requirements, such as use cases, is that of having duplicate pieces of functionality scattered across the specifications. Duplicate functionality can sometimes improve readability for end users, but hinders development-related tasks such as effort estimation, feature prioritization, and maintenance, among others. Unfortunately, inspecting textual requirements by hand in order to deal with redundant functionality can be an arduous, time-consuming, and error-prone activity for analysts. In this context, we introduce a novel approach called ReqAligner that aids analysts to spot signs of duplication in use cases in an automated fashion. To do so, ReqAligner combines several text processing techniques, such as a use case-aware classifier and a customized algorithm for sequence alignment. Essentially, the classifier converts the use cases into an abstract representation that consists of sequences of semantic actions, and then these sequences are compared pairwise in order to identify action matches, which become possible duplications. We have applied our technique to five real-world specifications, achieving promising results and identifying many sources of duplication in the use cases. Fil: Rago, Alejandro Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Marcos, Claudia Andrea. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Sistemas Tandil; Argentina Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina

Textual requirements are very common in software projects. However, this format of requirements often keeps relevant concerns (e.g., performance, synchronization, data access, etc.) from the analyst's view because their semantics are implicit in the text. Thus, analysts must carefully review requirements documents in order to identify key concerns and their effects. Concern mining tools based on NLP techniques can help in this activity. Nonetheless, existing tools cannot always detect all the crosscutting effects of a given concern on different requirements sections, as this detection requires a semantic analysis of the text. In this work, we describe an automated tool called REAssistant that supports the extraction of semantic information from textual use cases in order to reveal latent crosscutting concerns. To enable the analysis of use cases, we apply a tandem of advanced NLP techniques (e.g, dependency parsing, semantic role labeling, and domain actions) built on the UIMA framework, which generates different annotations for the use cases. Then, REAssistant allows analysts to query these annotations via concern-specific rules in order to identify all the effects of a given concern. The REAssistant tool has been evaluated with several case-studies, showing good results when compared to a manual identification of concerns and a third-party tool. In particular, the tool achieved a remarkable recall regarding the detection of crosscutting concern effects.

Finding software faults is a problematic activity in many systems. Existing approaches usually work close to the system implementation and require developers to perform different code analyses. Although these approaches are effective, the amount of information to be managed by developers is often overwhelming. This problem calls for complementary approaches able to work at higher levels of abstraction than code, helping developers to keep intellectual control over the system when analyzing faults. In this context, we present an expert-system approach, called FLABot, which assists developers in fault-localization tasks by reasoning about faults using software architecture models. We have evaluated a prototype of FLABot in two medium-size case studies, involving novice and non-novice developers. We compared time consumed, code browsed and faults found by these developers, with and without the support of FLABot, observing interesting effort reductions when applying FLABot. The results and lessons learned have shown that our approach is practical and reduces the efforts for finding individual faults. Fil: Soria, Alvaro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina Fil: Campo, Marcelo Ricardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina

Providing recommendation to groups of users has become a promising research area, since many items tend to be consumed by groups of people. Various techniques have been developed aiming at making recommendations to the group as a whole, but satisfying all group members in an even way still remains as a challenge. We propose a multi-agent approach based on negotiation techniques for group recommendation. In this approach we use the multilateral monotonic concession protocol to combine individual recommendations into a group recommendation. We applied our proposal in the movies domain. The results obtained indicate that using this negotiation protocol, users in the groups were more evenly satisfied than with traditional ranking aggregation approaches.

Information hiding is a positive consequence of properly defining component interfaces. Unfortunately, determining what should constitute a public interface remains difficult. We have analyzed over 3.6 million lines of Java open-source code and found that on the average, at least 20 % of defined methods are over-exposed, thus threatening public interfaces to unnecessary exposure. Such over-exposed methods may have their accessibility reduced to exactly reflect the method usage. We have identified three patterns in the source code to identify over-exposed methods. We also propose an Eclipse plugin to guide practitioners in identifying over-exposed methods and refactoring their applications. Our plugin has been successfully used to refactor a non-trivial application. Fil: Vidal, Santiago Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Bergel, Alexandre. Universidad de Chile; Chile Fil: Marcos, Claudia Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina

The Software Architecture is an important asset in a software development process, which serves to share and discuss the main design concerns among the project stakeholders. The architecture must be properly documented (e.g., via a Wiki environment) to be effectively used by these stakeholders. However, the process of producing architecture documentation often fails to deliver contents that address the stakeholders’ information needs. To address the problem, we argue for a knowledge management strategy in which: (i) architecture documentation is created incrementally; and (ii) its contents are driven by a model of stakeholder preferences. In this work, we present an information optimization approach applied to the architecture documentation domain, derived from an existing documentation method called Views & Beyond. To do so, we define the Next SAD Version Problem (NSVP) and then provide tool support to assist architects in producing cost-effective documentation. Based on prior work, we perform a sensitivity analysis of the optimization model and develop a robust formulation that takes into account uncertainty in the parameter estimations for NSVP instances, thus improving the outcomes of our documentation assistant. Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Villavicencio, Christian Paulo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Nicoletti, Matías Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina Fil: Vázquez, Hernán Ceferino. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina

Code smells are a popular mechanism to identify structural design problems in software systems. Since it is generally not feasible to f x all the smells arising in the code, some of them are often postponed by developer s to be resolved in the future. One reason for this decision is that the improvement of the code structure, to achieve modifability goals, requires extra effort from developer s. Therefore, they might not always spend this additional effort, particularly when they are focused on delivering customer-visible features. This postponement of code smells are seen as a source of technical debt. Furthermore, not all the code smells may be urgent to f x in the context of the system's modifability and business goals. While there are a number of tools to detect smells, they do not allow developer s to discover the most urgent smells according to their goals. In this article, we present a fexible tool to prioritize technical debt in the form of code smells. The tool is fexible to allow developer s to add new smell detection strategies and to prioritize smells, and groups of smells, based on the confguration of their manifold criteria. To illustrate this fexibility, we present an application example of our tool. The results suggest that our tool can be easily extended to be aligned with the developer's goals.

Quality-attribute requirements describe constraints on the development and behavior of a software system, and their satisfaction is key for the success of a software project. Detecting and analyzing quality attributes in early development stages provides insights for system design, reduces risks, and ultimately improves the developers? understanding of the system. A common problem, however, is that quality-attribute information tends to be understated in requirements specifications and scattered across several documents. Thus, making the quality attributes first-class citizens becomes usually a time-consuming task for analysts. Recent developments have made it possible to mine concerns semi-automatically from textual documents. Leveraging on these ideas, we present a semiautomated approach to identify latent quality attributes that works in two stages. First, a mining tool extracts early aspects from use cases, and then these aspects are processed to derive candidate quality attributes. This derivation is based on an ontology of quality-attribute scenarios. We have built a prototype tool called QAMiner to implement our approach. The evaluation of this tool in two case studies from the literature has shown interesting results. As main contribution, we argue that our approach can help analysts to skim requirements documents and quickly produce a list of potential quality attributes for the system. Fil: Rago, Alejandro Miguel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina Fil: Diaz Pace, Jorge Andres. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina Fil: Marcos, Claudia Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil. Instituto Superior de Ingenieria del Software; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina

Software architectures are very important to capture early design decisions and reason about quality attributes of a system. Unfortunately, there are mismatches between the quality attributes prescribed by the architecture and those realized by its object-oriented implementation. The mismatches decrease the ability to reason architecturally about the system. Developing an object-oriented materialization that conforms to the original architecture depends on both the application of the right patterns and the developer's expertise. Since the space of allowed materializations can be really large, tool support for assisting the developer in the exploration of alternative materializations is of great help. In previous research, we developed a prototype for generating quality-preserving implementations of software architectures, using pre-compiled knowledge about architectural styles and frameworks. In this paper, we present a more flexible approach, called SAME, which focuses on the architectural connectors as the pillars for the materialization process. The SAME design assistant applies a case-based reasoning (CBR) metaphor to deal with connector-related materialization experiences and quality attributes. The CBR engine is able to recall and adapt past experiences to solve new materialization problems; thus SAME can take advantage of developers' knowledge. Preliminary experiments have shown that this approach can improve the exploration of object-oriented solutions that are still faithful to the architectural prescriptions.

Developing high-quality requirements specifications often demands a thoughtful analysis and an adequate level of expertise from analysts. Although requirements modeling techniques provide mechanisms for abstraction and clarity, fostering the reuse of shared functionality (e.g., via UML relationships for use cases), they are seldom employed in practice. A particular quality problem of textual requirements, such as use cases, is that of having duplicate pieces of functionality scattered across the specifications. Duplicate functionality can sometimes improve readability for end users, but hinders development-related tasks such as effort estimation, feature prioritization and maintenance, among others. Unfortunately, inspecting textual requirements by hand in order to deal with redundant functionality can be an arduous, time-consuming and error-prone activity for analysts. In this context, we introduce a novel approach called ReqAligner that aids analysts to spot signs of duplication in use cases in an automated fashion. To do so, ReqAligner combines several text processing techniques, such as a use-case-aware classifier and a customized algorithm for sequence alignment. Essentially, the classifier converts the use cases into an abstract representation that consists of sequences of semantic actions, and then these sequences are compared pairwise in order to identify action matches, which become possible duplications. We have applied our technique to five real-world specifications, achieving promising results and identifying many sources of duplication in the use cases.