Ramon Abilio

Detecting Code Smells in Software Product Lines -- An Exploratory Study

Code smells are symptoms that something is wrong in the source code. They have been catalogued and investigated in several programming techniques. These techniques can be used to develop Software Product Lines (SPL). However, feature-oriented programming (FOP) is a specific technique to deal with the modularization of features in SPL. One of the most popular FOP languages is AHEAD and, as far as we are concerned, we still lack systematic studies on the categorization and detection of code smells in AHEADFOP languages-based SPL. To fill this gap, this paper extends the definitions of three traditional code smells, namely God Method, God Class, and Shotgun Surgery, to take into account FOP abstractions. We then proposed 8 new FOP measures to quantify specific characteristics of compositional approaches like AHEAD. Finally, we combine the proposed and existing measures to define 3 detection strategies for identifying the investigated code smells. To evaluate the detection strategies, we performed an exploratory study involving 26 participants. The study participants rely on metrics to identify code smells in 8 AHEAD systems. Our results show that the proposed detection strategies can be used as code smell predictor since statistical tests indicate agreement among them and the study participants.

Software Variability Management: An Exploratory Study with Two Feature Modeling Tools

Software Product Line (SPL) is becoming widely adopted in industry due to its capability of minimizing costs and improving quality of software systems through systematic reuse of software artifacts. An SPL is a set of software systems sharing a common, managed set of features that satisfies the specific needs of a particular market segment. A feature represents an increment in functionality relevant to some stakeholders. There are several tools to support variability management by modeling features in SPL. However, it is hard for a developer to choose the most appropriate feature modeling tool due to the several options available. This paper presents the results of an exploratory study aiming to support SPL engineers choosing the feature modeling tool that best fits their needs. This exploratory study compares and analyzes two feature modeling tools, namely FeatureIDE and SPLOT, based on data from 56 participants that used the analyzed tools. In this study, we performed a four-dimension qualitative analysis with respect to common functionalities provided by feature modeling tools: (i) Feature Model Editor, (ii) Automated Analysis of Feature Models, (iii) Product Configuration, and (iv) Tool Notation. The main issues we observed in SPLOT are related to its interface. FeatureIDE, on the other hand, revealed some constraints when creating feature models.

Bad Smells in Software Product Lines: A Systematic Review

Software product line (SPL) is a set of software systems that share a common, managed set of features satisfying the specific needs of a particular market segment. Bad smells are symptoms that something may be wrong in system design. Bad smells in SPL are a relative new topic and need to be explored. This paper performed a Systematic Literature Review (SLR) to find and classify published work about bad smells in SPLs and their respective refactoring methods. Based on 18 relevant papers found in the SLR, we identified 70 bad smells and 95 refactoring methods related to them. The main contribution of this paper is a catalogue of bad smells and refactoring methods related to SPL.

A Systematic Review of Contemporary Metrics for Software Maintainability

Previous studies have been conducted with the aim of increasing the system quality. As a result, some contemporary technologies have been proposed for software development to improve maintainability, such as feature-oriented and aspect-oriented programming. Metrics are used to quantify the quality of systems developed in these technologies. Recently, contemporary metrics have been proposed or adapted from existing ones to evaluate specific issues of these contemporary technologies. This paper presents results of applying a systematic literature review to identify contemporary metrics associated with software maintainability and proposed for the feature-oriented and aspect-oriented technologies. Initially, we identify 672 published works and, after the primary selection, these quantity was reduced to 11 papers. These papers account for 33 and 78 contemporary metrics for feature-oriented and aspect-oriented technologies, respectively. The main contributions of this paper are (i) the list of metrics and measurable properties studies for feature-oriented and aspect-oriented programming, (ii) elaboration of a unified catalog of metrics applicable for both technologies, and (iii) identification of their main references.

Metrics for feature-oriented programming

Feature-oriented programming (FOP) is a programming technique to implement software product lines based on composition mechanisms called refinements. A software product line is a set of software systems that share a common, managed set of features satisfying the specific needs of a particular market segment. The literature reports various software metrics for software product lines developed using object-oriented and aspect-oriented programming. However, after a literature review, we observed that we lack the definition of FOP-specific metrics. Based on this observation, this paper proposes a set of eight novel metrics for feature-oriented programming. These metrics were derived both from our experience in FOP and from existing software metrics. We demonstrate the applicability of the proposed metrics by applying them to a software product line.

Managing reusable learning objects and experience reports in EduSE portal

There are initiatives to improve Software Engineering (SE) teaching and learning processes, but these are often isolated, because there is no appropriate channel for their dissemination in order to allow their use in similar contexts. In this sense, this paper presents an evolution of EduSE Portal aiming to store and manage these initiatives as learning objects (LOs) and experience reports in a repository, as well as coordinate the roles of stakeholders based on reuse processes. In the LOs repository, the SE researcher provides his/her initiative and a protocol that will guide the professor in LOs application in classroom. Thus, professors can search and retrieve LOs and researchers can get the community feedback. In the experience reports repository, researchers and professors perform the integration of their experiences and this exchange can improve both LOs application and evolution. An initial usability study is discussed, evaluating the infrastructure as a whole.

Systematic literature review supported by information retrieval techniques: A case study

Systematic Literature Review (SLR) is a means to synthesize relevant and high quality studies related to a specific topic or research questions. In general, a SLR has three phases, and the first one is the Primary Selection in which the selection of studies is usually performed manually reading title, abstract and keywords of each study. The number of published scientific studies has grown, increasing effort in carrying out this review. In this paper, we proposed two strategies to rank studies in decreasing order of importance, for a SLR, regarding the terms in the search string. These strategies are based on the Information Retrieval technique Vector Model. We implemented those strategies and conducted a case study to evaluate their applicability. As results, the second strategy presents 50% of precision on a recall of 80%. Among the contributions of this study, two strategies to rank relevant documents in a SLR, regarding the search string, were proposed and analyzed.

Applying Information Retrieval Techniques to Detect Duplicates and to Rank References in the Preliminary Phases of Systematic Literature Reviews

Systematic Literature Review (SLR) is a means to synthesize relevant and high quality studies related to a specific topic or research questions. In the Primary Selection stage of an SLR, the selection of studies is usually performed manually by reading title, abstract, and keywords of each study. In the last years, the number of published scientific studies has grown increasing the effort to perform this sort of reviews. In this paper, we proposed strategies to detect non-papers and duplicated references in results exported by search engines, and strategies to rank the references in decreasing order of importance for an SLR, regarding the terms in the search string. These strategies are based on Information Retrieval techniques. We implemented the strategies and carried out an experimental evaluation of their applicability using two real datasets. As results, the strategy to detect non-papers presented 100% of precision and 50% of recall; the strategy to detect duplicates detected more duplicates than the manual inspection; and one of the strategies to rank relevant references presented 50% of precision and 80% of recall. Therefore, the results show that the proposed strategies can minimize the effort in the Primary Selection stage of an SLR.

Identification and relationship between notation and tool for feature models with graphic representation

Feature models are composed of features and their relationships. They are used to represent the common features and variabilities of a Software Product Line (SPL). Many proposals for notations and tools to feature models can be found in the literature. Thus, the choosing the notation and the tool that best fits the needs of the software engineer is a hard task. This paper shows a study on which tools allow to represent some notations. Fifteen notations were identified and compared, which are related to five tools. The eight attributes of notations related to tools are: graphical structure, type of features (mandatory, optional, and external), type of decomposition (OR, XOR, and AND) and cross restrictions. In the analysis, notations, attributes, and tools were related. As main contribution, we presented a relationship between tools and notations of feature models that can assist in the choice of one notation/tool for modeling a domain.

Usability Evaluation of a Web System for Spatially Oriented Audio Descriptions of Images Addressed to Visually Impaired People

This paper describes a web system designed to provide spatially oriented audio descriptions of an image for visually impaired users. The system uses a hardware-independent platform of the technique of multimodal presentation of images. Visually impaired users interact with an image displayed on the screen while moving the cursor – with a mouse or a tablet (pen or finger touch) – and listening to the audio description of previously marked areas within the image. The paper also describes the usability evaluation performed with five participants and its main results. Generally, the five participants accomplished the usability test tasks and could better understand the image displayed. The paper also describes the main findings and discusses some implications for design, suggesting some improvements.