Érica Ferreira de Souza

Using Forward Snowballing to update Systematic Reviews in Software Engineering

Background: A Systematic Literature Review (SLR) is a methodology used to aggregate relevant evidence related to one or more research questions. Whenever new evidence is published after the completion of a SLR, this SLR should be updated in order to preserve its value. However, updating SLRs involves significant effort. Objective: The goal of this paper is to investigate the application of forward snowballing to support the update of SLRs. Method: We compare outcomes of an update achieved using the forward snowballing versus a published update using the search-based approach, i.e., searching for studies in electronic databases using a search string. Results: Forward snowballing showed a higher precision and a slightly lower recall. It reduced in more than five times the number of primary studies to filter however missed one relevant study. Conclusions: Due to its high precision, we believe that the use of forward snowballing considerably reduces the effort in updating SLRs in Software Engineering; however the risk of missing relevant papers should not be underrated.

Knowledge management initiatives in software testing: A mapping study

Abstract Context Software testing is a knowledge intensive process, and, thus, Knowledge Management (KM) principles and techniques should be applied to manage software testing knowledge. Objective This study conducts a survey on existing research on KM initiatives in software testing, in order to identify the state of the art in the area as well as the future research. Aspects such as purposes, types of knowledge, technologies and research type are investigated. Method The mapping study was performed by searching seven electronic databases. We considered studies published until December 2013. The initial resulting set was comprised of 562 studies. From this set, a total of 13 studies were selected. For these 13, we performed snowballing and direct search to publications of researchers and research groups that accomplished these studies. Results From the mapping study, we identified 15 studies addressing KM initiatives in software testing that have been reviewed in order to extract relevant information on a set of research questions. Conclusions Although only a few studies were found that addressed KM initiatives in software testing, the mapping shows an increasing interest in the topic in the recent years. Reuse of test cases is the perspective that has received more attention. From the KM point of view, most of the studies discuss aspects related to providing automated support for managing testing knowledge by means of a KM system. Moreover, as a main conclusion, the results show that KM is pointed out as an important strategy for increasing test effectiveness, as well as for improving the selection and application of suited techniques, methods and test cases. On the other hand, inadequacy of existing KM systems appears as the most cited problem related to applying KM in software testing.

Using Ontology Patterns for Building a Reference Software Testing Ontology

Software testing is a critical process for achieving product quality. Its importance is more and more recognized, and there is a growing concern in improving the accomplishment of this process. In this context, Knowledge Management emerges as an important supporting tool. However, managing relevant knowledge to reuse is difficult and it requires some means to represent and to associate semantics to a large volume of test information. In order to address this problem, we have developed a Reference Ontology on Software Testing (ROost). ROost is built reusing ontology patterns from the Software Process Ontology Pattern Language (SP-OPL). In this paper, we discuss how ROost was developed, and present a fragment of Roost that concerns with software testing process, its activities, artifacts, and procedures.

ROoST: Reference Ontology on Software Testing

Software testing is a complex and critical process for achieving product quality. Its importance has been increasing and well recognized, and there is a growing concern in improving the accomplishment of this process. In this context, Knowledge Management (KM) emerged as an important supporting approach to improve the software testing process. However, managing relevant testing knowledge requires effective means to represent and to associate semantics to a large volume of testing information. To address this concern, we have developed a Reference Ontology on Software Testing (ROoST). ROoST establishes a common conceptualization about the software testing domain, which can serve several KM-related purposes, such as defining a common vocabulary for knowledge workers with respect to the testing domain, structuring testing knowledge repositories, annotating testing knowledge items, and for making search for relevant information easier. In this paper, we present ROoST, and we discuss how it was developed using two ontology pattern languages. Moreover, we discuss how we evaluated ROoST following four complementary approaches: assessment by humans, data-driven evaluation, ontology testing, and application-based evaluation.

Using the Findings of a Mapping Study to Conduct a Research Project: A Case in Knowledge Management in Software Testing

A mapping study provides a broad overview of a research area in order to determine whether there is research evidence on a particular topic. Results of a systematic mapping may identify suitable areas for performing future research. In this paper, we discuss our experience in using the findings of a mapping study on Knowledge Management (KM) in Software Testing for performing a real research project, which also applied other empirical approaches. The main goals of this paper are: (i) to reinforce the importance of a systematic mapping in the conduction of a research project by discussing a real case of such application, and (ii) to present the results of our survey on the most important aspects of KM when applied to software testing.

Tool support for generating model-based test cases via web

Testing activities play an important role in order to obtain high quality software products. These activities become more important when considering critical software, for instance, space application software. Nowadays, there is an extensive collaboration among space institutions. So, it is more than natural to expect distributed development of software and software testing activities. Therefore, a collaborative tool hosted on the internet becomes quite useful. In this respect, WEB-PerformCharts 2.0 tool discussed in this paper moves in this direction. The tool focuses on supporting a single aspect of distributed software development: the activity of generating test cases via web. Moreover, it allows model-based test case generation by means of formal methods formal languages statecharts and FSM which are considered state of the art in software development. WEB-PerformCharts 2.0 can be used to generate test cases for any kind of reactive systems modelled in statecharts or FSM. We present three case studies in different application domains to demonstrate the feasibility of our tool.

H-Switch Cover: a new test criterion to generate test case from finite state machines

Test cases generation based on Finite State Machines (FSMs) has been addressed for quite some time. Model-based testing has drawn attention from researchers and practitioners as one of the approaches to support software verification and validation. Several test criteria have been proposed in the literature to generate test cases based on formal methods, such as FSM. However, there is still a lot to be done on this aspect in order to clearly direct a test designer to choose a test criterion most suitable to generate test cases for a certain application domain. This work presents a new test criterion for model-based test case generation based on FSM, H-Switch Cover. H-Switch Cover relies on the traditional Switch Cover test criterion, but H-Switch Cover uses new heuristics to improve its performance, for example, adoption of rules to optimize graph balancing and traverse the graph for test cases generation. We conducted an investigation of cost and efficiency of this new test criterion by comparing it with unique input/output and distinguishing sequence. We used two embedded software products (space application software products) and mutation analysis for assessing efficiency. In general, for the case studies proposed in this paper in terms of cost (amount of events) and efficiency (mutation score), H-Switch Cover test criterion presented an average and a standard deviation better than the other two test criteria.

Evaluating strategies for forward snowballing application to support secondary studies updates: emergent results

Context: Secondary studies should be updated from time to time to include new evidence to preserve their value. It is recognized that one search technique to update secondary studies is forward snowballing and that the number of studies identified is dependent on the electronic databases selected. However, there is no consensus on what electronic database is most appropriate for applying forward snowballing. Objective: The main goal of this study is to evaluate the use of different electronic databases for applying forward snowballing to update secondary studies. Method: Six updates were performed using forward snowballing with support from two electronic databases, one specific (IEEE Xplore) and the other generic (Google Scholar) and three combinations were evaluated to obtain new evidence during secondary studies updating: (1) searching using Google Scholar as electronic database; (2) searching using IEEE Xplore as electronic database; and (3) searching using both, IEEE Xplore and Google Scholar as complementary electronic databases. Results: The use of a specific electronic database is not indicated for forward snowballing application to update SLRs, since many relevant studies may not be identified. However, the use of a generic database is sufficient to discover the majority of the studies. Conclusions: The emergent contribution of our work to the body of knowledge in the SLR field is to add empirical evidence regarding the use of different electronic databases to support forward snowballing application during secondary studies updates. These results should help reviewers when they decide to find evidences to update their SLRs.

Using meta-ethnography to synthesize research on knowledge management and agile software development methodology

Context: Software development processes are considered as knowledge intensive and therefore Knowledge Management (KM) can be applied to efficiently manage the knowledge generated. Agile practices can benefit the software organizations in terms of KM. Some studies have already presented evidence about this relationship. However, the intersection of these two areas still require further more clarification. Objective: This study aims to synthesize research on KM and Agile Software Development (ASD) using the meta-ethnography method. Method: In order to achieve the proposed goal, first, we applied the seven phases of meta-ethnography analysis method on a five articles selected from a tertiary study on KM and ASD. Second, the relations identified between the areas investigated were analysed from interviews with three agile development methodology experts. Results: A relation map that summarizes the synthesis identified between KM, agile values and scrum activities was created. Conclusion: There is a significant contribution in KM and ASD for both software engineering academics and industry.

Knowledge Management Diagnostics in Software Development Organizations: a Systematic Literature Review

Context: Managing knowledge is one of the main challenges for software development organizations. Thus, the principles of Knowledge Management (KM) are presented as determinant and effective factors for the software product quality. There are several approaches to applying KM in an organization. However, for a KM approaches to succeed, it is important to conduct a KM diagnostic in order to analyze the KM current state that already exists in the organization. Objective: The objective of this paper is to present the results of a Systematic Literature Review (SLR) conducted to summarize existing research on KM diagnostic in software development organizations. Method: SLR was performed by searching four electronic databases. We also performed backward snowballing from reference lists of selected studies. Results: From the SLR, we identified 24 studies addressing investigated differents approaches related to KM diagnostics in software development organizations. Conclusion: Based on our results we conclude that in the software engineering context the KM diagnosis practice still does not seem consolidated.