Ricardo Britto

Effort estimation in agile software development: a systematic literature review

Context: Ever since the emergence of agile methodologies in 2001, many software companies have shifted to Agile Software Development (ASD), and since then many studies have been conducted to investigate effort estimation within such context; however to date there is no single study that presents a detailed overview of the state of the art in effort estimation for ASD. Objectives: The aim of this study is to provide a detailed overview of the state of the art in the area of effort estimation in ASD. Method: To report the state of the art, we conducted a systematic literature review in accordance with the guidelines proposed in the evidence-based software engineering literature. Results: A total of 25 primary studies were selected; the main findings are: i) Subjective estimation techniques (e.g. expert judgment, planning poker, use case points estimation method) are the most frequently applied in an agile context; ii) Use case points and story points are the most frequently used size metrics respectively; iii) MMRE (Mean Magnitude of Relative Error) and MRE (Magnitude of Relative Error) are the most frequently used accuracy metrics; iv) team skills, prior experience and task size are cited as the three important cost drivers for effort estimation in ASD; and v) Extreme Programming (XP) and SCRUM are the only two agile methods that are identified in the primary studies. Conclusion: Subjective estimation techniques, e.g. expert judgment-based techniques, planning poker or the use case points method, are the one used the most in agile effort estimation studies. As for the size metrics, the ones that were used the most in the primary studies were story points and use case points. Several research gaps were identified, relating to the agile methods, size metrics and cost drivers, thus suggesting numerous possible avenues for future work.

An Empirical Investigation on Effort Estimation in Agile Global Software Development

Effort estimation is a project management activity that is mandatory for the execution of software projects. Despite its importance, there have been just a few studies published on such activities within the Agile Global Software Development (AGSD) context. Their aggregated results were recently published as part of a secondary study that reported the state of the art on effort estimation in AGSD. This study aims to complement the above-mentioned secondary study by means of an empirical investigation on the state of the practice on effort estimation in AGSD. To do so, a survey was carried out using as instrument an on-line questionnaire and a sample comprising software practitioners experienced in effort estimation within the AGSD context. Results show that the effort estimation techniques used within the AGSD and collocated contexts remained unchanged, with planning poker being the one employed the most. Sourcing strategies were found to have no or a small influence upon the choice of estimation techniques. With regard to effort predictors, global challenges such as cultural and time zone differences were reported, in addition to factors that are commonly considered in the collocated context, such as team experience. Finally, many challenges that impact the accuracy of the effort estimates were reported by the respondents, such as problems with the software requirements and the fact that the communication effort between sites is not properly accounted.

Taxonomies in software engineering

Context: Software Engineering (SE) is an evolving discipline with new subareas being continuously developed and added. To structure and better understand the SE body of knowledge, taxonomies have been proposed in all SE knowledge areas.Objective: The objective of this paper is to characterize the state-of-the-art research on SE taxonomies.Method: A systematic mapping study was conducted, based on 270 primary studies.Results: An increasing number of SE taxonomies have been published since 2000 in a broad range of venues, including the top SE journals and conferences. The majority of taxonomies can be grouped into the following SWEBOK knowledge areas: construction (19.55%), design (19.55%), requirements (15.50%) and maintenance (11.81%). Illustration (45.76%) is the most frequently used approach for taxonomy validation. Hierarchy (53.14%) and faceted analysis (39.48%) are the most frequently used classification structures. Most taxonomies rely on qualitative procedures to classify subject matter instances, but in most cases (86.53%) these procedures are not described in sufficient detail. The majority of the taxonomies (97%) target unique subject matters and many taxonomy-papers are cited frequently. Most SE taxonomies are designed in an ad-hoc way. To address this issue, we have revised an existing method for developing taxonomies in a more systematic way.Conclusion: There is a strong interest in taxonomies in SE, but few taxonomies are extended or revised. Taxonomy design decisions regarding the used classification structures, procedures and descriptive bases are usually not well described and motivated.

Software Architects in Large-Scale Distributed Projects: An Ericsson Case Study

Software architects are key assets for successful development projects. However, not much research has investigated the challenges they face in large-scale distributed projects. So, researchers investigated how architects at Ericsson were organized, their roles and responsibilities, and the effort they spent guarding and governing a large-scale legacy product developed by teams at multiple locations. Despite recent trends such as microservices and agile development, Ericsson had to follow a more centralized approach to deal with the challenges of scale, distribution, and monolithic architecture of a legacy software product. So, the architectural decisions were centralized to a team of architects. The team extensively used code reviews to not only check the codes state but also reveal defects that could turn into maintainability problems. The study results also suggest that the effort architects spend designing architecture, guarding its integrity and evolvability, and mentoring development teams is directly related to team maturity. In addition, significant investment is needed whenever new teams and locations are onboarded.

A hybrid approach to suggest software product line portfolios

Graphical abstractDisplay Omitted HighlightsThe work proposes a hybrid approach to deal with the Product Portfolio Scope Problem.The approach is composed by a solution to deploy the feature relevance indicated by the customers into code assets of a SPL, based on a systematic method (SQFD).The approach includes a method to estimate the cost of an asset based on common and relevant measures related to source code, together with a fuzzy system to deal with the imprecision to set reference values.The work presents an application of an NSGA-II to search for products minimizing the cost and maximizing the relevance of the candidate products.The approach was evaluated using different scenarios, exploring the mains aspects related to method in the practice: size, granularity of features and products search space.The previous version of our hybrid approach was dependent on the employed technologies and algorithms. Herein we reformulate our approach, detaching it from any particular technique/algorithm.The data collection process associated with our approach was improved to facilitate the hybrid approachs usage and mitigate associated construct validity threats.A more comprehensive evaluation, which focused on show the real word usefulness and scalability of our hybrid approach. To validate the usefulness of our approach, it was used the SPL associated with a tool broadly employed in both industrial and academic contexts (ArgoUML-SPL). The scalability of our approach was evaluated using a synthetic SPL.All the experiments were based on the guidelines defined by Arcuri and Briand in order to evaluate the statistical significance of this kind of work. Software product line (SPL) development is a new approach to software engineering which aims at the development of a whole range of products. However, as long as SPL can be useful, there are many challenges regarding the use of that approach. One of the main problems which hinders the adoption of software product line (SPL) is the complexity regarding product management. In that context, we can remark the scoping problem. One of the existent ways to deal with scoping is the product portfolio scoping (PPS). PPS aims to define the products that should be developed as well as their key features. In general, that approach is driven by marketing aspects, like cost of the product and customer satisfaction. Defining a product portfolio by using the many different available aspects is a NP-hard problem. This work presents an improved hybrid approach to solve the feature model selection problem, aiming at supporting product portfolio scoping. The proposal is based in a hybrid approach not dependent on any particular algorithm/technology. We have evaluated the usefulness and scalability of our approach using one real SPL (ArgoUML-SPL) and synthetic SPLs. As per the evaluation results, our approach is both useful from a practitioners perspective and scalable.

Experiences from Measuring Learning and Performance in Large-Scale Distributed Software Development

Background: Developers and development teams in large-scale software development are often required to learn continuously. Organizations also face the need to train and support new developers and teams on-boarded in ongoing projects. Although learning is associated with performance improvements, experience shows that training and learning does not always result in a better performance or significant improvements might take too long. Aims: In this paper, we report our experiences from establishing an approach to measure learning results and associated performance impact for developers and teams in Ericsson. Method: Experiences reported herein are a part of an exploratory case study of an on-going large-scale distributed project in Ericsson. The data collected for our measurements included archival data and expert knowledge acquired through both unstructured and semi-structured interviews. While performing the measurements, we faced a number of challenges, documented in the form of lessons learned. Results: We aggregated our experience in eight lessons learned related to collection, preparation and analysis of data for further measurement of learning potential and performance in large-scale distributed software development. Conclusions: Measuring learning and performance is a challenging task. Major problems were related to data inconsistencies caused by, among other factors, distributed nature of the project. We believe that the documented experiences shared herein can help other researchers and practitioners to perform similar measurements and overcome the challenges of large-scale distributed software projects, as well as proactively address these challenges when establishing project measurement programs.

An extended global software engineering taxonomy

BackgroundIn Global Software Engineering (GSE), the need for a common terminology and knowledge classification has been identified to facilitate the sharing and combination of knowledge by GSE researchers and practitioners. A GSE taxonomy was recently proposed to address such a need, focusing on a core set of dimensions; however its dimensions do not represent an exhaustive list of relevant GSE factors. Therefore, this study extends the existing taxonomy, incorporating new GSE dimensions that were identified by means of two empirical studies conducted recently.MethodsTo address the research questions of this study, we used evidence found through a systematic literature review and a survey. Based on literature, new dimensions were added to the existing taxonomy.ResultsWe identified seven dimensions to extend and incorporate into the recently proposed GSE taxonomy. The resulting extended taxonomy was later on validated by comparing it with the existing taxonomy on which the extension is built and one additional taxonomy. We also demonstrated the utility of the extended taxonomy using it to classify eight finished real GSE projects. The extended taxonomy was representative enough to classify the projects in a clear way.ConclusionsThe extended taxonomy can help both researchers and practitioners by providing dimensions that can enable the description of different GSE contexts in a more comprehensive way; this can facilitate the understanding, comparison and aggregation of GSE-related findings.

Effort Estimation in Agile Global Software Development Context

Both Agile Software Development (ASD) and Global Software Development (GSD) are 21st century trends in the software industry. Many studies are reported in the literature wherein software companies have applied an agile method or practice GSD. Given that effort estimation plays a remarkable role in software project management, how do companies perform effort estimation when they use agile method in a GSD context? Based on two effort estimation Systematic Literature Reviews (SLR) - one in within the ASD context and the other in a GSD context, this paper reports a study in which we combined the results of these SLRs to report the state of the art of effort estimation in agile global software development (ASD) context.

Bloom's taxonomy in software engineering education: A systematic mapping study

Designing and assessing learning outcomes could be a challenging activity for any Software Engineering (SE) educator. To support the process of designing and assessing SE courses, educators have been applied the cognitive domain of Blooms taxonomy. However, to the best of our knowledge, the evidence on the usage of Blooms taxonomy in SE higher education has not yet been systematically aggregated or reviewed. Therefore, in this paper we report the state of the art on the usage of Blooms taxonomy in SE education, identified by conducted a systematic mapping study. As a result of the performed systematic mapping study, 26 studies were deemed as relevant. The main findings from these studies are: i) Blooms taxonomy has mostly been applied at undergraduate level for both design and assessment of software engineering courses; ii) software construction is the leading SE subarea in which Blooms taxonomy has been applied. The results clearly point out the usefulness of Blooms taxonomy in the SE education context. We intend to use the results from this systematic mapping study to develop a set of guidelines to support the usage of Blooms taxonomy cognitive levels to design and assess SE courses.

Effort estimation in large-scale software development: An industrial case study

Context: Software projects frequently incur schedule and budget overruns. Planning and estimation are particularlychallenging in large and globally distributed projects. While software engineering ...