Guilherme Horta Travassos

Cross versus Within-Company Cost Estimation Studies: A Systematic Review

The objective of this paper is to determine under what circumstances individual organizations would be able to rely on cross-company-based estimation models. We performed a systematic review of studies that compared predictions from cross-company models with predictions from within-company models based on analysis of project data. Ten papers compared cross-company and within-company estimation models; however, only seven presented independent results. Of those seven, three found that cross-company models were not significantly different from within-company models, and four found that cross-company models were significantly worse than within-company models. Experimental procedures used by the studies differed making it impossible to undertake formal meta-analysis of the results. The main trend distinguishing study results was that studies with small within-company data sets (i.e.,

A survey on model-based testing approaches: a systematic review

20 projects) that used leave-one-out cross validation all found that the within-company model was significantly different (better) from the cross-company model. The results of this review are inconclusive. It is clear that some organizations would be ill-served by cross-company models whereas others would benefit. Further studies are needed, but they must be independent (i.e., based on different data bases or at least different single company data sets) and should address specific hypotheses concerning the conditions that would favor cross-company or within-company models. In addition, experimenters need to standardize their experimental procedures to enable formal meta-analysis, and recommendations are made in Section 3.

Detecting defects in object-oriented designs: using reading techniques to increase software quality

This paper describes a systematic review performed on model-based testing (MBT) approaches. A selection criterion was used to narrow the initially identified four hundred and six papers to focus on seventy-eight papers. Detailed analysis of these papers shows where MBT approaches have been applied, the characteristics, and the limitations. The comparison criteria includes representation models, support tools, test coverage criteria, the level of automation, intermediate models, and the complexity. This paper defines and explains the review methodology and presents some results.

Towards an Ontology of software maintenance

Inspections can be used to identify defects in software artifacts. In this way, inspection methods help to improve software quality, especially when used early in software development. Inspections of software design may be especially crucial since design defects (problems of correctness and completeness with respect to the requirements, internal consistency, or other quality attributes) can directly affect the quality of, and effort required for, the implementation. We have created a set of “reading techniques” (so called because they help a reviewer to “read” a design artifact for the purpose of finding relevant information) that gives specific and practical guidance for identifying defects in Object-Oriented designs. Each reading technique in the family focuses the reviewer on some aspect of the design, with the goal that an inspection team applying the entire family should achieve a high degree of coverage of the design defects. In this paper, we present an overview of this new set of reading techniques. We discuss how some elements of these techniques are based on empirical results concerning an analogous set of reading techniques that supports defect detection in requirements documents. We present an initial empirical study that was run to assess the feasibility of these new techniques, and discuss the changes made to the latest version of the techniques based on the results of this study.

An empirical methodology for introducing software processes

SUMMARY We suggest that empirical studies of maintenance are difficult to understand unless the context of the study is fully defined. We developed a preliminary ontology to identify a number of factors that influence maintenance. The purpose of the ontology is to identify factors that would affect the results of empirical studies. We present the ontology in the form of a UML model. Using the maintenance factors included in the ontology, we define two common maintenance scenarios and consider the industrial issues associated with them. Copyright

Replicating software engineering experiments: addressing the tacit knowledge problem

There is a growing interest in empirical study in software engineering, both for validating mature technologies and for guiding improvements of less-mature technologies. This paper introduces an empirical methodology, based on experiences garnered over more than two decades of work by the Empirical Software Engineering Group at the University of Maryland and related organizations, for taking a newly proposed improvement to development processes from the conceptual phase through transfer to industry. The methodology presents a series of questions that should be addressed, as well as the types of studies that best address those questions. The methodology is illustrated by a specific research program on inspection processes for Object-Oriented designs. Specific examples of the studies that were performed and how the methodology impacted the development of the inspection process are also described.

Scientific research ontology to support systematic review in software engineering

Recently the awareness of the importance of replicating studies has been growing in the empirical software engineering community. The results of any one study cannot simply be extrapolated to all environments because there are many uncontrollable sources of variation between different environments. In our work, we have reasoned that the availability of laboratory packages for experiments can encourage better replications and complementary studies. However, even with effectively specified laboratory packages, transfer of experimental know-how can still be difficult. A cooperation between Brazilian and American researchers addressing effective running of replications was formed in 1999. One of the specific issues being addressed is the problem of transferring tacit knowledge. We discuss what we learned about the tacit knowledge transfer problem and the evolution of laboratory packages in the description of a replication performed in Brazil using a PBR (Perspective Based Reading) laboratory package; also how further issues are addressed.

Knowledge-Sharing Issues in Experimental Software Engineering

The term systematic review is used to refer to a specific methodology of research, developed in order to gather and evaluate the available evidence pertaining to a focused topic. It represents a secondary study that depends on primary study results to be accomplished. Several primary studies have been conducted in the field of Software Engineering in the last years, determining an increasing improvement in methodology. However, in most cases software is built with technologies and processes for which developers have insufficient evidence to confirm their suitability, limits, qualities, costs, and inherent risks. Conducting systematic reviews in Software Engineering consists in a major methodological tool to scientifically improve the validity of assertions that can be made in the field and, as a consequence, the reliability degree of the methods that are employed for developing software technologies and supporting software processes. This paper aims at discussing the significance of experimental studies, particularly systematic reviews, and their use in supporting software processes. A template designed to support systematic reviews in Software Engineering is presented, and the development of ontologies to describe knowledge regarding such experimental studies is also introduced.

Supporting risks in software project management

Recently the awareness of the importance of replicating studies has been growing in the empirical software engineering community. The results of any one study cannot simply be extrapolated to all environments because there are many uncontrollable sources of variation between different environments.In our work, we have reasoned that the availability of laboratory packages for experiments can encourage better replications and complementary studies. However, even with effectively specified laboratory packages, transfer of experimental know-how can still be difficult. In this paper, we discuss the collaboration structures we have been using in the Readers’ Project, a bilateral project supported by the Brazilian and American national science agencies that is investigating replications and transfer of experimental know-how issues. In particular, we discuss how these structures map to the Nonaka–Takeuchi knowledge sharing model, a well-known paradigm used in the knowledge management literature. We describe an instantiation of the Nonaka–Takeuchi Model for software engineering experimentation, establishing a framework for discussing knowledge sharing issues related to experimental software engineering. We use two replications to illustrate some of the knowledge sharing issues we have faced and discuss the mechanisms we are using to tackle those issues in Readers’ Project.

Towards supporting the life cycle of large scale scientific experiments

Complex software development is a risky job. The number of unsuccessful projects surpasses the number of successful developments, particularly when large projects are analyzed. This paper describes an approach to develop, retrieve, and reuse management knowledge and experience concerned with software development risks. Scenarios are used to model risk impact and resolution strategies efficacy within risk archetypes. A risk archetype is an information structure that holds knowledge about software development risks. A risk management process organizes the use of risk archetypes within an application development effort. The process resembles a reuse process framework, where two sub-processes are respectively responsible for identifying and reusing risk information. Simulating the impact of the expected risks can support some of the decisions throughout the software development process. The contribution of this paper is to show how risk archetypes and scenario models can represent reusable project management knowledge. An observational analysis of applying such an approach in an industrial environment and a feasibility study are also described.