Jeffrey C. Carver

The role of replications in Empirical Software Engineering

Replications play a key role in Empirical Software Engineering by allowing the community to build knowledge about which results or observations hold under which conditions. Therefore, not only can a replication that produces similar results as the original experiment be viewed as successful, but a replication that produce results different from those of the original experiment can also be viewed as successful. In this paper we identify two types of replications: exact replications, in which the procedures of an experiment are followed as closely as possible; and conceptual replications, in which the same research question is evaluated by using a different experimental procedure. The focus of this paper is on exact replications. We further explore them to identify two sub-categories: dependent replications, where researchers attempt to keep all the conditions of the experiment the same or very similar and independent replications, where researchers deliberately vary one or more major aspects of the conditions of the experiment. We then discuss the role played by each type of replication in terms of its goals, benefits, and limitations. Finally, we highlight the importance of producing adequate documentation for an experiment (original or replication) to allow for replication. A properly documented replication provides the details necessary to gain a sufficient understanding of the study being replicated without requiring the replicator to slavishly follow the given procedures.

An empirical methodology for introducing software processes

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.

A systematic literature review to identify and classify software requirement errors

Most software quality research has focused on identifying faults (i.e., information is incorrectly recorded in an artifact). Because software still exhibits incorrect behavior, a different approach is needed. This paper presents a systematic literature review to develop taxonomy of errors (i.e., the sources of faults) that may occur during the requirements phase of software lifecycle. This taxonomy is designed to aid developers during the requirement inspection process and to improve overall software quality. The review identified 149 papers from the software engineering, psychology and human cognition literature that provide information about the sources of requirements faults. A major result of this paper is a categorization of the sources of faults into a formal taxonomy that provides a starting point for future research into error-based approaches to improving software quality.

Replicating software engineering experiments: addressing the tacit knowledge problem

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.

Understanding the High-Performance-Computing Community: A Software Engineer's Perspective

Computational scientists developing software for HPC systems face unique software engineering issues. Attempts to transfer SE technologies to this domain must take these issues into account.

Characterizing software architecture changes: A systematic review

With todays ever increasing demands on software, software developers must produce software that can be changed without the risk of degrading the software architecture. One way to address software changes is to characterize their causes and effects. A software change characterization mechanism allows developers to characterize the effects of a change using different criteria, e.g. the cause of the change, the type of change that needs to be made, and the part of the system where the change must take place. This information then can be used to illustrate the potential impact of the change. This paper presents a systematic literature review of software architecture change characteristics. The results of this systematic review were used to create the Software Architecture Change Characterization Scheme (SACCS). This report addresses key areas involved in making changes to software architecture. SACCSs purpose is to identify the characteristics of a software change that will have an impact on the high-level software architecture.

Parallel Programmer Productivity: A Case Study of Novice Parallel Programmers

In developing High-Performance Computing (HPC) software, time to solution is an important metric. This metric is comprised of two main components: the human effort required developing the software, plus the amount of machine time required to execute it. To date, little empirical work has been done to study the first component: the human effort required and the effects of approaches and practices that may be used to reduce it. In this paper, we describe a series of studies that address this problem. We instrumented the development process used in multiple HPC classroom environments. We analyzed data within and across such studies, varying factors such as the parallel programming model used and the application being developed, to understand their impact on the development process.

Knowledge-Sharing Issues in Experimental 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. 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.

Program comprehension of domain-specific and general-purpose languages: comparison using a family of experiments

Domain-specific languages (DSLs) are often argued to have a simpler notation than general-purpose languages (GPLs), since the notation is adapted to the specific problem domain. Consequently, the impact of domain relevance on the creation of the problem representation is believed to improve programmers’ efficiency and accuracy when using DSLs compared with using similar solutions like application libraries in GPLs. Most of the common beliefs have been based upon qualitative conclusions drawn by developers. Rather than implementing the same problem in a DSL and in a GPL and comparing the efficiency and accuracy of each approach, developers often compare the implementation of a new program in a DSL to their previous experiences implementing similar programs in GPLs. Such a conclusion may or may not be valid. This paper takes a more skeptical approach to acceptance of those beliefs. By reporting on a family of three empirical studies comparing DSLs and GPLs in different domains. The results of the studies showed that when using a DSL, developers are more accurate and more efficient in program comprehension than when using a GPL. These results validate some of the long- held beliefs of the DSL community that until now were only supported by anecdotal evidence.

A checklist for integrating student empirical studies with research and teaching goals

The use of empirical studies with students in software engineering helps researchers gain insight into new or existing techniques and methods. However, due mainly to concerns of external validity, questions have been raised about the value of these types of studies. The authors of this paper draw on their experiences of conducting a large number of empirical studies in university courses in three countries (Italy, Norway, and the United States) to address this important issue. This paper first identifies the requirements that research and pedagogy place on a valid empirical study with students. This information is then used as the basis for a checklist that provides guidance for researchers and educators when planning and conducting studies in university courses. The goal of this checklist is to help ensure that these studies have as much research and pedagogical value as possible. Finally, an example application of the checklist is provided to illustrate its use.