Applying the experimental paradigm to software engineering

En este keynote, la Prof. Juristo describe el paradigma experimental y cómo podría aplicarse a la ingeniería del software, destacando los desafíos de su aplicación y los logros conseguidos hasta el momento

Basics on design and analysis of SE experiments: widespread shortcomings

Keynote speech about experimental desig

Design Patterns in Software Maintenance: An Experiment Replication at UPM - Experiences with the RESER'11 Joint Replication Project

Replication of software engineering experiments is crucial for dealing with validity threats to experiments in this area. Even though the empirical software engineering community is aware of the importance of replication, the replication rate is still very low. The RESER'11 Joint Replication Project aims to tackle this problem by simultaneously running a series of several replications of the same experiment. In this article, we report the results of the replication run at the Universidad Politécnica de Madrid. Our results are inconsistent with the original experiment. However, we have identified possible causes for them. We also discuss our experiences (in terms of pros and cons) during the replication

Reporting experiments to satisfy professionals information needs

Although the aim of empirical software engineering is to provide evidence for selecting the appropriate technology, it appears that there is a lack of recognition of this work in industry. Results from empirical research only rarely seem to find their way to company decision makers. If information relevant for software managers is provided in reports on experiments, such reports can be considered as a source of information for them when they are faced with making decisions about the selection of software engineering technologies. To bridge this communication gap between researchers and professionals, we propose characterizing the information needs of software managers in order to show empirical software engineering researchers which information is relevant for decision-making and thus enable them to make this information available. We empirically investigated decision makers? information needs to identify which information they need to judge the appropriateness and impact of a software technology. We empirically developed a model that characterizes these needs. To ensure that researchers provide relevant information when reporting results from experiments, we extended existing reporting guidelines accordingly.We performed an experiment to evaluate our model with regard to its effectiveness. Software managers who read an experiment report according to the proposed model judged the technology?s appropriateness significantly better than those reading a report about the same experiment that did not explicitly address their information needs. Our research shows that information regarding a technology, the context in which it is supposed to work, and most importantly, the impact of this technology on development costs and schedule as well as on product quality is crucial for decision makers

Enriching Requirements Analysis with the Personas Technique

A thorough understanding of the users that interact with the system is necessary to develop usable systems. The Personas technique developed by the human-computer interaction (HCI) discipline gathers data about users, gains an understanding of their characteristics, defines fictitious personas based on this understanding and focuses on these personas throughout the software development process. The aim of our research is to build Personas into systems development following software engineering (SE) guidelines. The benefits to be gained are an understanding of the user which is not traditionally taken into account in SE. To do this, we had to undertake two types of tasks. First, we modified the Personas technique to conform to the levels of systematization common in SE. We have called the modified technique PersonaSE. Second, we incorporated the proposed technique into the software requirements analysis proces

Determining the effectiveness of three software evaluation techniques through informal aggregation

An accepted fact in software engineering is that software must undergo verification and validation process during development to ascertain and improve its quality level. But there are too many techniques than a single developer could master, yet, it is impossible to be certain that software is free of defects. So, it is crucial for developers to be able to choose from available evaluation techniques, the one most suitable and likely to yield optimum quality results for different products. Though, some knowledge is available on the strengths and weaknesses of the available software quality assurance techniques but not much is known yet on the relationship between different techniques and contextual behavior of the techniques. Objective: This research investigates the effectiveness of two testing techniques ? equivalence class partitioning and decision coverage and one review technique ? code review by abstraction, in terms of their fault detection capability. This will be used to strengthen the practical knowledge available on these techniques

Understanding replication of experiments in software engineering: a classification

Context: Replication plays an important role in experimental disciplines. There are still many uncertain- ties about how to proceed with replications of SE experiments. Should replicators reuse the baseline experiment materials? How much liaison should there be among the original and replicating experiment- ers, if any? What elements of the experimental configuration can be changed for the experiment to be considered a replication rather than a new experiment? Objective: To improve our understanding of SE experiment replication, in this work we propose a classi- fication which is intend to provide experimenters with guidance about what types of replication they can perform. Method: The research approach followed is structured according to the following activities: (1) a litera- ture review of experiment replication in SE and in other disciplines, (2) identification of typical elements that compose an experimental configuration, (3) identification of different replications purposes and (4) development of a classification of experiment replications for SE. Results: We propose a classification of replications which provides experimenters in SE with guidance about what changes can they make in a replication and, based on these, what verification purposes such a replication can serve. The proposed classification helped to accommodate opposing views within a broader framework, it is capable of accounting for less similar replications to more similar ones regarding the baseline experiment. Conclusion: The aim of replication is to verify results, but different types of replication serve special ver- ification purposes and afford different degrees of change. Each replication type helps to discover partic- ular experimental conditions that might influence the results. The proposed classification can be used to identify changes in a replication and, based on these, understand the level of verification

Effect of domain knowledge on elicitation effectiveness: an internally replicated controlled experiment

Context. Requirements elicitation is a highly communicative activity in which human interactions play a critical role. A number of analyst characteristics or skills may influence elicitation process effectiveness. Aim. Study the influence of analyst problem domain knowledge on elicitation effectiveness. Method. We executed a controlled experiment with post-graduate students. The experimental task was to elicit requirements using open interview and consolidate the elicited information immediately afterwards. We used four different problem domains about which students had different levels of knowledge. Two tasks were used in the experiment, whereas the other two were used in an internal replication of the experiment; that is, we repeated the experiment with the same subjects but with different domains. Results. Analyst problem domain knowledge has a small but statistically significant effect on the effectiveness of the requirements elicitation activity. The interviewee has a big positive and significant influence, as does general training in requirements activities and interview experience. Conclusion. During early contacts with the customer, a key factor is the interviewee; however, training in tasks related to requirements elicitation and knowledge of the problem domain helps requirements analysts to be more effectiv