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

Characterisation schema for selecting software testing techniques

The importance of properly selecting testing techniques is widely accepted in the software engineering community. However, there are chiefly two reasons why the selections now made by software developers cannot be classed as correct. Firstly, they have limited knowledge of all the techniques now available, which means that there are a lot of techniques with which the average developer is unfamiliar. Secondly, the information now available with regard to the different existing testing techniques is mostly procedural (that is, focused on how to use the technique), whereas there is almost no pragmatic information (focused on the result of using the technique). The open problem addressed in this research is precisely how to help developers improve software testing technique selection. A testing technique characterisation schema is proposed to achieve this objective. Being instantiated for multiple techniques, the schema can be used to build a repository containing information on testing techniques. This schema systematically describes all the testing techniques, focusing mainly on pragmatic aspects of the techniques, leading to more objective selections. The proposed characterisation schema is composed of a non-flat set of attributes, grouped around the elements of the testing process to which they refer. These elements are then grouped around the different testing process stages. This logical grouping makes the schema information coherent. An empirical and iterative process was followed to arrive at this schema. An empirical process was used, because testing techniques are not founded on a solid theoretical basis. This means that the schema needs to be founded not only on testing theory, but also on what the different subjects related to software testing know about techniques. It is iterative, because a schema based on the theory now existing on testing will be created. This schema is gradually refined with the knowledge of developers, researchers and experts in the area. The completed characterisation schema was evaluated in two different ways. Firstly, the schema is verified empirically by instantiating it for multiple testing techniques. Secondly, an experiment is carried out, in which the repository created in the earlier verification is put into use to select testing techniques for different projects. Finally, the original contribution of this research is a conceptual tool that can be used by developers to systematically and objectively select the testing techniques to be used in a software project

A systematic mapping study on testing technique experiments: has the situation changed since 2000?

Context: Empirical Software Engineering (ESE) replication researchers need to store and manipulate experimental data for several purposes, in particular analysis and reporting. Current research needs call for sharing and preservation of experimental data as well. In a previous work, we analyzed Replication Data Management (RDM) needs. A novel concept, called Experimental Ecosystem, was proposed to solve current deficiencies in RDM approaches. The empirical ecosystem provides replication researchers with a common framework that integrates transparently local heterogeneous data sources. A typical situation where the Empirical Ecosystem is applicable, is when several members of a research group, or several research groups collaborating together, need to share and access each other experimental results. However, to be able to apply the Empirical Ecosystem concept and deliver all promised benefits, it is necessary to analyze the software architectures and tools that can properly support it

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

Replications of software engineering experiments

There are many open issues that must be addressed before the replication process can be successfully formalized in empirical software engineering research. We define replication as the deliberate repetition of the same empirical study for the purpose of determining whether the results of the first experiment can be reproduced. This definition would appear at first glance to be good. However, it needs several clarifications that have not yet been forthcoming in software engineering: – What is the exact meaning of the same empirical study? Namely how similar should an experiment be to the baseline study for it to be considered a replication? What is the exact meaning of a result being reproduced? Namely how similar does a result have to be to the result of the baseline study for it to be considered reproduced? These and other methodological questions need to be researched and tailored for empirical software engineering

Comparing the effectiveness of equivalence partitioning, branch testing and code reading by stepwise abstraction applied by subjects

Some verification and validation techniques have been evaluated both theoretically and empirically. Most empirical studies have been conducted without subjects, passing over any effect testers have when they apply the techniques. We have run an experiment with students to evaluate the effectiveness of three verification and validation techniques (equivalence partitioning, branch testing and code reading by stepwise abstraction). We have studied how well able the techniques are to reveal defects in three programs. We have replicated the experiment eight times at different sites. Our results show that equivalence partitioning and branch testing are equally effective and better than code reading by stepwise abstraction. The effectiveness of code reading by stepwise abstraction varies significantly from program to program. Finally, we have identified project contextual variables that should be considered when applying any verification and validation technique or to choose one particular technique

Estudio de la Efectividad de Tres Técnicas de Evaluación de Código: Resultados de una Serie de Experimentos.

Hasta la fecha se han evaluado distintas técnicas de verificación y validación teórica y empíricamente. La mayoría de las evaluaciones empíricas se han llevado a cabo sin sujetos, abstrayendo el efecto del sujeto sobre la técnica a la hora de aplicarla. Hemos evaluado mediante un experimento con sujetos la efectividad de tres técnicas de verificación y validación de código: partición en clases de equivalencia, cobertura de decisión y lectura de código mediante abstracciones sucesivas, estudiando la capacidad de las técnicas para la detección de fallos en tres programas distintos. Hemos replicado el experimento ocho veces en cuatro entornos distintos. Los resultados arrojan diferencias entre las técnicas y señalan variables contextuales del proyecto software que deberían considerarse cuando se quiera elegir o aplicar una técnica de verificación y validación