A data collection case study supporting requirements oriented prediction and management in software developments

Consider the statement "this project should cost X and has risk of Y". Such statements are used daily in industry as the basis for making decisions. The work reported here is part of a study aimed at providing a rational and pragmatic basis for such statements. Of particular interest are predictions made in the requirements and early phases of projects. A preliminary model has been constructed using Bayesian Belief Networks and in support of this, a programme to collect and study data during the execution of various software development projects commenced in May 2002. The data collection programme is undertaken under the constraints of a commercial industrial regime of multiple concurrent small to medium scale software development projects. Guided by pragmatism, the work is predicated on the use of data that can be collected readily by project managers; including expert judgements, effort, elapsed times and metrics collected within each project.

A pointcut-based coverage analysis approach for aspect-oriented programs

Aspect-oriented programming (AOP) is a promising technology that supports separation of crosscutting concerns (i.e., functionality that tends to be tangled with, and scattered through the rest of the system). In AOP, a method-like construct named advice is applied to join points in the system through a special construct named pointcut. This mechanism supports the modularization of crosscutting behavior; however, since the added interactions are not explicit in the source code, it is hard to ensure their correctness. To tackle this problem, this paper presents a rigorous coverage analysis approach to ensure exercising the logic of each advice - statements, branches, and def-use pairs - at each affected join point. To make this analysis possible, a structural model based on Java bytecode - called PointCut-based Del-Use Graph (PCDU) - is proposed, along with three integration testing criteria. Theoretical, empirical, and exploratory studies involving 12 aspect-oriented programs and several fault examples present evidence of the feasibility and effectiveness of the proposed approach. (C) 2010 Elsevier Inc. All rights reserved.

Fault Coverage-Driven Incremental Test Generation

In this paper, we consider a classical problem of complete test generation for deterministic finite-state machines (FSMs) in a more general setting. The first generalization is that the number of states in implementation FSMs can even be smaller than that of the specification FSM. Previous work deals only with the case when the implementation FSMs are allowed to have the same number of states as the specification FSM. This generalization provides more options to the test designer: when traditional methods trigger a test explosion for large specification machines, tests with a lower, but yet guaranteed, fault coverage can still be generated. The second generalization is that tests can be generated starting with a user-defined test suite, by incrementally extending it until the desired fault coverage is achieved. Solving the generalized test derivation problem, we formulate sufficient conditions for test suite completeness weaker than the existing ones and use them to elaborate an algorithm that can be used both for extending user-defined test suites to achieve the desired fault coverage and for test generation. We present the experimental results that indicate that the proposed algorithm allows obtaining a trade-off between the length and fault coverage of test suites.

A transformational language for mutant description

Mutation testing has been used to assess the quality of test case suites by analyzing the ability in distinguishing the artifact under testing from a set of alternative artifacts, the so-called mutants. The mutants are generated from the artifact under testing by applying a set of mutant operators, which produce artifacts with simple syntactical differences. The mutant operators are usually based on typical errors that occur during the software development and can be related to a fault model. In this paper, we propose a language-named MuDeL (MUtant DEfinition Language)-for the definition of mutant operators, aiming not only at automating the mutant generation, but also at providing precision and formality to the operator definition. The proposed language is based on concepts from transformational and logical programming paradigms, as well as from context-free grammar theory. Denotational semantics formal framework is employed to define the semantics of the MuDeL language. We also describe a system-named mudelgen-developed to support the use of this language. An executable representation of the denotational semantics of the language is used to check the correctness of the implementation of mudelgen. At the very end, a mutant generator module is produced, which can be incorporated into a specific mutant tool/environment. (C) 2008 Elsevier Ltd. All rights reserved.

Uma abordagem sistemática para implementação, gerenciamento e customização de testes de linhas de produto de software

Through the adoption of the software product line (SPL) approach, several benefits are achieved when compared to the conventional development processes that are based on creating a single software system at a time. The process of developing a SPL differs from traditional software construction, since it has two essential phases: the domain engineering - when common and variables elements of the SPL are defined and implemented; and the application engineering - when one or more applications (specific products) are derived from the reuse of artifacts created in the domain engineering. The test activity is also fundamental and aims to detect defects in the artifacts produced in SPL development. However, the characteristics of an SPL bring new challenges to this activity that must be considered. Several approaches have been recently proposed for the testing process of product lines, but they have been shown limited and have only provided general guidelines. In addition, there is also a lack of tools to support the variability management and customization of automated case tests for SPLs. In this context, this dissertation has the goal of proposing a systematic approach to software product line testing. The approach offers: (i) automated SPL test strategies to be applied in the domain and application engineering, (ii) explicit guidelines to support the implementation and reuse of automated test cases at the unit, integration and system levels in domain and application engineering; and (iii) tooling support for automating the variability management and customization of test cases. The approach is evaluated through its application in a software product line for web systems. The results of this work have shown that the proposed approach can help the developers to deal with the challenges imposed by the characteristics of SPLs during the testing process

POPT: uma abordagem de ensino de programação orientada a problema e testes

There is a growing interest of the Computer Science education community for including testing concepts on introductory programming courses. Aiming at contributing to this issue, we introduce POPT, a Problem-Oriented Programming and Testing approach for Introductory Programming Courses. POPT main goal is to improve the traditional method of teaching introductory programming that concentrates mainly on implementation and neglects testing. POPT extends POP (Problem Oriented Programing) methodology proposed on the PhD Thesis of Andrea Mendonça (UFCG). In both methodologies POPT and POP, students skills in dealing with ill-defined problems must be developed since the first programming courses. In POPT however, students are stimulated to clarify ill-defined problem specifications, guided by de definition of test cases (in a table-like manner). This paper presents POPT, and TestBoot a tool developed to support the methodology. In order to evaluate the approach a case study and a controlled experiment (which adopted the Latin Square design) were performed. In an Introductory Programming course of Computer Science and Software Engineering Graduation Programs at the Federal University of Rio Grande do Norte, Brazil. The study results have shown that, when compared to a Blind Testing approach, POPT stimulates the implementation of programs of better external quality the first program version submitted by POPT students passed in twice the number of test cases (professor-defined ones) when compared to non-POPT students. Moreover, POPT students submitted fewer program versions and spent more time to submit the first version to the automatic evaluation system, which lead us to think that POPT students are stimulated to think better about the solution they are implementing. The controlled experiment confirmed the influence of the proposed methodology on the quality of the code developed by POPT students

Uma ferramenta de análise automatizada de técnicas de seleção de testes de regressão baseada em mineração de repositórios de software

The main goal of Regression Test (RT) is to reuse the test suite of the latest version of a software in its current version, in order to maximize the value of the tests already developed and ensure that old features continue working after the new changes. Even with reuse, it is common that not all tests need to be executed again. Because of that, it is encouraged to use Regression Tests Selection (RTS) techniques, which aims to select from all tests, only those that reveal faults, this reduces costs and makes this an interesting practice for the testing teams. Several recent research works evaluate the quality of the selections performed by RTS techniques, identifying which one presents the best results, measured by metrics such as inclusion and precision. The RTS techniques should seek in the System Under Test (SUT) for tests that reveal faults. However, because this is a problem without a viable solution, they alternatively seek for tests that reveal changes, where faults may occur. Nevertheless, these changes may modify the execution flow of the algorithm itself, leading some tests no longer exercise the same stretch. In this context, this dissertation investigates whether changes performed in a SUT would affect the quality of the selection of tests performed by an RTS, if so, which features the changes present which cause errors, leading the RTS to include or exclude tests wrongly. For this purpose, a tool was developed using the Java language to automate the measurement of inclusion and precision averages achieved by a regression test selection technique for a particular feature of change. In order to validate this tool, an empirical study was conducted to evaluate the RTS technique Pythia, based on textual differencing, on a large web information system, analyzing the feature of types of tasks performed to evolve the SUT