Model-Based Filtering of Combinatorial Test Suites

International audienceTobias is a combinatorial test generation tool which can efficiently generate a large number of test cases by unfolding a test pattern and computing all combinations of parameters. In this paper, we first propose a model-based testing approach where Tobias test cases are first run on an executable UML/OCL specification. This animation of test cases on a model allows to filter out invalid test sequences produced by blind enumeration, typically the ones which violate the pre-conditions of operations, and to provide an oracle for the valid ones. We then introduce recent extensions of the Tobias tool which support an incremental unfolding and filtering process, and its associated toolset. This allows to address explosive test patterns featuring a large number of invalid test cases, and only a small number of valid ones. For instance, these new constructs could mandate test cases to satisfy a given predicate at some point or to follow a given behavior. The early detection of invalid test cases improves the calculation time of the whole generation and execution process, and helps fighting combinatorial explosion

A survey on test suite reduction frameworks and tools

Software testing is a widely accepted practice that ensures the quality of a System under Test (SUT). However, the gradual increase of the test suite size demands high portion of testing budget and time. Test Suite Reduction (TSR) is considered a potential approach to deal with the test suite size problem. Moreover, a complete automation support is highly recommended for software testing to adequately meet the challenges of a resource constrained testing environment. Several TSR frameworks and tools have been proposed to efficiently address the test-suite size problem. The main objective of the paper is to comprehensively review the state-of-the-art TSR frameworks to highlights their strengths and weaknesses. Furthermore, the paper focuses on devising a detailed thematic taxonomy to classify existing literature that helps in understanding the underlying issues and proof of concept. Moreover, the paper investigates critical aspects and related features of TSR frameworks and tools based on a set of defined parameters. We also rigorously elaborated various testing domains and approaches followed by the extant TSR frameworks. The results reveal that majority of TSR frameworks focused on randomized unit testing, and a considerable number of frameworks lacks in supporting multi-objective optimization problems. Moreover, there is no generalized framework, effective for testing applications developed in any programming domain. Conversely, Integer Linear Programming (ILP) based TSR frameworks provide an optimal solution for multi-objective optimization problems and improve execution time by running multiple ILP in parallel. The study concludes with new insights and provides an unbiased view of the state-of-the-art TSR frameworks. Finally, we present potential research issues for further investigation to anticipate efficient TSR frameworks

Test Generation and Evaluation from High-Level Properties for Common Criteria Evaluations - The TASCCC Testing Tool

International audienceIn this paper, we present a model-based testing tool resulting from a research project, named TASCCC. This tool is a complete tool chain dedicated to property-based testing in UML/OCL, that integrates various technologies inside a dedicated Eclipse plug-in. The test properties are expressed in a dedicated language based on property patterns. These properties are then used for two purposes. First, they can be employed to evaluate the relevance of a test suite according to specific coverage criteria. Second, it is possible to generate test scenarios that will illustrate or exercise the property. These test scenarios are then unfolded and animated on the Smartesting's CertifyIt model animator, that is used to filter out infeasible sequences. This tool has been used in industrial partnership, aiming at providing an assistance for Common Criteria evaluations, especially by providing test generation reports used to show the link between the test cases and the Common Criteria artefacts

Enhancing Formal Modelling Tool Support with Increased Automation

Progress report for the qualification exam report for PhD Student Kenneth Lausdahl. Initial work on enhancing tool support for the formal method VDM and the concept of unifying a abstract syntax tree with the ability for isolated extensions is described. The tool support includes a connection to UML and a test automation principle based on traces written as a kind of regular expressions

Applying TSR techniques over large test suites

Tese de mestrado em Engenharia Informática (Engenharia de Software) Universidade de Lisboa, Faculdade de Ciências, 2020Com o aumento da necessidade de garantir a qualidade do software criado atualmente, tem sido cada vez mais indispensável dedicar parte do tempo de desenvolvimento (por vezes mais de metade) a testar o código desenvolvido. Apesar da elevada importˆancia desta tarefa, é uma atividade que algumas vezes é ignorada ou negligenciada, devido a ser um trabalho por vezes monótono e cansativo. Esta é uma área bastante explorada por investigadores que tentam, de diversas maneiras, automatizar algum deste processo e, também, reduzir o tempo e recursos necessários para efetuar esta tarefa. Nomeadamente, considera-se a proposta de técnicas de redução de testes e ferramentas que as implementem, com o objetivo de agilizar esta tarefa, eliminando casos de testes desnecessários sem comprometer a cobertura dada pelo conjunto de testes original, bem como técnicas de prioritização de testes, que reorganizam conjuntos de testes com o objetivo de executar os mais relevantes (de acordo com um determinado critério) primeiramente, aumentando assim a sua capacidade de atingir algum objetivo. Neste contexto, destacam-se os testes de regressão, que permitem testar alterações ao software, verificando se as funcionalidades antigas continuam a funcionar com as alterações feitas. Salientam-se estes testes na medida em que são considerados o tipo de testes de software mais cansativo, comportando elevados custos e não evidenciando ganho claros a curto-prazo e, consequentemente, beneficiando particularmente das técnicas descritas anteriormente. Com o surgimento destas técnicas, é inevitável surgirem algumas comparações, tentando escolher as que melhor se adequam a diferentes necessidades. O objetivo deste trabalho consiste em dar resposta a duas questões, particularmente interessantes dado o estado de arte atual: “Qual a melhor ferramenta de redução de testes?”(de acordo com parâmetros pré-definidos) e “Se uma ferramenta de prioritização de testes for modificada, pode substituir de forma eficiente uma ferramenta de redução de testes?”. Para realizar a presente dissertação, foi estudado um grupo de ferramentas de redução de testes, de forma a ter uma melhor noção do estado de arte atual. Apesar de inicialmente terem sido encontradas onze ferramentas que poderiam vir a ser usadas com este propósito, os testes realizados, assim como as propriedades de algumas ferramentas, restringiram a utilização da maioria delas, Assim, foram consideradas três ferramentas: Evo- Suite, Testler e Randoop. De forma a tornar o objetivo deste trabalho mais enriquecido, foi também estudada uma ferramenta de prioritização de testes, Kanonizo. Para respondermos às questões apresentadas, foi desenvolvida uma ferramenta que integra o conjunto de ferramentas de redução de testes seleccionado e que, dado um conjunto de projetos open-source, aplica as técnicas destas ferramentas a cada um destes, efetuando assim a redução dos seus testes. Seguidamente, a ferramenta desenvolvida utiliza a ferramenta de prioritização Kanonizo para obter uma lista dos vários testes, ordenados consoante a sua importância; finalmente, são eliminados os testes menos importantes, segundo um valor pré-definido. De seguida, utilizando uma ferramenta de análise de código, neste caso a OpenClover, são recolhidas métricas referentes a cada conjunto de testes, para os projetos originais e igualmente para cada um dos reduzidos. Estas são depois utilizadas para avaliar a eficácia da redução para cada ferramenta. A eficácia da redução pode ser influenciada por diversos fatores. No caso da nossa ferramenta, foram considerados o tamanho do ficheiro de testes, o número de testes, o tempo de execução dos mesmos, a percentagem de cobertura total do código e a percentagem de cobertura de “ramos”no código. Por este motivo, decidiu-se adotar uma metodologia de Multi-Criteria Decision-Making, mais especificamente a Analytic Hierarchy Process que, segundo diversos critérios e valores de importância definidos entre eles, deduz a prioridade que cada critério deve ter ao tentar atingir um objetivo comum, isto é, que peso tem cada critério no cálculo da pontuação de cada ferramenta. Após a finalização e aperfeiçoamento da ferramenta, foram realizadas experiências que nos permitiram analisar a eficácia de cada ferramenta. Dada a facilidade de configuração da ferramenta, foram efetuadas diversas análises às reduções efetuadas pelas ferramentas, alterando a importância de cada critério considerado, visando verificar de que maneira estes influenciavam a escolha da melhor ferramenta. As pontuações de cada ferramenta de redução foram calculadas para seis cenários diferentes: um que replicasse as necessidades do ”mundo real”, dando portanto mais importância ao tempo de execução dos testes e cobertura atingida do que à dimensão dos testes em si; e um focando toda a importância para cada um dos sub-critérios definidos. Cada um destes cenários foi feito duas vezes - uma com os testes gerados pelo EvoSuite, e outra com os testes já existentes - com o objetivo de averiguar se as ferramentas de redução teriam um comportamento semelhante na presença de testes gerados automaticamente ou por humanos. Ignorando a ferramenta de prioritização, e tendo em conta o facto de que a EvoSuite só poderia ser usada com testes gerados por si mesma, a ferramenta de redução que teve uma melhor pontuação foi a Testler, o que responde à nossa primeira questão do estudo. Quanto à segunda questão, apesar dos resultados terem mostrado indubitavelmente que a Kanonizo obteve pontuações melhores que as outras ferramentas analisadas, esta é uma questão susceptível à influência de diversos fatores. No contexto das experiências efetuadas, podemos dizer que a Kanonizo pode substituir qualquer uma das ferramentas de redução e, confiando nas pontuações, fazer um trabalho mais eficaz. No entanto, num contexto mais abrangente, torna-se difícil responder a esta questão sem considerar um número mais elevado de ferramentas de redução de testes. Para mais, dependendo do algoritmo utilizado na ferramenta de prioritização, a redução feita por nós pode não ter qualquer critério (no caso de algoritmos random), o que faria essencialmente com que estivéssemos a apagar métodos aleatoriamente, podendo causar grandes perdas em termos de cobertura de código. Quando falamos de “substituir”uma ferramenta de redução por uma de prioritização com uma abordagem semelhante à nossa, é melhor utilizar algoritmos de prioritização que visem algum critério, como dar prioridade a testes que cubram, por exemplo, linhas de código ainda não cobertas, por exemplo, aumentando assim a probabilidade dos testes menos importantes serem redundantes e, consequentemente, apagados. Esta ferramenta foi desenvolvida de modo a que fosse facilmente modificável e expansível, oferecendo assim uma maneira fácil para integrar novas ferramentas de redução de testes, permitindo realizar novas comparações à medida que estas ferramentas forem surgindo. Para além disso, destaca-se também a simplicidade da configuração dos critérios a ter em conta quando calculamos a pontuação de cada ferramenta, e o valor que estes têm em comparação com os outros, possibilitando facilmente o cálculo de pontuações tendo em conta diversos cenários.Ao longo deste trabalho, o maior problema encontrado foi o estudo das ferramentas de redução. Para além de algumas não serem open-source, muitas das que eram não iam de encontro aos nossos requisitos para integração na ferramenta, quer por linguagem de programação, quer por abordagem seguida, e muitas vezes a documentação encontrada estava desatualizada ou errada, dificultando todo o processo.With the growing need to assure the quality of the software created nowadays, it has become increasingly necessary to devote part of the development time (sometimes as much as half) to testing the developed code. Despite the high importance of this task, it is an activity that is sometimes ignored and neglected, due to it being, occasionally, a monotonous and tiring job. This is an area thoroughly investigated by researchers who try to automate some parts of this process, while also reducing the time and resources required for this task. In particular, we highlight the proposal of test reduction techniques and tools that implement them, with the goal of detecting unnecessary test cases without compromising the coverage given by the original test suite. The main objective of this work consists in answering two questions: “What is the best Test Suite Reduction tool?” (according to some criterion) and “Can a Test Case Prioritization tool be adapted to effectively replace a Test Suite Reduction tool?”. To answer these questions, we developed a framework that integrates a set of Test Suite Reduction and Test Cases Prioritization tools, with the possibility to integrate more, and that uses them, given a set of open source Java projects, to apply each of its techniques. We then gather test execution data about these projects and compare them to compute a score for each Test Suite Reduction tool, which is used to rank them. This score is achieved by applying a Multi-Criteria Decision-Making methodology, the Analytic Hierarchy Process, to weigh several chosen code metrics on the final score. To answer the second question we integrated a Test Case Prioritization tool into our framework, with which we will get a list of the less important test cases, that we will then remove, simulating a reduction

Enhancing System Realisation in Formal Model Development

Software for mission-critical systems is sometimes analysed using formal specification to increase the chances of the system behaving as intended. When sufficient insights into the system have been obtained from the formal analysis, the formal specification is realised in the form of a software implementation. One way to realise the system's software is by automatically generating it from the formal specification -- a technique referred to as code generation. However, in general it is difficult to make guarantees about the correctness of the generated code -- especially while requiring automation of the steps involved in realising the formal specification. This PhD dissertation investigates ways to improve the automation of the steps involved in realising and validating a system based on a formal specification. The approach aims to develop properly designed software tools which support the integration of formal methods tools into the software development life cycle, and which leverage the formal specification in the subsequent validation of the system. The tools developed use a new code generation infrastructure that has been built as part of this PhD project and implemented in the Overture tool -- a formal methods tool that supports the Vienna Development Method. The development of the code generation infrastructure has involved the re-design of the software architecture of Overture. The new architecture brings forth the reuse and extensibility features of Overture to take into account the needs and requirements of software extensions targeting Overture. The tools developed in this PhD project have successfully supported three case studies from externally funded projects. The feedback received from the case study work has further helped improve the code generation infrastructure and the tools built using it

Génération automatique de tests à partir de patrons de propriétés

National audienceCet article propose une technique originale de génération de tests, à partir d'un modèle formel d'une application, écrit sous la forme d'une machine abstraite B, et d'une propriété définie suivant certains patrons. Les patrons sont des structures paramétrées génériques permettant d'exprimer une propriété formelle se basant sur des prédicats d'états et des événements du système. La technique présentée se base sur la production automatique de scénarios de tests qui sont issus de la propriété en elle-même et d'un besoin de test, ce dernier décrivant informellement une intention de test d'un ingénieur validation. En fonction du patron de propriété considérée et de son instanciation concrète, un ou plusieurs besoins de tests peuvent s'appliquer. Les scénarios de tests produits sont exprimés sous la forme d'expressions régulières décrivant des enchaînements d'opérations amenant à des états pertinents du système. Un mécanisme d'animation symbolique du modèle est utilisé pour déplier les scénarios et instancier les tests, notamment les paramètres des opérations, jusqu'ici abstraits. Ceci permet de produire des cas de tests abstraits prêts à être concrétisés pour le système sous test. Nous présentons l'application de ces principes à travers une étude de cas issue du milieu industriel

Model based test suite minimization using metaheuristics

Software testing is one of the most widely used methods for quality assurance and fault detection purposes. However, it is one of the most expensive, tedious and time consuming activities in software development life cycle. Code-based and specification-based testing has been going on for almost four decades. Model-based testing (MBT) is a relatively new approach to software testing where the software models as opposed to other artifacts (i.e. source code) are used as primary source of test cases. Models are simplified representation of a software system and are cheaper to execute than the original or deployed system. The main objective of the research presented in this thesis is the development of a framework for improving the efficiency and effectiveness of test suites generated from UML models. It focuses on three activities: transformation of Activity Diagram (AD) model into Colored Petri Net (CPN) model, generation and evaluation of AD based test suite and optimization of AD based test suite. Unified Modeling Language (UML) is a de facto standard for software system analysis and design. UML models can be categorized into structural and behavioral models. AD is a behavioral type of UML model and since major revision in UML version 2.x it has a new Petri Nets like semantics. It has wide application scope including embedded, workflow and web-service systems. For this reason this thesis concentrates on AD models. Informal semantics of UML generally and AD specially is a major challenge in the development of UML based verification and validation tools. One solution to this challenge is transforming a UML model into an executable formal model. In the thesis, a three step transformation methodology is proposed for resolving ambiguities in an AD model and then transforming it into a CPN representation which is a well known formal language with extensive tool support. Test case generation is one of the most critical and labor intensive activities in testing processes. The flow oriented semantic of AD suits modeling both sequential and concurrent systems. The thesis presented a novel technique to generate test cases from AD using a stochastic algorithm. In order to determine if the generated test suite is adequate, two test suite adequacy analysis techniques based on structural coverage and mutation have been proposed. In terms of structural coverage, two separate coverage criteria are also proposed to evaluate the adequacy of the test suite from both perspectives, sequential and concurrent. Mutation analysis is a fault-based technique to determine if the test suite is adequate for detecting particular types of faults. Four categories of mutation operators are defined to seed specific faults into the mutant model. Another focus of thesis is to improve the test suite efficiency without compromising its effectiveness. One way of achieving this is identifying and removing the redundant test cases. It has been shown that the test suite minimization by removing redundant test cases is a combinatorial optimization problem. An evolutionary computation based test suite minimization technique is developed to address the test suite minimization problem and its performance is empirically compared with other well known heuristic algorithms. Additionally, statistical analysis is performed to characterize the fitness landscape of test suite minimization problems. The proposed test suite minimization solution is extended to include multi-objective minimization. As the redundancy is contextual, different criteria and their combination can significantly change the solution test suite. Therefore, the last part of the thesis describes an investigation into multi-objective test suite minimization and optimization algorithms. The proposed framework is demonstrated and evaluated using prototype tools and case study models. Empirical results have shown that the techniques developed within the framework are effective in model based test suite generation and optimizatio