Target Directed Event Sequence Generation for Android Applications

Testing is a commonly used approach to ensure the quality of software, of which model-based testing is a hot topic to test GUI programs such as Android applications (apps). Existing approaches mainly either dynamically construct a model that only contains the GUI information, or build a model in the view of code that may fail to describe the changes of GUI widgets during runtime. Besides, most of these models do not support back stack that is a particular mechanism of Android. Therefore, this paper proposes a model LATTE that is constructed dynamically with consideration of the view information in the widgets as well as the back stack, to describe the transition between GUI widgets. We also propose a label set to link the elements of the LATTE model to program snippets. The user can define a subset of the label set as a target for the testing requirements that need to cover some specific parts of the code. To avoid the state explosion problem during model construction, we introduce a definition "state similarity" to balance the model accuracy and analysis cost. Based on this model, a target directed test generation method is presented to generate event sequences to effectively cover the target. The experiments on several real-world apps indicate that the generated test cases based on LATTE can reach a high coverage, and with the model we can generate the event sequences to cover a given target with short event sequences

Using formal methods to support testing

Formal methods and testing are two important approaches that assist in the development of high quality software. While traditionally these approaches have been seen as rivals, in recent years a new consensus has developed in which they are seen as complementary. This article reviews the state of the art regarding ways in which the presence of a formal specification can be used to assist testing

Advanced information processing system: The Army fault tolerant architecture conceptual study. Volume 1: Army fault tolerant architecture overview

Digital computing systems needed for Army programs such as the Computer-Aided Low Altitude Helicopter Flight Program and the Armored Systems Modernization (ASM) vehicles may be characterized by high computational throughput and input/output bandwidth, hard real-time response, high reliability and availability, and maintainability, testability, and producibility requirements. In addition, such a system should be affordable to produce, procure, maintain, and upgrade. To address these needs, the Army Fault Tolerant Architecture (AFTA) is being designed and constructed under a three-year program comprised of a conceptual study, detailed design and fabrication, and demonstration and validation phases. Described here are the results of the conceptual study phase of the AFTA development. Given here is an introduction to the AFTA program, its objectives, and key elements of its technical approach. A format is designed for representing mission requirements in a manner suitable for first order AFTA sizing and analysis, followed by a discussion of the current state of mission requirements acquisition for the targeted Army missions. An overview is given of AFTA's architectural theory of operation

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

The Impact of Automated Cognitive Assistants on Situational Awareness in the Brigade Combat Team

This research investigated the impact of automated cognitive assistants, specifically, the Personalized Assistant that Learns (PAL), on situational awareness, efficiency and effectiveness of decision making in the brigade combat team. PAL was recently commissioned by Defense Advanced Research Projects Agency (DARPA) to enhance decision making with the Command Post of the Future (CPOF). This is the first study to investigate PAL's effectiveness. Previous literature has indicated that automated cognitive assistants can reduce cognitive load and improve the efficiency and effectiveness of decision-making. This is consistent with constructivist theories that assume that relegating repetitive tasks to an assistant allows decision makers to focus on the most critical issues. This is particularly true in those conditions where the environment is in continuous flux and the decision makers must remain cognizant of changing situations. To investigate PAL'S influence on situational awareness, two groups of military officers comprising a convenience sample were placed into two groups representing brigade combat teams. Before tests were administered, each team was trained on the cognitive assistants and given a hands-on examination to measure competency in PAL and CPOF. All subjects participated in one trial with PAL-enhanced CPOF and one trial with CPOF alone. Self-assessments of situational awareness were administered which included sub-scales on: task management, information management, decision support, and appreciation of the environment, visualization and trust. Speed and quality of decision-making were also measured. Repeated measures analysis of variance was used to compare PAL and CPOF only on situational awareness. In the repeated measures ANOVA, the overall difference on self-report of situational awareness approachedthe .05 level with PAL (M = 1.85, SD = 0.46) and CPOF (M = 2.06, SD = 0.57; F(1,10) = 4.61, p = .057), with the lower score indicating higher approval. There was a significant difference on the decision support category of situational awareness in the second trial using both PAL and CPOF (M = 2.21, SD = 0.59; rated higher than the first trial (M = 2.53, SD = 0.49; F(1,10) = 5.06, p = .048). The following differences were not significant but the means all favored PAL over CPOF: quality of decision making products PAL (M = 2.89, SD = 0.75); CPOF (M = 2.53, SD = 0.83), speed of submission in minutes PAL (M = 9:13, SD = 3:15); CPOF (M = 10:00, SD = 5:53), and Situational Awareness quizzes PAL (M = 67.03, SD = 7.15); CPOF (M = 59.24, SD = 8.23). While comparisons of PAL and CPOF were not significant, results indicate that the PAL automated cognitive assistant has promise in improving the situational awareness and efficiency of military leaders in complex decision making. The findings demonstrate that as military officers grow more accustomed to using these analytical systems, both PAL and CPOF, they rate their support in decision making higher. This initial study of PAL was conducted with a convenience sample of 12 military officers. Further studies are warranted to investigate the benefits of automated cognitive assistant on an array of factors that influence decision-making across conditions and audiences

10381 Summary and Abstracts Collection -- Robust Query Processing

Dagstuhl seminar 10381 on robust query processing (held 19.09.10 - 24.09.10) brought together a diverse set of researchers and practitioners with a broad range of expertise for the purpose of fostering discussion and collaboration regarding causes, opportunities, and solutions for achieving robust query processing. The seminar strove to build a unified view across the loosely-coupled system components responsible for the various stages of database query processing. Participants were chosen for their experience with database query processing and, where possible, their prior work in academic research or in product development towards robustness in database query processing. In order to pave the way to motivate, measure, and protect future advances in robust query processing, seminar 10381 focused on developing tests for measuring the robustness of query processing. In these proceedings, we first review the seminar topics, goals, and results, then present abstracts or notes of some of the seminar break-out sessions. We also include, as an appendix, the robust query processing reading list that was collected and distributed to participants before the seminar began, as well as summaries of a few of those papers that were contributed by some participants

Automatically Generating Test Cases for Safety-Critical Software via Symbolic Execution

Automated test generation based on symbolic execution can be beneficial for systematically testing safety-critical software, to facilitate test engineers to pursue the strict testing requirements mandated by the certification standards, while controlling at the same time the costs of the testing process. At the same time, the development of safety-critical software is often constrained with programming languages or coding conventions that ban linguistic features which are believed to downgrade the safety of the programs, e.g., they do not allow dynamic memory allocation and variable-length arrays, limit the way in which loops are used, forbid recursion, and bound the complexity of control conditions. As a matter of facts, these linguistic features are also the main efficiency-blockers for the test generation approaches based on symbolic execution at the state of the art. This paper contributes new evidence of the effectiveness of generating test cases with symbolic execution for a significant class of industrial safety critical-systems. We specifically focus on Scade, a largely adopted model-based development language for safety-critical embedded software, and we report on a case study in which we exploited symbolic execution to automatically generate test cases for a set of safety-critical programs developed in Scade. To this end, we introduce a novel test generator that we developed in a recent industrial project on testing safety-critical railway software written in Scade, and we report on our experience of using this test generator for testing a set of Scade programs that belong to the development of an on-board signaling unit for high-speed rail. The results provide empirically evidence that symbolic execution is indeed a viable approach for generating high-quality test suites for the safety-critical programs considered in our case study