Test Generation and Dependency Analysis for Web Applications

In web application testing existing model based web test generators derive test paths from a navigation model of the web application, completed with either manually or randomly generated inputs. Test paths extraction and input generation are handled separately, ignoring the fact that generating inputs for test paths is difficult or even impossible if such paths are infeasible. In this thesis, we propose three directions to mitigate the path infeasibility problem. The first direction uses a search based approach defining novel set of genetic operators that support the joint generation of test inputs and feasible test paths. Results show that such search based approach can achieve higher level of model coverage than existing approaches. Secondly, we propose a novel web test generation algorithm that pre-selects the most promising candidate test cases based on their diversity from previously generated tests. Results of our empirical evaluation show that promoting diversity is beneficial not only to a thorough exploration of the web application behaviours, but also to the feasibility of automatically generated test cases. Moreover, the diversity based approach achieves higher coverage of the navigation model significantly faster than crawling based and search based approaches. The third approach we propose uses a web crawler as a test generator. As such, the generated tests are concrete, hence their navigations among the web application states are feasible by construction. However, the crawling trace cannot be easily turned into a minimal test suite that achieves the same coverage due to test dependencies. Indeed, test dependencies are undesirable in the context of regression testing, preventing the adoption of testing optimization techniques that assume tests to be independent. In this thesis, we propose the first approach to detect test dependencies in a given web test suite by leveraging the information available both in the web test code and on the client side of the web application. Results of our empirical validation show that our approach can effectively and efficiently detect test dependencies and it enables dependency aware formulations of test parallelization and test minimization

TimeMachine: Timeline Generation for Knowledge-Base Entities

We present a method called TIMEMACHINE to generate a timeline of events and relations for entities in a knowledge base. For example for an actor, such a timeline should show the most important professional and personal milestones and relationships such as works, awards, collaborations, and family relationships. We develop three orthogonal timeline quality criteria that an ideal timeline should satisfy: (1) it shows events that are relevant to the entity; (2) it shows events that are temporally diverse, so they distribute along the time axis, avoiding visual crowding and allowing for easy user interaction, such as zooming in and out; and (3) it shows events that are content diverse, so they contain many different types of events (e.g., for an actor, it should show movies and marriages and awards, not just movies). We present an algorithm to generate such timelines for a given time period and screen size, based on submodular optimization and web-co-occurrence statistics with provable performance guarantees. A series of user studies using Mechanical Turk shows that all three quality criteria are crucial to produce quality timelines and that our algorithm significantly outperforms various baseline and state-of-the-art methods.Comment: To appear at ACM SIGKDD KDD'15. 12pp, 7 fig. With appendix. Demo and other info available at http://cs.stanford.edu/~althoff/timemachine

Automatic assessment of creativity in heuristic problem-solving based on query diversity

Indexación: Web of Science; Scopus.Research, development and innovation are the pillars on which companies rely to offer new products and services capable of attracting consumer demand. This is why creative problem-solving emerges as one of the most relevant skills of the 21st century. Fortunately, there are many creativity training programs that have proven effective. However, many of these programs and methods base on a previous measurement of creativity and require experienced reviewers, they consume time for being manual, and they are far from everyday activities. In this study, we propose a model to estimate the creative quality of users' solutions dealing with heuristic problems, based on the automatic analysis of query patterns issued during the information search to solve the problem. This model has been able to predict the creative quality of solutions produced by 226 users, reaching a sensitivity of 78.43%. Likewise, the level of agreement among reviewers in relation to the creative characteristics is evaluated through two rubrics, and thereby, observing the difficulties of the manual evaluation: subjectivity and effort. The proposed model could be used to foster prompt detection of non-creative solutions and it could be implemented in diverse industrial processes that can range from the recruitment of talent to the evaluation of performance in R&D&I processes.https://www.revistadyna.com/search/automatic-assessment-of-creativity-in-heuristic-problem-solving-based-on-query-diversit

Mapping functional traits: comparing abundance and presence-absence estimates at large spatial scales

Efforts to quantify the composition of biological communities increasingly focus on functional traits. The composition of communities in terms of traits can be summarized in several ways. Ecologists are beginning to map the geographic distribution of trait-based metrics from various sources of data, but the maps have not been tested against independent data. Using data for birds of the Western Hemisphere, we test for the first time the most commonly used method for mapping community trait composition – overlaying range maps, which assumes that the local abundance of a given species is unrelated to the traits in question – and three new methods that as well as the range maps include varying degrees of information about interspecific and geographic variation in abundance. For each method, and for four traits (body mass, generation length, migratory behaviour, diet) we calculated community-weighted mean of trait values, functional richness and functional divergence. The maps based on species ranges and limited abundance data were compared with independent data on community species composition from the American Christmas Bird Count (CBC) scheme coupled with data on traits. The correspondence with observed community composition at the CBC sites was mostly positive (62/73 correlations) but varied widely depending on the metric of community composition and method used (R2: 5.6×10−7 to 0.82, with a median of 0.12). Importantly, the commonly-used range-overlap method resulted in the best fit (21/22 correlations positive; R2: 0.004 to 0.8, with a median of 0.33). Given the paucity of data on the local abundance of species, overlaying range maps appears to be the best available method for estimating patterns of community composition, but the poor fit for some metrics suggests that local abundance data are urgently needed to allow more accurate estimates of the composition of communities