A CONSIDERATION OF THE DEVOLUTION OF FEDERAL AGRICULTURAL POLICY

Diverse needs and preferences across the United States provide justification for the devolution, or decentralization, of many Federal Government programs to the State or local level. The move toward devolution, however, has not been evidenced in U.S. agricultural policy, despite significant differences across States in such areas as commodity production, production costs, income distribution, and opportunities for off-farm work. The existing structure of USDA funding and program delivery already reflects an appreciation of the gains from devolution, with some programs accommodating differences in State and regional preferences. This report considers the implications of devolving $22 billion in 2003 budget outlays, mostly for domestic commodity and natural resource programs and rural development and housing programs. The local knowledge of needs and references is valuable and can provide the basis for increased program efficiency.Public policy, devolution, agricultural policy, program delivery, Agricultural and Food Policy,

Mutation Testing as a Safety Net for Test Code Refactoring

Refactoring is an activity that improves the internal structure of the code without altering its external behavior. When performed on the production code, the tests can be used to verify that the external behavior of the production code is preserved. However, when the refactoring is performed on test code, there is no safety net that assures that the external behavior of the test code is preserved. In this paper, we propose to adopt mutation testing as a means to verify if the behavior of the test code is preserved after refactoring. Moreover, we also show how this approach can be used to identify the part of the test code which is improperly refactored

A Study of Equivalent and Stubborn Mutation Operators using Human Analysis of Equivalence

Though mutation testing has been widely studied for more than thirty years, the prevalence and properties of equivalent mutants remain largely unknown. We report on the causes and prevalence of equivalent mutants and their relationship to stubborn mutants (those that remain undetected by a high quality test suite, yet are non-equivalent). Our results, based on manual analysis of 1,230 mutants from 18 programs, reveal a highly uneven distribution of equivalence and stubbornness. For example, the ABS class and half UOI class generate many equivalent and almost no stubborn mutants, while the LCR class generates many stubborn and few equivalent mutants. We conclude that previous test effectiveness studies based on fault seeding could be skewed, while developers of mutation testing tools should prioritise those operators that we found generate disproportionately many stubborn (and few equivalent) mutants

Do Null-Type Mutation Operators Help Prevent Null-Type Faults?

The null-type is a major source of faults in Java programs, and its overuse has a severe impact on software maintenance. Unfortunately traditional mutation testing operators do not cover null-type faults by default, hence cannot be used as a preventive measure. We address this problem by designing four new mutation operators which model null-type faults explicitly. We show how these mutation operators are capable of revealing the missing tests, and we demonstrate that these mutation operators are useful in practice. For the latter, we analyze the test suites of 15 open-source projects to describe the trade-offs related to the adoption of these operators to strengthen the test suite

Class mutation operators for C++ object-oriented systems

Mutation testing is a fault injection testing technique around which a great variety of studies and tools for different programming languages have been developed. Nevertheless, the mutation testing research with respect to C++ is pending. This paper proposes a set of class mutation operators related to this language and its particular object-oriented (OO) features. In addition, an implementation technique to apply mutation testing based on the traversal of the abstract syntax tree (AST) is presented. Finally, an experiment is conducted to study the operator behaviour with different C++ programs, suggesting their usefulness in the creation of complete test suites. The analysis includes a Web service (WS) library, one of the domains where this technique can prove useful, considering its challenging testing phase and that C++ is still a reference language for critical distributed systems WS

Traceability for Mutation Analysis in Model Transformation

International audienceModel transformation can't be directly tested using program techniques. Those have to be adapted to model characteristics. In this paper we focus on one test technique: mutation analysis. This technique aims to qualify a test data set by analyzing the execution results of intentionally faulty program versions. If the degree of qualification is not satisfactory, the test data set has to be improved. In the context of model, this step is currently relatively fastidious and manually performed. We propose an approach based on traceability mechanisms in order to ease the test model set improvement in the mutation analysis process. We illustrate with a benchmark the quick automatic identification of the input model to change. A new model is then created in order to raise the quality of the test data set

Demonstrable Evidence of Beneficial Physical Outcomes from University Physical Education Activity Courses

Introduction: Engagement in physical activity (PA) is often dramatically reduced during the transition from high school into college. There appears to be more stability in PA patterns during the transition from college into post-graduate life. Consequently, researchers have highlighted the years in higher education as pivotal for shaping lasting PA habits. Sadly, there is a widespread lack of evidence regarding the outcomes from physical education activity courses (PEAC) offered on campuses of higher education. Thus, their overall value lacks validation. The purpose of this work was to offer evidence of outcomes from engagement in a single, semester-long university PEAC class. Methods: Students were recruited from a variety of classes. There were no directions provided to the instructors of the courses. For grouping, classes were categorized as aerobic- (aerobics, jogging, and walking) or sport-activity (badminton, pickle ball, self-defense, strength training, and ultimate frisbee). Students in the aerobic-activity arm were randomized to aerobic testing where they underwent a submaximal treadmill protocol and grip strength (GS) testing or body composition testing (air displacement plethysmography) and GS. Those in the sport-activity arm underwent vertical jump and GS testing. Students reported to the human performance lab in the first two and final two weeks of the semester. Paired t-tests were conducted to identify differences in pre-post outcomes. Values were carried forward, not dropped, when a subject failed to return at post-test. Results: A total of 46 students (age = 21.7 ± 4.1) were randomized into the aerobic (n=25; m/f = 11/14) or body composition arms (n=21; m/f = 7/14). Additionally, 45 students (age = 20.8 ± 3.2; m/f = 23/22) from sport-activity classes were enrolled. Participation in aerobic-activity classes resulted in improvements in estimated maximal aerobic ability (p = 0.030; 42.9 ± 9.9 vs. 44.6 ± 10.1). Participation also resulted in increases in GS for those allocated to both the aerobic (p = 0.010; 56.4 ± 21.5 vs. 60.3 ± 22.3) and body composition (p = 0.022; 54.1 ± 22.1 vs. 58.1 ± 24.6) arms. Participation did not result in changes in body composition (p = 0.817; 24.7 ± 8.5 vs. 24.6 ± 7.4) despite a near-significant increase in weight (p = 0.057; 152.7 ± 38.5 vs. 154.5 ± 37.7). Participation in sport-activity classes resulted in an improvement in vertical jump (p = 0.007; 18.2 ± 6.1 vs. 18.9 ± 6.0) and GS (p = 0.002; 65.3 ± 25.6 vs. 70.0 ± 27.8). Discussion: An important first step in rebutting challenges about the credibility and worthiness of PEAC offerings is evidencing beneficial outcomes. These results represent simple, but important, markers of change. Additional demonstrable evidence is needed to ascertain elements such as what outcomes are achievable, what classes are most effective classes, and what components from class support lasting change

Survey Responses From “Wellness for Life” Classes: Overall Value and Barriers, Motivators, and Motives Towards Physical Activity

Introduction: Skill-based sport activity classes were the historical trend, but greater numbers of higher education institutions now offer courses that encompass “wellness for life” concepts. The goal of these offerings is to guide students in the development of knowledge, skills, and behaviors to adopt and maintain healthful behaviors. There is a need to amass evidence of the outcomes arising from engagement in these classes. Purpose: The purpose of this work was to document outcomes from participation in a single, semester-long, university wellness for life class. Methods: Students were recruited from courses at two universities. Survey responses were collected in the first two and final two weeks of class. The survey items included identification of: engagement in regular physical activity (PA), perceptions about PA (“view of self as an exerciser”, “contentment with current PA level”, among others), and barriers, motivators, and motives towards PA. There were no intervention suggestions provided to instructors. Results: A total of 173 students (m/f/not identified = 51/118/4; age 19.6 ± 1.4) participated. When questioned, many students identified as being an “exerciser.” Some perceived “no need to change their program” (n=37) but most “wanted more regular exercise” (n=88). A lesser number of students identified as being a “non-exerciser.” Most all “wanted more regular exercise” (n=46), but two had “no desire to start a program.” At post-test, the respective numbers were: 37, 95, 41, and 3. Numbers did not always align due to incomplete survey responses. The perceived value of the class to current and future health, rated on a scale from 0 (no impact)-100 (most influential), improved pre-post class (p \u3c 0.001) from 61.7 (±24.5) to 67.8 (±23.5). The top barrier, motivator, and motive at pre-test were: “I need to do better at managing my time to exercise more often,” “If I better organized my time or schedule I could exercise more,” and “I get pleasure or enjoy sports so I exercise,” respectively. There was shuffling among the top choices from pre- to post-test, but the top barrier remained the same. The top motivator became, “If I had more time I would exercise more,” and the top motive became, “I feel less stress after I exercise.” Discussion: Evidenced by the pre-post responses, students feel that wellness for life classes have some benefit and that perception improves after experiencing the class. There appears to be consistency in those who view themselves as “exercisers” and “non-exercisers,” which might represent a precarious situation. There is constancy in the primary barrier to exercise – the socially acceptable answer – time. It is obvious that time management is a critical element for inclusion in these classes. Students may also benefit more if instructors would offer insight on the use of motivators and motives in overcoming personal barriers

N-Gram Based Test Sequence Generation from Finite State Models

Abstract. Model based testing offers a powerful mechanism to test ap-plications that change dynamically and continuously, for which only some limited black-box knowledge is available (this is typically the case of fu-ture internet applications). Models can be inferred from observations of real executions and test cases can be derived from models, according to various strategies (e.g., graph or random visits). The problem is that a relatively large proportion of the test cases obtained in this way might result to be non executable, because they involve infeasible paths. In this paper, we propose a novel test case derivation strategy, based on the computation of the N-gram statistics. Event sequences are gen-erated for which the subsequences of size N respect the distribution of the N-tuples observed in the execution traces. In this way, generated and observed sequences share the same context (up to length N), hence increasing the likelihood for the generated ones of being actually exe-cutable. A consequence of the increased proportion of feasible test cases is that model coverage is also expected to increase.

Mutation-aware fault prediction

We introduce mutation-aware fault prediction, which leverages additional guidance from metrics constructed in terms of mutants and the test cases that cover and detect them. We report the results of 12 sets of experiments, applying 4 di↵erent predictive modelling techniques to 3 large real world systems (both open and closed source). The results show that our proposal can significantly (p 0.05) improve fault prediction performance. Moreover, mutation based metrics lie in the top 5% most frequently relied upon fault predictors in 10 of the 12 sets of experiments, and provide the majority of the top ten fault predictors in 9 of the 12 sets of experiments.http://www0.cs.ucl.ac.uk/staff/F.Sarro/resource/papers/ISSTA2016-Bowesetal.pd