Comparing text-based and dependence-based approaches for determining the origins of bugs

Identifying bug origins – the point where erroneous code was introduced – is crucial for many software engineering activities, from identifying process weaknesses to gathering data to support bug detection tools. Unfortunately, this information is not usually recorded when fixing bugs, and recovering it later is challenging. Recently, the text approach and the dependence approach have been developed to tackle this problem. Respectively, they examine textual and dependence-related changes that occurred prior to a bug fix. However, only limited evaluation has been carried out, partially because of a lack of available implementations and of datasets linking bugs to origins. To address this, origins of 174 bugs in three projects were manually identified and compared to a simulation of the approaches. Both approaches were partially successful across a variety of bugs – achieving 29–79% precision and 40–70% recall. Results suggested the precise definition of program dependence could affect performance, as could whether the approaches identified a single or multiple origins. Some potential improvements are explored in detail and identify pragmatic strategies for combining techniques along with simple modifications. Even after adopting these improvements, there remain many challenges: large commits, unrelated changes and long periods between origins and fixes all reduce effectiveness

A preliminary evaluation of text-based and dependency-based techniques for determining the origins of bugs

A crucial step in understanding the life cycle of software bugs is identifying their origin. Unfortunately this information is not usually recorded and recovering it at a later date is challenging. Recently two approaches have been developed that attempt to solve this problem: the text approach and the dependency approach. However only limited evaluation has been carried out on their effectiveness so far, partially due to the lack of data sets linking bugs to their introduction. Producing such data sets is both time-consuming and challenging due to the subjective nature of the problem. To improve this, the origins of 166 bugs in two open-source projects were manually identified. These were then compared to a simulation of the approaches. The results show that both approaches were partially successful across a variety of different types of bugs. They achieved a precision of 29%{79% and a recall of 40%{70%, and could perform better when combined. However there remain a number of challenges to overcome in future development|large commits, unrelated changes and large numbers of versions between the origin and the x all reduce their effectiveness

Studying the lives of software bugs

For as long as people have made software, they have made mistakes in that software. Software bugs are widespread, and the maintenance required to fix them has a major impact on the cost of software and how developers' time is spent. Reducing this maintenance time would lower the cost of software and allow for developers to spend more time on new features, improving the software for end-users. Bugs are hugely diverse and have a complex life cycle. This makes them difficult to study, and research is often carried out on synthetic bugs or toy programs. However, a better understanding of the bug life cycle would greatly aid in developing tools to reduce the time spent on maintenance. This thesis will study the life cycle of bugs, and develop such an understanding. Overall, this thesis examines over 3000 real bugs, from real projects, concentrating on three of the most important points in the life cycle: origin, reporting and fix. Firstly, two existing techniques are compared for discovering the origin of a bug. A number of improvements are evaluated, and the most effective approach is found to be combining the techniques. Furthermore, the behaviour of developers is found to have a major impact on the accuracy of the techniques. Secondly, a large number of bugs are analysed to determine what information is provided when users report bugs. For most bugs, much important information is missing, or inaccurate. Most importantly, there appears to be a considerable gap between what users provide and what developers actually want. Finally, an evaluation is carried out on a number of novel alterations to techniques used to determine the location of bug fixes. Compared to existing techniques, these alterations successfully increase the number of bugs which can be usefully localised, aiding developers in removing the bugs.For as long as people have made software, they have made mistakes in that software. Software bugs are widespread, and the maintenance required to fix them has a major impact on the cost of software and how developers' time is spent. Reducing this maintenance time would lower the cost of software and allow for developers to spend more time on new features, improving the software for end-users. Bugs are hugely diverse and have a complex life cycle. This makes them difficult to study, and research is often carried out on synthetic bugs or toy programs. However, a better understanding of the bug life cycle would greatly aid in developing tools to reduce the time spent on maintenance. This thesis will study the life cycle of bugs, and develop such an understanding. Overall, this thesis examines over 3000 real bugs, from real projects, concentrating on three of the most important points in the life cycle: origin, reporting and fix. Firstly, two existing techniques are compared for discovering the origin of a bug. A number of improvements are evaluated, and the most effective approach is found to be combining the techniques. Furthermore, the behaviour of developers is found to have a major impact on the accuracy of the techniques. Secondly, a large number of bugs are analysed to determine what information is provided when users report bugs. For most bugs, much important information is missing, or inaccurate. Most importantly, there appears to be a considerable gap between what users provide and what developers actually want. Finally, an evaluation is carried out on a number of novel alterations to techniques used to determine the location of bug fixes. Compared to existing techniques, these alterations successfully increase the number of bugs which can be usefully localised, aiding developers in removing the bugs

Automated Fixing of Programs with Contracts

This paper describes AutoFix, an automatic debugging technique that can fix faults in general-purpose software. To provide high-quality fix suggestions and to enable automation of the whole debugging process, AutoFix relies on the presence of simple specification elements in the form of contracts (such as pre- and postconditions). Using contracts enhances the precision of dynamic analysis techniques for fault detection and localization, and for validating fixes. The only required user input to the AutoFix supporting tool is then a faulty program annotated with contracts; the tool produces a collection of validated fixes for the fault ranked according to an estimate of their suitability. In an extensive experimental evaluation, we applied AutoFix to over 200 faults in four code bases of different maturity and quality (of implementation and of contracts). AutoFix successfully fixed 42% of the faults, producing, in the majority of cases, corrections of quality comparable to those competent programmers would write; the used computational resources were modest, with an average time per fix below 20 minutes on commodity hardware. These figures compare favorably to the state of the art in automated program fixing, and demonstrate that the AutoFix approach is successfully applicable to reduce the debugging burden in real-world scenarios.Comment: Minor changes after proofreadin

Next nearest neighbour Ising models on random graphs

This paper develops results for the next nearest neighbour Ising model on random graphs. Besides being an essential ingredient in classic models for frustrated systems, second neighbour interactions interactions arise naturally in several applications such as the colour diversity problem and graphical games. We demonstrate ensembles of random graphs, including regular connectivity graphs, that have a periodic variation of free energy, with either the ratio of nearest to next nearest couplings, or the mean number of nearest neighbours. When the coupling ratio is integer paramagnetic phases can be found at zero temperature. This is shown to be related to the locked or unlocked nature of the interactions. For anti-ferromagnetic couplings, spin glass phases are demonstrated at low temperature. The interaction structure is formulated as a factor graph, the solution on a tree is developed. The replica symmetric and energetic one-step replica symmetry breaking solution is developed using the cavity method. We calculate within these frameworks the phase diagram and demonstrate the existence of dynamical transitions at zero temperature for cases of anti-ferromagnetic coupling on regular and inhomogeneous random graphs.Comment: 55 pages, 15 figures, version 2 with minor revisions, to be published J. Stat. Mec

Verification and validation of models

Simulation Models;econometrics

Dynamics of Innovation in an “Open Source” Collaboration Environment: Lurking, Laboring and Launching FLOSS Projects on SourceForge

A systems analysis perspective is adopted to examine the critical properties of the Free/Libre/Open Source Software (FLOSS) mode of innovation, as reflected on the SourceForge platform (SF.net). This approach re-scales March’s (1991) framework and applies it to characterize the “innovation system” of a “distributed organization” of interacting agents in a virtual collaboration environment. The innovation system of the virtual collaboration environment is an emergent property of two “coupled” processes: one involves interactions among agents searching for information to use in designing novel software products, and the other involves the mobilization of individual capabilities for application in the software development projects. Micro-dynamics of this system are studied empirically by constructing transition probability matrices representing movements of 222,835 SF.net users among 7 different activity states. Estimated probabilities are found to form first-order Markov chains describing ergodic processes. This makes it possible to computate the equilibrium distribution of agents among the states, thereby suppressing transient effects and revealing persisting patterns of project-joining and project-launching.innovation systems, collaborative development environments, industrial districts, exploration and exploitation dynamics, open source software, FLOSS, SourceForge, project-joining, project-founding, Markov chain analysis.

Exploring Stages of Recovery from Crack Cocaine Addiction

Crack cocaine users need efficacious treatment options to address triggers and cravings for the drug. The purpose of this qualitative, multiple case study was to explore the recovery narratives of 3 purposefully selected substance abuse counselors who were once addicted to crack cocaine and whether or not these narratives fit within the 5 stages of the transtheoretical model of change (TTM). The TTM was used in this study to explore the stages of change in those with prior addiction regarding the motivational strategies needed to promote change. Data collected in face to face interviews were organized using thematic content analysis and QDA Minor Lite analysis software. Study results showed that the action stage seems the be the most promising focus for change. Each participant once in the action stage moved between action and relapse until action and maintenance became solidified in their mindset. The action stage, therefore led to social change for the individual, their family, and the community in which they lived. Therefore, the process of recover does fit within the stages of the TTM, however, relapse and risk of relapse plays a vital part of not making the stages qualitatively distinct. The results of the study show that various factors create the addiction process and help to recover from it. However, self-actualization and self-determination prove to be the motivating factors of change and recovery. The findings contribute to social change by understanding how the recovery stories fit within the stages of the TTM and how further understanding of the relapse process is necessary to possibly get to a definitive termination stage