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Register a new userConsolidating a Model for Describing Situated Software Practices
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Added by
Stephen MacDonell
Publication date
2020
fields
Informatics Engineering
and research's language is
English
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Many prescriptive approaches to developing software intensive systems have been advocated but each is based on assumptions about context. It has been found that practitioners do not follow prescribed methodologies, but rather select and adapt specific practices according to local needs. As researchers, we would like to be in a position to support such tailoring. However, at the present time we simply do not have sufficient evidence relating practice and context for this to be possible. We have long understood that a deeper understanding of situated software practices is crucial for progress in this area, and have been exploring this problem from a number of perspectives. In this position paper, we draw together the various aspects of our work into a holistic model and discuss the ways in which the model might be applied to support the long term goal of evidence-based decision support for practitioners. The contribution specific to this paper is a discussion on model evaluation, including a proof-of-concept demonstration of model utility. We map Kernel elements from the Essence system to our model and discuss gaps and limitations exposed in the Kernel. Finally, we overview our plans for further refining and evaluating the model.
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It is widely acknowledged by researchers and practitioners that software development methodologies are generally adapted to suit specific project contexts. Research into practices-as-implemented has been fragmented and has tended to focus either on the strength of adherence to a specific methodology or on how the efficacy of specific practices is affected by contextual factors. We submit the need for a more holistic, integrated approach to investigating context-related best practice. We propose a six-dimensional model of the problem-space, with dimensions organisational drivers (why), space and time (where), culture (who), product life-cycle stage (when), product constraints (what) and engagement constraints (how). We test our model by using it to describe and explain a reported implementation study. Our contributions are a novel approach to understanding situated software practices and a preliminary model for software contexts.
Context. Computer workers in general, and software developers specifically, are under a high amount of stress due to continuous deadlines and, often, over-commitment. Objective. This study investigates the effects of a neuroplasticity practice, a specific breathing practice, on the attention awareness, well-being, perceived productivity, and self-efficacy of computer workers. Method. We created a questionnaire mainly from existing, validated scales as entry and exit survey for data points for comparison before and after the intervention. The intervention was a 12-week program with a weekly live session that included a talk on a well-being topic and a facilitated group breathing session. During the intervention period, we solicited one daily journal note and one weekly well-being rating. We replicated the intervention in a similarly structured 8-week program. The data was analyzed using a Bayesian multi-level model for the quantitative part and thematic analysis for the qualitative part. Results. The intervention showed improvements in participants experienced inner states despite an ongoing pandemic and intense outer circumstances for most. Over the course of the study, we found an improvement in the participants ratings of how often they found themselves in good spirits as well as in a calm and relaxed state. We also aggregate a large number of deep inner reflections and growth processes that may not have surfaced for the participants without deliberate engagement in such a program. Conclusion. The data indicates usefulness and effectiveness of an intervention for computer workers in terms of increasing well-being and resilience. Everyone needs a way to deliberately relax, unplug, and recover. Breathing practice is a simple way to do so, and the results call for establishing a larger body of work to make this common practice.
In the domain of software engineering, our efforts as researchers to advise industry on which software practices might be applied most effectively are limited by our lack of evidence based information about the relationships between context and practice efficacy. In order to accumulate such evidence, a model for context is required. We are in the exploratory stage of evolving a model for context for situated software practices. In this paper, we overview the evolution of our proposed model. Our analysis has exposed a lack of clarity in the meanings of terms reported in the literature. Our base model dimensions are People, Place, Product and Process. Our contributions are a deepening of our understanding of how to scope contextual factors when considering software initiatives and the proposal of an initial theoretical construct for context. Study limitations relate to a possible subjectivity in the analysis and a restricted evaluation base. In the next stage in the research, we will collaborate with academics and practitioners to formally refine the model.
Many methods have been proposed to estimate how much effort is required to build and maintain software. Much of that research assumes a ``classic waterfall-based approach rather than contemporary projects (where the developing process may be more iterative than linear in nature). Also, much of that work tries to recommend a single method-- an approach that makes the dubious assumption that one method can handle the diversity of software project data. To address these drawbacks, we apply a configuration technique called ``ROME (Rapid Optimizing Methods for Estimation), which uses sequential model-based optimization (SMO) to find what combination of effort estimation techniques works best for a particular data set. We test this method using data from 1161 classic waterfall projects and 120 contemporary projects (from Github). In terms of magnitude of relative error and standardized accuracy, we find that ROME achieves better performance than existing state-of-the-art methods for both classic and contemporary problems. In addition, we conclude that we should not recommend one method for estimation. Rather, it is better to search through a wide range of different methods to find what works best for local data. To the best of our knowledge, this is the largest effort estimation experiment yet attempted and the only one to test its methods on classic and contemporary projects.
Usability is an increasing concern in open source software (OSS). Given the recent changes in the OSS landscape, it is imperative to examine the OSS contributors current valued factors, practices, and challenges concerning usability. We accumulated this knowledge through a survey with a wide range of contributors to OSS applications. Through analyzing 84 survey responses, we found that many participants recognized the importance of usability. While most relied on issue tracking systems to collect user feedback, a few participants also adopted typical user-centered design methods. However, most participants demonstrated a system-centric rather than a user-centric view. Understanding the diverse needs and consolidating various feedback of end-users posed unique challenges for the OSS contributors when addressing usability in the most recent development context. Our work provided important insights for OSS practitioners and tool designers in exploring ways for promoting a user-centric mindset and improving usability practice in the current OSS communities.
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