Interactive ambient visualizations for soft advice

Abstract

Some software packages offer the user soft advice: recommendations that are intended to help the user create high-quality artifacts but which may turn out to be bad advice. It is left to the user to determine whether the soft advice really will improve quality and to decide whether to adopt it. Visualizations can help the user in making this decision, but we believe that conventional visualizations are less than ideal. In this article, we describe an interactive ambient visualization to help users identify, understand, and interpret soft advice. Our visualization was developed to help programmers interpret code smells, which are indications that a software project may be suffering from design problems. We describe a laboratory experiment with 12 programmers that tests several hypotheses about our visualization. The findings suggest that our tool helps programmers to identify smells more effectively and to make more informed judgments about the design of the program under development. We then describe an application of our visualization technique in another domain: an English style and grammar advisor. This second application suggests that our technique can be applied to several domains and also suggests how the technique must be varied to make it domain specific.

ConCAD: A Tool for Interactive Detection of Code Anomalies

“…Because code anomalies can go unnoticed while developers are working, techniques for anomaly detection have been developed to alert programmers and to help them understand the cause of those anomalies. These techniques are comprised of two components [5][1]: 1) Detection Mechanism which allows developers to define algorithms and choose some metrics -and adjust thresholds -to compose the detection strategy [4]; and 2) User interface which displays the results of anomaly detection.…”

“…The ID techniques continuously work in the background to detect anomaly instances while software developers work on coding tasks. A developer using ID techniques can identify anomaly instances earlier, allowing developers to analyze and modify the source code while interacting with the affected code elements [1] [5]. Non-Interactive Detection (NID) technique does not support the developer's interaction with affected code elements unless the detection mechanism receives the developer's request, after which it will detect potential code anomalies by analyzing the entire project.…”

“…Developers using NID techniques may identify anomaly occurrences only after the code churns are merged with other software components. Finally, once developers directly interact with the detection mechanism and a global list of anomaly instances, they cannot concurrently perform other programming activities [1] [5].…”

Integrating Interactive Detection of Code Smells into Scrum: Feasibility, Benefits, and Challenges

“…In contrast to NID, the ID technique allows developers interact with smelly code elements as they edit or browse their program statements [6]. This feature can help the developer be aware of new occurrences of code smells as soon as they are introduced [10]. Empirical studies show that the sooner code smells are removed, the less effort and time is spent on this activity [2,11].…”

Conducting interview studies: Challenges, lessons learned, and open questions

“…We do not consider these challenges minor or attributable to inexperience -indeed, over the years we have conducted many studies involving software developers, including usability studies [6], heuristic evaluations [7], panels, controlled experiments [8], surveys [9], interviews [10], and paper mockups [11]. We faced these challenges in spite of following general [12] and methodologyspecific [13] guidelines for conducting empirical research.…”