Culture fit is an essential consideration while designing websites in this technologically evolving era, yet it is too often ignored in current usability evaluation methods. The heuristic evaluation is one such method, in which, generally, experts use a set of heuristics as a guide. These heuristics are well designed to pinpoint the general usability design faults; however, they limit identifying potential usability problems for specific domains and cultures. This article presents a formal methodology with a sequence of steps of how domain and culture-specific heuristics can be designed. This methodology is validated and applied in the context of websites for universities in Pakistan.

Already from the early days of testing, practitioners distinguish between unit tests and integration tests as a strategy to locate defects. Unfortunately, the mining software engineering community rarely distinguishes between these two strategies, mainly because it is not straightforward to separate them in the code repositories under study. In this paper we exploited the TravisTorrent dataset provided for the MSR 2017 mining challenge, separated unit tests from integration tests, and correlated these against the workflow as recorded in the corresponding issue reports. Further analysis confirmed that it is worthwhile to treat unit tests and integration tests differently: we discovered that unit tests cause more breaking builds, that fixing the defects exposed by unit tests takes longer and implies more coordination between team members.

Continuous integration is a best practice adopted in modern software development teams to identify potential faults immediately upon project build. Once a fault is detected it must be repaired immediately, hence continuous integration provides an ideal testbed for experimenting with the state of the art in fault localisation. In this paper we propose a variant of what is known as spectrum based fault localisation, which leverages patterns of method calls by means of frequent itemset mining. We compare our variant (we refer to it as patterned spectrum analysis) against the state of the art and demonstrate on 351 real bugs drawn from five representative open source java projects that patterned spectrum analysis is more effective in localising the fault. Based on anecdotal evidence from this comparison, we suggest avenues for further improvements. Keywords: Automated developer tests; Continuous Integration; Spectrum based fault localisation; Statistical debugging