James Heires's blog

Quantitative Software Management (QSM) consultant, James Heires, recently discussed the benefits of estimating and forecasting software reliability at RAMS (Reliability & Maintainability Symposium) 2023.  Theme for the conference:  "Artificial Intelligence and Machine Learning (AI/ML) application to our R&M tools, techniques, and processes (and products) promises speed and scale.... When program management instantiates advanced techniques into R&M engineering activities, such as digital design and machine learning and other advanced analytics, it enables products to evolve at a much more proactive, effective, and cost-efficient approach.  Ultimately it facilitates increased speed to market, adoption of new technology, and especially for repairable systems, products that are more reliable, maintainable, and supportable."

“I'm sorry, Dave. I'm afraid I can't do that” – HAL 9000^[1]

Source lines of code (SLOC) is a measure of software size, in use since the 1960s. This blog post describes various uses of SLOC from the perspective of software measurement.

There seems to be a love/hate relationship with the line of code measure. Despite its broad and continuous use (or perhaps because of it) SLOC seems to get the blame for many a failed software project, process improvement or software metrics initiative. There are even those who claim that “…in many situations usage of LOC metrics can be viewed as professional malpractice…”^[2] But, as you will see, SLOC has many benefits, when used intelligently.