- Jun 2, 2008
1.6 The Benefits of Detecting Software Security Defects Early5
Limited data is available that discusses the return on investment (ROI) of reducing security flaws in source code (refer to Section 1.6.1 for more on this subject). Nevertheless, a number of studies have shown that significant cost benefits are realized through improvements to reduce software defects (including security flaws) throughout the SDLC [Goldenson 2003]. The general software quality case is made in this section, including reasonable arguments for extending this case to include software security defects.
Proactively tackling software security is often under-budgeted and dismissed as a luxury. In an attempt to shorten development schedules or decrease costs, software project managers often reduce the time spent on secure software practices during requirements analysis and design. In addition, they often try to compress the testing schedule or reduce the level of effort. Skimping on software quality6 is one of the worst decisions an organization that wants to maximize development speed can make; higher quality (in the form of lower defect rates) and reduced development time go hand in hand. Figure 1-3 illustrates the relationship between defect rate and development time.
Figure 1-3 Relationship between defect rate and development time
Projects that achieve lower defect rates typically have shorter schedules. But many organizations currently develop software with defect levels that result in longer schedules than necessary. In the 1970s, studies performed by IBM demonstrated that software products with lower defect counts also had shorter development schedules [Jones 1991]. After surveying more than 4000 software projects, Capers Jones  reported that poor quality was one of the most common reasons for schedule overruns. He also reported that poor quality was a significant factor in approximately 50 percent of all canceled projects. A Software Engineering Institute survey found that more than 60 percent of organizations assessed suffered from inadequate quality assurance [Kitson 1993]. On the curve in Figure 1-3, the organizations that experienced higher numbers of defects are to the left of the "95 percent defect removal" line.
The "95 percent defect removal" line is significant because that level of prerelease defect removal appears to be the point at which projects achieve the shortest schedules for the least effort and with the highest levels of user satisfaction [Jones 1991]. If more than 5 percent of defects are found after a product has been released, then the product is vulnerable to the problems associated with low quality, and the organization takes longer to develop its software than necessary. Projects that are completed with undue haste are particularly vulnerable to shortchanging quality assurance at the individual developer level. Any developer who has been pushed to satisfy a specific deadline or ship a product quickly knows how much pressure there can be to cut corners because "we're only three weeks from the deadline." As many as four times the average number of defects are reported for released software products that were developed under excessive schedule pressure. Developers participating in projects that are in schedule trouble often become obsessed with working harder rather than working smarter, which gets them into even deeper schedule trouble.
One aspect of quality assurance that is particularly relevant during rapid development is the presence of error-prone modules—that is, modules that are responsible for a disproportionate number of defects. Barry Boehm reported that 20 percent of the modules in a program are typically responsible for 80 percent of the errors [Boehm 1987]. On its IMS project, IBM found that 57 percent of the errors occurred in 7 percent of the modules [Jones 1991]. Modules with such high defect rates are more expensive and time-consuming to deliver than less error-prone modules. Normal modules cost about $500 to $1000 per function point to develop, whereas error-prone modules cost about $2000 to $4000 per function point to develop [Jones 1994]. Error-prone modules tend to be more complex, less structured, and significantly larger than other modules. They often are developed under excessive schedule pressure and are not fully tested. If development speed is important, then identification and redesign of error-prone modules should be a high priority.
If an organization can prevent defects or detect and remove them early, it can realize significant cost and schedule benefits. Studies have found that reworking defective requirements, design, and code typically accounts for 40 to 50 percent of the total cost of software development [Jones 1986b]. As a rule of thumb, every hour an organization spends on defect prevention reduces repair time for a system in production by three to ten hours. In the worst case, reworking a software requirements problem once the software is in operation typically costs 50 to 200 times what it would take to rework the same problem during the requirements phase [Boehm 1988]. It is easy to understand why this phenomenon occurs. For example, a one-sentence requirement could expand into 5 pages of design diagrams, then into 500 lines of code, then into 15 pages of user documentation and a few dozen test cases. It is cheaper to correct an error in that one-sentence requirement at the time requirements are specified (assuming the error can be identified and corrected) than it is after design, code, user documentation, and test cases have been written. Figure 1-4 illustrates that the longer defects persist, the more expensive they are to correct.
Figure 1-4 Cost of correcting defects by life-cycle phase
The savings potential from early defect detection is significant: Approximately 60 percent of all defects usually exist by design time [Gilb 1988]. A decision early in a project to exclude defect detection amounts to a decision to postpone defect detection and correction until later in the project, when defects become much more expensive and time-consuming to address. That is not a rational decision when time and development dollars are at a premium. According to software quality assurance empirical research, $1 required to resolve an issue during the design phase grows into $60 to $100 required to resolve the same issue after the application has shipped [Soo Hoo 2001].
When a software product has too many defects, including security flaws, vulnerabilities, and bugs, software engineers can end up spending more time correcting these problems than they spent on developing the software in the first place. Project managers can achieve the shortest possible schedules with a higher-quality product by addressing security throughout the SDLC, especially during the early phases, to increase the likelihood that software is more secure the first time.
1.6.1 Making the Business Case for Software Security: Current State7
As software project managers and developers, we know that when we want to introduce new approaches in our development processes, we have to make a cost–benefit argument to executive management to convince them that this move offers a business or strategic return on investment. Executives are not interested in investing in new technical approaches simply because they are innovative or exciting. For profit-making organizations, we need to make a case that demonstrates we will improve market share, profit, or other business elements. For other types of organizations, we need to show that we will improve our software in a way that is important—in a way that adds to the organization's prestige, that ensures the safety of troops in the battlefield, and so on.
In the area of software security, we have started to see some evidence of successful ROI or economic arguments for security administrative operations, such as maintaining current levels of patches, establishing organizational entities such as computer security incident response teams (CSIRTs) to support security investment, and so on [Blum 2006, Gordon 2006, Huang 2006, Nagaratnam 2005]. In their article "Tangible ROI through Secure Software Engineering," Kevin Soo Hoo and his colleagues at @stake state the following:
- Findings indicate that significant cost savings and other advantages are achieved when security analysis and secure engineering practices are introduced early in the development cycle. The return on investment ranges from 12 percent to 21 percent, with the highest rate of return occurring when analysis is performed during application design.
- Since nearly three-quarters of security-related defects are design issues that could be resolved inexpensively during the early stages, a significant opportunity for cost savings exists when secure software engineering principles are applied during design.
However, except for a few studies [Berinato 2002; Soo Hoo 2001], we have seen little evidence presented to support the idea that investment during software development in software security will result in commensurate benefits across the entire life cycle.
Results of the Hoover project [Jaquith 2002] provide some case study data that supports the ROI argument for investment in software security early in software development. In his article "The Security of Applications: Not All Are Created Equal," Jaquith says that "the best-designed e-business applications have one-quarter as many security defects as the worst. By making the right investments in application security, companies can out-perform their peers—and reduce risk by 80 percent."
In their article "Impact of Software Vulnerability Announcements on the Market Value of Software Vendors: An Empirical Investigation," the authors state that "On average, a vendor loses around 0.6 percent value in stock price when a vulnerability is reported. This is equivalent to a loss in market capitalization values of $0.86 billion per vulnerability announcement." The purpose of the study described in this article is "to measure vendors' incentive to develop secure software" [Telang 2004].
We believe that in the future Microsoft may well publish data reflecting the results of using its Security Development Lifecycle [Howard 2006, 2007]. We would also refer readers to the business context discussion in chapter 2 and the business climate discussion in chapter 10 of McGraw's recent book [McGraw 2006] for ideas.